Patent Grant
12009095
The present disclosure relates to various surgical systems. Surgical procedures are typically performed in surgical operating theaters or rooms in a healthcare facility such as, for example, a hospital. A sterile field is typically created around the patient. The sterile field may include the scrubbed team members, who are properly attired, and all furniture and fixtures in the area. Various surgical devices and systems are utilized in performance of a surgical procedure.
In one general aspect, a computer system configured to be communicably coupled to a plurality of surgical devices. The computer system comprises a processor and a memory coupled to the processor. The memory stores instructions that, when executed by the processor, cause the computer system to: determine which of the plurality of surgical devices are utilized during a surgical procedure based at least in part on perioperative data received from the one or more of the plurality of surgical devices; determine whether each of the plurality of surgical devices utilized during the surgical procedure is a reusable surgical device or a non-reusable surgical device; determine a maintenance cost for each reusable surgical device; determine a replacement cost for each non-reusable surgical device; and determine a total cost of the plurality of surgical devices for the surgical procedure according to the maintenance cost for each reusable surgical device and the replacement cost for each non-reusable surgical device.
In another general aspect, a computer system comprising a processor and a memory coupled to the processor. The memory stores instructions that, when executed by the processor, cause the computer system to: identify one or more surgical devices utilized during a surgical procedure according to perioperative data received from the one or more surgical devices; and determine a total cost of the one or more surgical devices for the surgical procedure according to a maintenance cost or a replacement cost associated with each of the one or more surgical devices.
In yet another general aspect, a computer-implemented method for determining a surgical device cost for a surgical procedure. The method comprises: determining, by a computer system, which of a plurality of surgical devices are utilized during the surgical procedure based at least in part on perioperative data received from one or more of the plurality of surgical devices; determining, by the computer system, whether each of the plurality of surgical devices utilized during the surgical procedure is a reusable surgical device or a non-reusable surgical device; determining, by the computer system, a maintenance cost for each reusable surgical device; determining, by the computer system, a replacement cost for each non-reusable surgical device; and determining, by the computer system, a total cost of the plurality of surgical devices for the surgical procedure according to the maintenance cost for each reusable surgical device and the replacement cost for each non-reusable surgical device.
In yet another general aspect, a surgical system is disclosed comprising a plurality of surgical devices distributed across a plurality of medical facilities and a surgical hub configured to be communicably coupled to the plurality of surgical devices. Each surgical device of the plurality of surgical devices is configured to generate and transmit signals. The surgical hub comprises a processor and a memory coupled to the processor. The memory storing instructions that, when executed by the processor, cause the surgical system to detect a connection of a first surgical device of the plurality of surgical devices in a first medical facility of the plurality of medical facilities, receive operational parameters associated with a historical use of the first surgical device, generate a control program update for the first surgical device based on the received operational parameters, detect a connection of a second surgical device of the plurality of surgical devices in a second medical facility of the plurality of medical facilities, and implement the control program update via the second surgical device to improve a surgical outcome associated with a use of the second surgical device. The control program update is determined to improve a surgical outcome associated with a use of the first surgical device.
In yet another general aspect, a surgical system is disclosed comprising a plurality of surgical devices distributed across a plurality of medical facilities and a surgical hub configured to be communicably coupled to the plurality of surgical devices. Rach surgical device of the plurality of surgical devices is configured to generate and transmit signals. The surgical hub comprises a processor and a memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the surgical system to detect a connection of a first surgical device of the plurality of surgical devices in a first medical facility of the plurality of medical facilities, receive operational parameters associated with a historical use of the first surgical device, generate a control program update for the first surgical device based on the received operational parameters, and implement the control program update via the first surgical device to improve a future surgical outcome associated with a use of the first surgical device. The control program update is determined to improve the future surgical outcome associated with a use of the first surgical device.
In yet another general aspect, a computer-implemented method for generating a control program update to improve a surgical outcome associated with a plurality of surgical devices distributed across a plurality of medical facilities is disclosed. The plurality of surgical devices are configured for use during a surgical procedure. The method comprises detecting a connection of a first surgical device of the plurality of surgical devices in a first medical facility of the plurality of medical facilities, receiving operational parameters associated with a historical use of the first surgical device, generating a control program update for the first surgical device based on the received operational parameters, and implementing the control program update via the first surgical device to improve a future surgical outcome associated with a use of the first surgical device. The control program update is determined to improve the future surgical outcome associated with the use of the first surgical device.
The various aspects described herein, both as to organization and methods of operation, together with further objects and advantages thereof, may best be understood by reference to the following description, taken in conjunction with the accompanying drawings as follows.
Applicant of the present application owns the following U.S. Patent Applications, filed on Nov. 6, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Patent Applications, filed on Sep. 10, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Patent Applications, filed on Aug. 28, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Patent Applications, filed on Aug. 23, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Patent Applications, filed on Jun. 30, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Patent Applications, filed on Jun. 29, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional Patent Applications, filed on Jun. 28, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional Patent Application, filed on Apr. 19, 2018, the disclosure of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional Patent Applications, filed on Mar. 30, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Patent Applications, filed on Mar. 29, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional Patent Applications, filed on Mar. 28, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional Patent Applications, filed on Mar. 8, 2018, the disclosure of each of which is herein incorporated by reference in its entirety:
Applicant of the present application owns the following U.S. Provisional Patent Applications, filed on Dec. 28, 2017, the disclosure of each of which is herein incorporated by reference in its entirety:
Before explaining various aspects of surgical devices and generators in detail, it should be noted that the illustrative examples are not limited in application or use to the details of construction and arrangement of parts illustrated in the accompanying drawings and description. The illustrative examples may be implemented or incorporated in other aspects, variations and modifications, and may be practiced or carried out in various ways. Further, unless otherwise indicated, the terms and expressions employed herein have been chosen for the purpose of describing the illustrative examples for the convenience of the reader and are not for the purpose of limitation thereof. Also, it will be appreciated that one or more of the following-described aspects, expressions of aspects, and/or examples, can be combined with any one or more of the other following-described aspects, expressions of aspects and/or examples.
Referring to
Other types of robotic systems can be readily adapted for use with the surgical system 102. Various examples of robotic systems and surgical tools that are suitable for use with the present disclosure are described in U.S. Provisional Patent Application Ser. No. 62/611,339, titled ROBOT ASSISTED SURGICAL PLATFORM, filed Dec. 28, 2017, the disclosure of which is herein incorporated by reference in its entirety.
Various examples of cloud-based analytics that are performed by the cloud 104, and are suitable for use with the present disclosure, are described in U.S. Provisional Patent Application Ser. No. 62/611,340, titled CLOUD-BASED MEDICAL ANALYTICS, filed Dec. 28, 2017, the disclosure of which is herein incorporated by reference in its entirety.
In various aspects, the imaging device 124 includes at least one image sensor and one or more optical components. Suitable image sensors include, but are not limited to, Charge-Coupled Device (CCD) sensors and Complementary Metal-Oxide Semiconductor (CMOS) sensors.
The optical components of the imaging device 124 may include one or more illumination sources and/or one or more lenses. The one or more illumination sources may be directed to illuminate portions of the surgical field. The one or more image sensors may receive light reflected or refracted from the surgical field, including light reflected or refracted from tissue and/or surgical instruments.
The one or more illumination sources may be configured to radiate electromagnetic energy in the visible spectrum as well as the invisible spectrum. The visible spectrum, sometimes referred to as the optical spectrum or luminous spectrum, is that portion of the electromagnetic spectrum that is visible to (i.e., can be detected by) the human eye and may be referred to as visible light or simply light. A typical human eye will respond to wavelengths in air that are from about 380 nm to about 750 nm.
The invisible spectrum (i.e., the non-luminous spectrum) is that portion of the electromagnetic spectrum that lies below and above the visible spectrum (i.e., wavelengths below about 380 nm and above about 750 nm). The invisible spectrum is not detectable by the human eye. Wavelengths greater than about 750 nm are longer than the red visible spectrum, and they become invisible infrared (IR), microwave, and radio electromagnetic radiation. Wavelengths less than about 380 nm are shorter than the violet spectrum, and they become invisible ultraviolet, x-ray, and gamma ray electromagnetic radiation.
In various aspects, the imaging device 124 is configured for use in a minimally invasive procedure. Examples of imaging devices suitable for use with the present disclosure include, but not limited to, an arthroscope, angioscope, bronchoscope, choledochoscope, colonoscope, cytoscope, duodenoscope, enteroscope, esophagogastro-duodenoscope (gastroscope), endoscope, laryngoscope, nasopharyngo-neproscope, sigmoidoscope, thoracoscope, and ureteroscope.
In one aspect, the imaging device employs multi-spectrum monitoring to discriminate topography and underlying structures. A multi-spectral image is one that captures image data within specific wavelength ranges across the electromagnetic spectrum. The wavelengths may be separated by filters or by the use of instruments that are sensitive to particular wavelengths, including light from frequencies beyond the visible light range, e.g., IR and ultraviolet. Spectral imaging can allow extraction of additional information the human eye fails to capture with its receptors for red, green, and blue. The use of multi-spectral imaging is described in greater detail under the heading “Advanced Imaging Acquisition Module” in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, the disclosure of which is herein incorporated by reference in its entirety. Multi-spectrum monitoring can be a useful tool in relocating a surgical field after a surgical task is completed to perform one or more of the previously described tests on the treated tissue.
It is axiomatic that strict sterilization of the operating room and surgical equipment is required during any surgery. The strict hygiene and sterilization conditions required in a “surgical theater,” i.e., an operating or treatment room, necessitate the highest possible sterility of all medical devices and equipment. Part of that sterilization process is the need to sterilize anything that comes in contact with the patient or penetrates the sterile field, including the imaging device 124 and its attachments and components. It will be appreciated that the sterile field may be considered a specified area, such as within a tray or on a sterile towel, that is considered free of microorganisms, or the sterile field may be considered an area, immediately around a patient, who has been prepared for a surgical procedure. The sterile field may include the scrubbed team members, who are properly attired, and all furniture and fixtures in the area.
In various aspects, the visualization system 108 includes one or more imaging sensors, one or more image-processing units, one or more storage arrays, and one or more displays that are strategically arranged with respect to the sterile field, as illustrated in
As illustrated in
In one aspect, the hub 106 is also configured to route a diagnostic input or feedback entered by a non-sterile operator at the visualization tower 111 to the primary display 119 within the sterile field, where it can be viewed by a sterile operator at the operating table. In one example, the input can be in the form of a modification to the snapshot displayed on the non-sterile display 107 or 109, which can be routed to the primary display 119 by the hub 106.
Referring to
Referring now to
During a surgical procedure, energy application to tissue, for sealing and/or cutting, is generally associated with smoke evacuation, suction of excess fluid, and/or irrigation of the tissue. Fluid, power, and/or data lines from different sources are often entangled during the surgical procedure. Valuable time can be lost addressing this issue during a surgical procedure. Detangling the lines may necessitate disconnecting the lines from their respective modules, which may require resetting the modules. The hub modular enclosure 136 offers a unified environment for managing the power, data, and fluid lines, which reduces the frequency of entanglement between such lines.
Aspects of the present disclosure present a surgical hub for use in a surgical procedure that involves energy application to tissue at a surgical site. The surgical hub includes a hub enclosure and a combo generator module slidably receivable in a docking station of the hub enclosure. The docking station includes data and power contacts. The combo generator module includes two or more of an ultrasonic energy generator component, a bipolar RF energy generator component, and a monopolar RF energy generator component that are housed in a single unit. In one aspect, the combo generator module also includes a smoke evacuation component, at least one energy delivery cable for connecting the combo generator module to a surgical instrument, at least one smoke evacuation component configured to evacuate smoke, fluid, and/or particulates generated by the application of therapeutic energy to the tissue, and a fluid line extending from the remote surgical site to the smoke evacuation component.
In one aspect, the fluid line is a first fluid line and a second fluid line extends from the remote surgical site to a suction and irrigation module slidably received in the hub enclosure. In one aspect, the hub enclosure comprises a fluid interface.
Certain surgical procedures may require the application of more than one energy type to the tissue. One energy type may be more beneficial for cutting the tissue, while another different energy type may be more beneficial for sealing the tissue. For example, a bipolar generator can be used to seal the tissue while an ultrasonic generator can be used to cut the sealed tissue. Aspects of the present disclosure present a solution where a hub modular enclosure 136 is configured to accommodate different generators, and facilitate an interactive communication therebetween. One of the advantages of the hub modular enclosure 136 is enabling the quick removal and/or replacement of various modules.
Aspects of the present disclosure present a modular surgical enclosure for use in a surgical procedure that involves energy application to tissue. The modular surgical enclosure includes a first energy-generator module, configured to generate a first energy for application to the tissue, and a first docking station comprising a first docking port that includes first data and power contacts, wherein the first energy-generator module is slidably movable into an electrical engagement with the power and data contacts and wherein the first energy-generator module is slidably movable out of the electrical engagement with the first power and data contacts,
Further to the above, the modular surgical enclosure also includes a second energy-generator module configured to generate a second energy, different than the first energy, for application to the tissue, and a second docking station comprising a second docking port that includes second data and power contacts, wherein the second energy-generator module is slidably movable into an electrical engagement with the power and data contacts, and wherein the second energy-generator module is slidably movable out of the electrical engagement with the second power and data contacts.
In addition, the modular surgical enclosure also includes a communication bus between the first docking port and the second docking port, configured to facilitate communication between the first energy-generator module and the second energy-generator module.
Referring to
In one aspect, the hub modular enclosure 136 comprises a modular power and communication backplane 149 with external and wireless communication headers to enable the removable attachment of the modules 140, 126, 128 and interactive communication therebetween.
In one aspect, the hub modular enclosure 136 includes docking stations, or drawers, 151, herein also referred to as drawers, which are configured to slidably receive the modules 140, 126, 128.
In various aspects, the smoke evacuation module 126 includes a fluid line 154 that conveys captured/collected smoke and/or fluid away from a surgical site and to, for example, the smoke evacuation module 126. Vacuum suction originating from the smoke evacuation module 126 can draw the smoke into an opening of a utility conduit at the surgical site. The utility conduit, coupled to the fluid line, can be in the form of a flexible tube terminating at the smoke evacuation module 126. The utility conduit and the fluid line define a fluid path extending toward the smoke evacuation module 126 that is received in the hub enclosure 136.
In various aspects, the suction/irrigation module 128 is coupled to a surgical tool comprising an aspiration fluid line and a suction fluid line. In one example, the aspiration and suction fluid lines are in the form of flexible tubes extending from the surgical site toward the suction/irrigation module 128. One or more drive systems can be configured to cause irrigation and aspiration of fluids to and from the surgical site.
In one aspect, the surgical tool includes a shaft having an end effector at a distal end thereof and at least one energy treatment associated with the end effector, an aspiration tube, and an irrigation tube. The aspiration tube can have an inlet port at a distal end thereof and the aspiration tube extends through the shaft. Similarly, an irrigation tube can extend through the shaft and can have an inlet port in proximity to the energy deliver implement. The energy deliver implement is configured to deliver ultrasonic and/or RF energy to the surgical site and is coupled to the generator module 140 by a cable extending initially through the shaft.
The irrigation tube can be in fluid communication with a fluid source, and the aspiration tube can be in fluid communication with a vacuum source. The fluid source and/or the vacuum source can be housed in the suction/irrigation module 128. In one example, the fluid source and/or the vacuum source can be housed in the hub enclosure 136 separately from the suction/irrigation module 128. In such example, a fluid interface can be configured to connect the suction/irrigation module 128 to the fluid source and/or the vacuum source.
In one aspect, the modules 140, 126, 128 and/or their corresponding docking stations on the hub modular enclosure 136 may include alignment features that are configured to align the docking ports of the modules into engagement with their counterparts in the docking stations of the hub modular enclosure 136. For example, as illustrated in
In some aspects, the drawers 151 of the hub modular enclosure 136 are the same, or substantially the same size, and the modules are adjusted in size to be received in the drawers 151. For example, the side brackets 155 and/or 156 can be larger or smaller depending on the size of the module. In other aspects, the drawers 151 are different in size and are each designed to accommodate a particular module.
Furthermore, the contacts of a particular module can be keyed for engagement with the contacts of a particular drawer to avoid inserting a module into a drawer with mismatching contacts.
As illustrated in
In various aspects, the imaging module 138 comprises an integrated video processor and a modular light source and is adapted for use with various imaging devices. In one aspect, the imaging device is comprised of a modular housing that can be assembled with a light source module and a camera module. The housing can be a disposable housing. In at least one example, the disposable housing is removably coupled to a reusable controller, a light source module, and a camera module. The light source module and/or the camera module can be selectively chosen depending on the type of surgical procedure. In one aspect, the camera module comprises a CCD sensor. In another aspect, the camera module comprises a CMOS sensor. In another aspect, the camera module is configured for scanned beam imaging. Likewise, the light source module can be configured to deliver a white light or a different light, depending on the surgical procedure.
During a surgical procedure, removing a surgical device from the surgical field and replacing it with another surgical device that includes a different camera or a different light source can be inefficient. Temporarily losing sight of the surgical field may lead to undesirable consequences. The module imaging device of the present disclosure is configured to permit the replacement of a light source module or a camera module midstream during a surgical procedure, without having to remove the imaging device from the surgical field.
In one aspect, the imaging device comprises a tubular housing that includes a plurality of channels. A first channel is configured to slidably receive the camera module, which can be configured for a snap-fit engagement with the first channel. A second channel is configured to slidably receive the light source module, which can be configured for a snap-fit engagement with the second channel. In another example, the camera module and/or the light source module can be rotated into a final position within their respective channels. A threaded engagement can be employed in lieu of the snap-fit engagement.
In various examples, multiple imaging devices are placed at different positions in the surgical field to provide multiple views. The imaging module 138 can be configured to switch between the imaging devices to provide an optimal view. In various aspects, the imaging module 138 can be configured to integrate the images from the different imaging device.
Various image processors and imaging devices suitable for use with the present disclosure are described in U.S. Pat. No. 7,995,045, titled COMBINED SBI AND CONVENTIONAL IMAGE PROCESSOR, which issued on Aug. 9, 2011, which is herein incorporated by reference in its entirety. In addition, U.S. Pat. No. 7,982,776, titled SBI MOTION ARTIFACT REMOVAL APPARATUS AND METHOD, which issued on Jul. 19, 2011, which is herein incorporated by reference in its entirety, describes various systems for removing motion artifacts from image data. Such systems can be integrated with the imaging module 138. Furthermore, U.S. Patent Application Publication No. 2011/0306840, titled CONTROLLABLE MAGNETIC SOURCE TO FIXTURE INTRACORPOREAL APPARATUS, which published on Dec. 15, 2011, and U.S. Patent Application Publication No. 2014/0243597, titled SYSTEM FOR PERFORMING A MINIMALLY INVASIVE SURGICAL PROCEDURE, which published on Aug. 28, 2014, each of which is herein incorporated by reference in its entirety.
Modular devices 1a-1n located in the operating theater may be coupled to the modular communication hub 203. The network hub 207 and/or the network switch 209 may be coupled to a network router 211 to connect the devices 1a-1n to the cloud 204 or the local computer system 210. Data associated with the devices 1a-1n may be transferred to cloud-based computers via the router for remote data processing and manipulation. Data associated with the devices 1a-1n may also be transferred to the local computer system 210 for local data processing and manipulation. Modular devices 2a-2m located in the same operating theater also may be coupled to a network switch 209. The network switch 209 may be coupled to the network hub 207 and/or the network router 211 to connect to the devices 2a-2m to the cloud 204. Data associated with the devices 2a-2n may be transferred to the cloud 204 via the network router 211 for data processing and manipulation. Data associated with the devices 2a-2m may also be transferred to the local computer system 210 for local data processing and manipulation.
It will be appreciated that the surgical data network 201 may be expanded by interconnecting multiple network hubs 207 and/or multiple network switches 209 with multiple network routers 211. The modular communication hub 203 may be contained in a modular control tower configured to receive multiple devices 1a-1n/2a-2m. The local computer system 210 also may be contained in a modular control tower. The modular communication hub 203 is connected to a display 212 to display images obtained by some of the devices 1a-1n/2a-2m, for example during surgical procedures. In various aspects, the devices 1a-1n/2a-2m may include, for example, various modules such as an imaging module 138 coupled to an endoscope, a generator module 140 coupled to an energy-based surgical device, a smoke evacuation module 126, a suction/irrigation module 128, a communication module 130, a processor module 132, a storage array 134, a surgical device coupled to a display, and/or a non-contact sensor module, among other modular devices that may be connected to the modular communication hub 203 of the surgical data network 201.
In one aspect, the surgical data network 201 may comprise a combination of network hub(s), network switch(es), and network router(s) connecting the devices 1a-1n/2a-2m to the cloud. Any one of or all of the devices 1a-1n/2a-2m coupled to the network hub or network switch may collect data in real time and transfer the data to cloud computers for data processing and manipulation. It will be appreciated that cloud computing relies on sharing computing resources rather than having local servers or personal devices to handle software applications. The word “cloud” may be used as a metaphor for “the Internet,” although the term is not limited as such. Accordingly, the term “cloud computing” may be used herein to refer to “a type of Internet-based computing,” where different services—such as servers, storage, and applications—are delivered to the modular communication hub 203 and/or computer system 210 located in the surgical theater (e.g., a fixed, mobile, temporary, or field operating room or space) and to devices connected to the modular communication hub 203 and/or computer system 210 through the Internet. The cloud infrastructure may be maintained by a cloud service provider. In this context, the cloud service provider may be the entity that coordinates the usage and control of the devices 1a-1n/2a-2m located in one or more operating theaters. The cloud computing services can perform a large number of calculations based on the data gathered by smart surgical instruments, robots, and other computerized devices located in the operating theater. The hub hardware enables multiple devices or connections to be connected to a computer that communicates with the cloud computing resources and storage.
Applying cloud computer data processing techniques on the data collected by the devices 1a-1n/2a-2m, the surgical data network provides improved surgical outcomes, reduced costs, and improved patient satisfaction. At least some of the devices 1a-1n/2a-2m may be employed to view tissue states to assess leaks or perfusion of sealed tissue after a tissue sealing and cutting procedure. At least some of the devices 1a-1n/2a-2m may be employed to identify pathology, such as the effects of diseases, using the cloud-based computing to examine data including images of samples of body tissue for diagnostic purposes. This includes localization and margin confirmation of tissue and phenotypes. At least some of the devices 1a-1n/2a-2m may be employed to identify anatomical structures of the body using a variety of sensors integrated with imaging devices and techniques such as overlaying images captured by multiple imaging devices. The data gathered by the devices 1a-1n/2a-2m, including image data, may be transferred to the cloud 204 or the local computer system 210 or both for data processing and manipulation including image processing and manipulation. The data may be analyzed to improve surgical procedure outcomes by determining if further treatment, such as the application of endoscopic intervention, emerging technologies, a targeted radiation, targeted intervention, and precise robotics to tissue-specific sites and conditions, may be pursued. Such data analysis may further employ outcome analytics processing, and using standardized approaches may provide beneficial feedback to either confirm surgical treatments and the behavior of the surgeon or suggest modifications to surgical treatments and the behavior of the surgeon.
In one implementation, the operating theater devices 1a-1n may be connected to the modular communication hub 203 over a wired channel or a wireless channel depending on the configuration of the devices 1a-1n to a network hub. The network hub 207 may be implemented, in one aspect, as a local network broadcast device that works on the physical layer of the Open System Interconnection (OSI) model. The network hub provides connectivity to the devices 1a-1n located in the same operating theater network. The network hub 207 collects data in the form of packets and sends them to the router in half duplex mode. The network hub 207 does not store any media access control/Internet Protocol (MAC/IP) to transfer the device data. Only one of the devices 1a-1n can send data at a time through the network hub 207. The network hub 207 has no routing tables or intelligence regarding where to send information and broadcasts all network data across each connection and to a remote server 213 (
In another implementation, the operating theater devices 2a-2m may be connected to a network switch 209 over a wired channel or a wireless channel. The network switch 209 works in the data link layer of the OSI model. The network switch 209 is a multicast device for connecting the devices 2a-2m located in the same operating theater to the network. The network switch 209 sends data in the form of frames to the network router 211 and works in full duplex mode. Multiple devices 2a-2m can send data at the same time through the network switch 209. The network switch 209 stores and uses MAC addresses of the devices 2a-2m to transfer data.
The network hub 207 and/or the network switch 209 are coupled to the network router 211 for connection to the cloud 204. The network router 211 works in the network layer of the OSI model. The network router 211 creates a route for transmitting data packets received from the network hub 207 and/or network switch 211 to cloud-based computer resources for further processing and manipulation of the data collected by any one of or all the devices 1a-1n/2a-2m. The network router 211 may be employed to connect two or more different networks located in different locations, such as, for example, different operating theaters of the same healthcare facility or different networks located in different operating theaters of different healthcare facilities. The network router 211 sends data in the form of packets to the cloud 204 and works in full duplex mode. Multiple devices can send data at the same time. The network router 211 uses IP addresses to transfer data.
In one example, the network hub 207 may be implemented as a USB hub, which allows multiple USB devices to be connected to a host computer. The USB hub may expand a single USB port into several tiers so that there are more ports available to connect devices to the host system computer. The network hub 207 may include wired or wireless capabilities to receive information over a wired channel or a wireless channel. In one aspect, a wireless USB short-range, high-bandwidth wireless radio communication protocol may be employed for communication between the devices 1a-1n and devices 2a-2m located in the operating theater.
In other examples, the operating theater devices 1a-1n/2a-2m may communicate to the modular communication hub 203 via Bluetooth wireless technology standard for exchanging data over short distances (using short-wavelength UHF radio waves in the ISM band from 2.4 to 2.485 GHz) from fixed and mobile devices and building personal area networks (PANs). In other aspects, the operating theater devices 1a-1n/2a-2m may communicate to the modular communication hub 203 via a number of wireless or wired communication standards or protocols, including but not limited to Wi-Fi (IEEE 802.11 family), WiMAX (IEEE 802.16 family), IEEE 802.20, long-term evolution (LTE), and Ev-DO, HSPA+, HSDPA+, HSUPA+, EDGE, GSM, GPRS, CDMA, TDMA, DECT, and Ethernet derivatives thereof, as well as any other wireless and wired protocols that are designated as 3G, 4G, 5G, and beyond. The computing module may include a plurality of communication modules. For instance, a first communication module may be dedicated to shorter-range wireless communications such as Wi-Fi and Bluetooth, and a second communication module may be dedicated to longer-range wireless communications such as GPS, EDGE, GPRS, CDMA, WiMAX, LTE, Ev-DO, and others.
The modular communication hub 203 may serve as a central connection for one or all of the operating theater devices 1a-1n/2a-2m and handles a data type known as frames. Frames carry the data generated by the devices 1a-1n/2a-2m. When a frame is received by the modular communication hub 203, it is amplified and transmitted to the network router 211, which transfers the data to the cloud computing resources by using a number of wireless or wired communication standards or protocols, as described herein.
The modular communication hub 203 can be used as a standalone device or be connected to compatible network hubs and network switches to form a larger network. The modular communication hub 203 is generally easy to install, configure, and maintain, making it a good option for networking the operating theater devices 1a-1n/2a-2m.
The surgical hub 206 employs a non-contact sensor module 242 to measure the dimensions of the operating theater and generate a map of the surgical theater using either ultrasonic or laser-type non-contact measurement devices. An ultrasound-based non-contact sensor module scans the operating theater by transmitting a burst of ultrasound and receiving the echo when it bounces off the perimeter walls of an operating theater as described under the heading “Surgical Hub Spatial Awareness Within an Operating Room” in U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, which is herein incorporated by reference in its entirety, in which the sensor module is configured to determine the size of the operating theater and to adjust Bluetooth-pairing distance limits. A laser-based non-contact sensor module scans the operating theater by transmitting laser light pulses, receiving laser light pulses that bounce off the perimeter walls of the operating theater, and comparing the phase of the transmitted pulse to the received pulse to determine the size of the operating theater and to adjust Bluetooth pairing distance limits, for example.
The computer system 210 comprises a processor 244 and a network interface 245. The processor 244 is coupled to a communication module 247, storage 248, memory 249, non-volatile memory 250, and input/output interface 251 via a system bus. The system bus can be any of several types of bus structure(s) including the memory bus or memory controller, a peripheral bus or external bus, and/or a local bus using any variety of available bus architectures including, but not limited to, 9-bit bus, Industrial Standard Architecture (ISA), Micro-Charmel Architecture (MSA), Extended ISA (EISA), Intelligent Drive Electronics (IDE), VESA Local Bus (VLB), Peripheral Component Interconnect (PCI), USB, Advanced Graphics Port (AGP), Personal Computer Memory Card International Association bus (PCMCIA), Small Computer Systems Interface (SCSI), or any other proprietary bus.
The processor 244 may be any single-core or multicore processor such as those known under the trade name ARM Cortex by Texas Instruments. In one aspect, the processor may be an LM4F230H5QR ARM Cortex-M4F Processor Core, available from Texas Instruments, for example, comprising an on-chip memory of 256 KB single-cycle flash memory, or other non-volatile memory, up to 40 MHz, a prefetch buffer to improve performance above 40 MHz, a 32 KB single-cycle serial random access memory (SRAM), an internal read-only memory (ROM) loaded with StellarisWare® software, a 2 KB electrically erasable programmable read-only memory (EEPROM), and/or one or more pulse width modulation (PWM) modules, one or more quadrature encoder inputs (QEI) analogs, one or more 12-bit analog-to-digital converters (ADCs) with 12 analog input channels, details of which are available for the product datasheet.
In one aspect, the processor 244 may comprise a safety controller comprising two controller-based families such as TMS570 and RM4x, known under the trade name Hercules ARM Cortex R4, also by Texas Instruments. The safety controller may be configured specifically for IEC 61508 and ISO 26262 safety critical applications, among others, to provide advanced integrated safety features while delivering scalable performance, connectivity, and memory options.
The system memory includes volatile memory and non-volatile memory. The basic input/output system (BIOS), containing the basic routines to transfer information between elements within the computer system, such as during start-up, is stored in non-volatile memory. For example, the non-volatile memory can include ROM, programmable ROM (PROM), electrically programmable ROM (EPROM), EEPROM, or flash memory. Volatile memory includes random-access memory (RAM), which acts as external cache memory. Moreover, RAM is available in many forms such as SRAM, dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and direct Rambus RAM (DRRAM).
The computer system 210 also includes removable/non-removable, volatile/non-volatile computer storage media, such as for example disk storage. The disk storage includes, but is not limited to, devices like a magnetic disk drive, floppy disk drive, tape drive, Jaz drive, Zip drive, LS-60 drive, flash memory card, or memory stick. In addition, the disk storage can include storage media separately or in combination with other storage media including, but not limited to, an optical disc drive such as a compact disc ROM device (CD-ROM), compact disc recordable drive (CD-R Drive), compact disc rewritable drive (CD-RW Drive), or a digital versatile disc ROM drive (DVD-ROM). To facilitate the connection of the disk storage devices to the system bus, a removable or non-removable interface may be employed.
It is to be appreciated that the computer system 210 includes software that acts as an intermediary between users and the basic computer resources described in a suitable operating environment. Such software includes an operating system. The operating system, which can be stored on the disk storage, acts to control and allocate resources of the computer system. System applications take advantage of the management of resources by the operating system through program modules and program data stored either in the system memory or on the disk storage. It is to be appreciated that various components described herein can be implemented with various operating systems or combinations of operating systems.
A user enters commands or information into the computer system 210 through input device(s) coupled to the I/O interface 251. The input devices include, but are not limited to, a pointing device such as a mouse, trackball, stylus, touch pad, keyboard, microphone, joystick, game pad, satellite dish, scanner, TV tuner card, digital camera, digital video camera, web camera, and the like. These and other input devices connect to the processor through the system bus via interface port(s). The interface port(s) include, for example, a serial port, a parallel port, a game port, and a USB. The output device(s) use some of the same types of ports as input device(s). Thus, for example, a USB port may be used to provide input to the computer system and to output information from the computer system to an output device. An output adapter is provided to illustrate that there are some output devices like monitors, displays, speakers, and printers, among other output devices that require special adapters. The output adapters include, by way of illustration and not limitation, video and sound cards that provide a means of connection between the output device and the system bus. It should be noted that other devices and/or systems of devices, such as remote computer(s), provide both input and output capabilities.
The computer system 210 can operate in a networked environment using logical connections to one or more remote computers, such as cloud computer(s), or local computers. The remote cloud computer(s) can be a personal computer, server, router, network PC, workstation, microprocessor-based appliance, peer device, or other common network node, and the like, and typically includes many or all of the elements described relative to the computer system. For purposes of brevity, only a memory storage device is illustrated with the remote computer(s). The remote computer(s) is logically connected to the computer system through a network interface and then physically connected via a communication connection. The network interface encompasses communication networks such as local area networks (LANs) and wide area networks (WANs). LAN technologies include Fiber Distributed Data Interface (FDDI), Copper Distributed Data Interface (CDDI), Ethernet/IEEE 802.3, Token Ring/IEEE 802.5 and the like. WAN technologies include, but are not limited to, point-to-point links, circuit-switching networks like Integrated Services Digital Networks (ISDN) and variations thereon, packet-switching networks, and Digital Subscriber Lines (DSL).
In various aspects, the computer system 210 of
The communication connection(s) refers to the hardware/software employed to connect the network interface to the bus. While the communication connection is shown for illustrative clarity inside the computer system, it can also be external to the computer system 210. The hardware/software necessary for connection to the network interface includes, for illustrative purposes only, internal and external technologies such as modems, including regular telephone-grade modems, cable modems, and DSL modems, ISDN adapters, and Ethernet cards.
The USB network hub 300 device is implemented with a digital state machine instead of a microcontroller, and no firmware programming is required. Fully compliant USB transceivers are integrated into the circuit for the upstream USB transceiver port 302 and all downstream USB transceiver ports 304, 306, 308. The downstream USB transceiver ports 304, 306, 308 support both full-speed and low-speed devices by automatically setting the slew rate according to the speed of the device attached to the ports. The USB network hub 300 device may be configured either in bus-powered or self-powered mode and includes a hub power logic 312 to manage power.
The USB network hub 300 device includes a serial interface engine 310 (SIE). The SIE 310 is the front end of the USB network hub 300 hardware and handles most of the protocol described in chapter 8 of the USB specification. The SIE 310 typically comprehends signaling up to the transaction level. The functions that it handles could include: packet recognition, transaction sequencing, SOP, EOP, RESET, and RESUME signal detection/generation, clock/data separation, non-return-to-zero invert (NRZI) data encoding/decoding and bit-stuffing, CRC generation and checking (token and data), packet ID (PID) generation and checking/decoding, and/or serial-parallel/parallel-serial conversion. The 310 receives a clock input 314 and is coupled to a suspend/resume logic and frame timer 316 circuit and a hub repeater circuit 318 to control communication between the upstream USB transceiver port 302 and the downstream USB transceiver ports 304, 306, 308 through port logic circuits 320, 322, 324. The SIE 310 is coupled to a command decoder 326 via interface logic 328 to control commands from a serial EEPROM via a serial EEPROM interface 330.
In various aspects, the USB network hub 300 can connect 127 functions configured in up to six logical layers (tiers) to a single computer. Further, the USB network hub 300 can connect to all peripherals using a standardized four-wire cable that provides both communication and power distribution. The power configurations are bus-powered and self-powered modes. The USB network hub 300 may be configured to support four modes of power management: a bus-powered hub, with either individual-port power management or ganged-port power management, and the self-powered hub, with either individual-port power management or ganged-port power management. In one aspect, using a USB cable, the USB network hub 300, the upstream USB transceiver port 302 is plugged into a USB host controller, and the downstream USB transceiver ports 304, 306, 308 are exposed for connecting USB compatible devices, and so forth.
Additional details regarding the structure and function of the surgical hub and/or surgical hub networks can be found in U.S. Provisional Patent Application Ser. No. 62/659,900, titled METHOD OF HUB COMMUNICATION, filed Apr. 19, 2018, which is hereby incorporated by reference herein in its entirety.
In addition, surgical instruments 7012 may comprise transceivers for data transmission to and from their corresponding surgical hubs 7006 (which may also comprise transceivers). Combinations of surgical instruments 7012 and corresponding hubs 7006 may indicate particular locations, such as operating theaters in healthcare facilities (e.g., hospitals), for providing medical operations. For example, the memory of a surgical hub 7006 may store location data. As shown in
Based on connections to various surgical hubs 7006 via the network 7001, the cloud 7004 can aggregate data from specific data generated by various surgical instruments 7012 and their corresponding hubs 7006. Such aggregated data may be stored within the aggregated medical data databases 7011 of the cloud 7004. In particular, the cloud 7004 may advantageously perform data analysis and operations on the aggregated data to yield insights and/or perform functions that individual hubs 7006 could not achieve on their own. To this end, as shown in
The particular cloud computing system configuration described in the present disclosure is specifically designed to address various issues arising in the context of medical operations and procedures performed using medical devices, such as the surgical instruments 7012, 112. In particular, the surgical instruments 7012 may be digital surgical devices configured to interact with the cloud 7004 for implementing techniques to improve the performance of surgical operations. Various surgical instruments 7012 and/or surgical hubs 7006 may comprise touch controlled user interfaces such that clinicians may control aspects of interaction between the surgical instruments 7012 and the cloud 7004. Other suitable user interfaces for control such as auditory controlled user interfaces can also be used.
For example, the data collection and aggregation module 7022 could be used to generate self-describing data (e.g., metadata) including identification of notable features or configuration (e.g., trends), management of redundant data sets, and storage of the data in paired data sets which can be grouped by surgery but not necessarily keyed to actual surgical dates and surgeons. In particular, pair data sets generated from operations of surgical instruments 7012 can comprise applying a binary classification, e.g., a bleeding or a non-bleeding event. More generally, the binary classification may be characterized as either a desirable event (e.g., a successful surgical procedure) or an undesirable event (e.g., a misfired or misused surgical instrument 7012). The aggregated self-describing data may correspond to individual data received from various groups or subgroups of surgical hubs 7006. Accordingly, the data collection and aggregation module 7022 can generate aggregated metadata or other organized data based on raw data received from the surgical hubs 7006. To this end, the processors 7008 can be operationally coupled to the hub applications 7014 and aggregated medical data databases 7011 for executing the data analytics modules 7034. The data collection and aggregation module 7022 may store the aggregated organized data into the aggregated medical data databases 2212.
The resource optimization module 7020 can be configured to analyze this aggregated data to determine an optimal usage of resources for a particular or group of healthcare facilities. For example, the resource optimization module 7020 may determine an optimal order point of surgical stapling instruments 7012 for a group of healthcare facilities based on corresponding predicted demand of such instruments 7012. The resource optimization module 7020 might also assess the resource usage or other operational configurations of various healthcare facilities to determine whether resource usage could be improved. Similarly, the recommendations module 7030 can be configured to analyze aggregated organized data from the data collection and aggregation module 7022 to provide recommendations. For example, the recommendations module 7030 could recommend to healthcare facilities (e.g., medical service providers such as hospitals) that a particular surgical instrument 7012 should be upgraded to an improved version based on a higher than expected error rate, for example. Additionally, the recommendations module 7030 and/or resource optimization module 7020 could recommend better supply chain parameters such as product reorder points and provide suggestions of different surgical instrument 7012, uses thereof, or procedure steps to improve surgical outcomes. The healthcare facilities can receive such recommendations via corresponding surgical hubs 7006. More specific recommendations regarding parameters or configurations of various surgical instruments 7012 can also be provided. Hubs 7006 and/or surgical instruments 7012 each could also have display screens that display data or recommendations provided by the cloud 7004.
The patient outcome analysis module 7028 can analyze surgical outcomes associated with currently used operational parameters of surgical instruments 7012. The patient outcome analysis module 7028 may also analyze and assess other potential operational parameters. In this connection, the recommendations module 7030 could recommend using these other potential operational parameters based on yielding better surgical outcomes, such as better sealing or less bleeding. For example, the recommendations module 7030 could transmit recommendations to a surgical hub 7006 regarding when to use a particular cartridge for a corresponding stapling surgical instrument 7012. Thus, the cloud-based analytics system, while controlling for common variables, may be configured to analyze the large collection of raw data and to provide centralized recommendations over multiple healthcare facilities (advantageously determined based on aggregated data). For example, the cloud-based analytics system could analyze, evaluate, and/or aggregate data based on type of medical practice, type of patient, number of patients, geographic similarity between medical providers, which medical providers/facilities use similar types of instruments, etc., in a way that no single healthcare facility alone would be able to analyze independently.
The control program updating module 7026 could be configured to implement various surgical instrument 7012 recommendations when corresponding control programs are updated. For example, the patient outcome analysis module 7028 could identify correlations linking specific control parameters with successful (or unsuccessful) results. Such correlations may be addressed when updated control programs are transmitted to surgical instruments 7012 via the control program updating module 7026. Updates to instruments 7012 that are transmitted via a corresponding hub 7006 may incorporate aggregated performance data that was gathered and analyzed by the data collection and aggregation module 7022 of the cloud 7004. Additionally, the patient outcome analysis module 7028 and recommendations module 7030 could identify improved methods of using instruments 7012 based on aggregated performance data.
The cloud-based analytics system may include security features implemented by the cloud 7004. These security features may be managed by the authorization and security module 7024. Each surgical hub 7006 can have associated unique credentials such as username, password, and other suitable security credentials. These credentials could be stored in the memory 7010 and be associated with a permitted cloud access level. For example, based on providing accurate credentials, a surgical hub 7006 may be granted access to communicate with the cloud to a predetermined extent (e.g., may only engage in transmitting or receiving certain defined types of information). To this end, the aggregated medical data databases 7011 of the cloud 7004 may comprise a database of authorized credentials for verifying the accuracy of provided credentials. Different credentials may be associated with varying levels of permission for interaction with the cloud 7004, such as a predetermined access level for receiving the data analytics generated by the cloud 7004.
Furthermore, for security purposes, the cloud could maintain a database of hubs 7006, instruments 7012, and other devices that may comprise a “black list” of prohibited devices. In particular, a surgical hub 7006 listed on the black list may not be permitted to interact with the cloud, while surgical instruments 7012 listed on the black list may not have functional access to a corresponding hub 7006 and/or may be prevented from fully functioning when paired to its corresponding hub 7006. Additionally or alternatively, the cloud 7004 may flag instruments 7012 based on incompatibility or other specified criteria. In this manner, counterfeit medical devices and improper reuse of such devices throughout the cloud-based analytics system can be identified and addressed.
The surgical instruments 7012 may use wireless transceivers to transmit wireless signals that may represent, for example, authorization credentials for access to corresponding hubs 7006 and the cloud 7004. Wired transceivers may also be used to transmit signals. Such authorization credentials can be stored in the respective memory devices of the surgical instruments 7012. The authorization and security module 7024 can determine whether the authorization credentials are accurate or counterfeit. The authorization and security module 7024 may also dynamically generate authorization credentials for enhanced security. The credentials could also be encrypted, such as by using hash based encryption. Upon transmitting proper authorization, the surgical instruments 7012 may transmit a signal to the corresponding hubs 7006 and ultimately the cloud 7004 to indicate that the instruments 7012 are ready to obtain and transmit medical data. In response, the cloud 7004 may transition into a state enabled for receiving medical data for storage into the aggregated medical data databases 7011. This data transmission readiness could be indicated by a light indicator on the instruments 7012, for example. The cloud 7004 can also transmit signals to surgical instruments 7012 for updating their associated control programs. The cloud 7004 can transmit signals that are directed to a particular class of surgical instruments 7012 (e.g., electrosurgical instruments) so that software updates to control programs are only transmitted to the appropriate surgical instruments 7012. Moreover, the cloud 7004 could be used to implement system wide solutions to address local or global problems based on selective data transmission and authorization credentials. For example, if a group of surgical instruments 7012 are identified as having a common manufacturing defect, the cloud 7004 may change the authorization credentials corresponding to this group to implement an operational lockout of the group.
The cloud-based analytics system may allow for monitoring multiple healthcare facilities (e.g., medical facilities like hospitals) to determine improved practices and recommend changes (via the recommendations module 2030, for example) accordingly. Thus, the processors 7008 of the cloud 7004 can analyze data associated with an individual healthcare facility to identify the facility and aggregate the data with other data associated with other healthcare facilities in a group. Groups could be defined based on similar operating practices or geographical location, for example. In this way, the cloud 7004 may provide healthcare facility group wide analysis and recommendations. The cloud-based analytics system could also be used for enhanced situational awareness. For example, the processors 7008 may predictively model the effects of recommendations on the cost and effectiveness for a particular facility (relative to overall operations and/or various medical procedures). The cost and effectiveness associated with that particular facility can also be compared to a corresponding local region of other facilities or any other comparable facilities.
The data sorting and prioritization module 7032 may prioritize and sort data based on criticality (e.g., the severity of a medical event associated with the data, unexpectedness, suspiciousness). This sorting and prioritization may be used in conjunction with the functions of the other data analytics modules 7034 described above to improve the cloud-based analytics and operations described herein. For example, the data sorting and prioritization module 7032 can assign a priority to the data analysis performed by the data collection and aggregation module 7022 and patient outcome analysis modules 7028. Different prioritization levels can result in particular responses from the cloud 7004 (corresponding to a level of urgency) such as escalation for an expedited response, special processing, exclusion from the aggregated medical data databases 7011, or other suitable responses. Moreover, if necessary, the cloud 7004 can transmit a request (e.g. a push message) through the hub application servers for additional data from corresponding surgical instruments 7012. The push message can result in a notification displayed on the corresponding hubs 7006 for requesting supporting or additional data. This push message may be required in situations in which the cloud detects a significant irregularity or outlier and the cloud cannot determine the cause of the irregularity. The central servers 7013 may be programmed to trigger this push message in certain significant circumstances, such as when data is determined to be different from an expected value beyond a predetermined threshold or when it appears security has been comprised, for example.
Additional details regarding the cloud analysis system can be found in U.S. Provisional Patent Application Ser. No. 62/659,900, titled METHOD OF HUB COMMUNICATION, filed Apr. 19, 2018, which is hereby incorporated by reference herein in its entirety.
Although an “intelligent” device including control algorithms that respond to sensed data can be an improvement over a “dumb” device that operates without accounting for sensed data, some sensed data can be incomplete or inconclusive when considered in isolation, i.e., without the context of the type of surgical procedure being performed or the type of tissue that is being operated on. Without knowing the procedural context (e.g., knowing the type of tissue being operated on or the type of procedure being performed), the control algorithm may control the modular device incorrectly or suboptimally given the particular context-free sensed data. For example, the optimal manner for a control algorithm to control a surgical instrument in response to a particular sensed parameter can vary according to the particular tissue type being operated on. This is due to the fact that different tissue types have different properties (e.g., resistance to tearing) and thus respond differently to actions taken by surgical instruments. Therefore, it may be desirable for a surgical instrument to take different actions even when the same measurement for a particular parameter is sensed. As one specific example, the optimal manner in which to control a surgical stapling and cutting instrument in response to the instrument sensing an unexpectedly high force to close its end effector will vary depending upon whether the tissue type is susceptible or resistant to tearing. For tissues that are susceptible to tearing, such as lung tissue, the instrument's control algorithm would optimally ramp down the motor in response to an unexpectedly high force to close to avoid tearing the tissue. For tissues that are resistant to tearing, such as stomach tissue, the instrument's control algorithm would optimally ramp up the motor in response to an unexpectedly high force to close to ensure that the end effector is clamped properly on the tissue. Without knowing whether lung or stomach tissue has been clamped, the control algorithm may make a suboptimal decision.
One solution utilizes a surgical hub including a system that is configured to derive information about the surgical procedure being performed based on data received from various data sources and then control the paired modular devices accordingly. In other words, the surgical hub is configured to infer information about the surgical procedure from received data and then control the modular devices paired to the surgical hub based upon the inferred context of the surgical procedure.
A surgical hub 5104, which may be similar to the hub 106 in many respects, can be configured to derive the contextual information pertaining to the surgical procedure from the data based upon, for example, the particular combination(s) of received data or the particular order in which the data is received from the data sources 5126. The contextual information inferred from the received data can include, for example, the type of surgical procedure being performed, the particular step of the surgical procedure that the surgeon is performing, the type of tissue being operated on, or the body cavity that is the subject of the procedure. This ability by some aspects of the surgical hub 5104 to derive or infer information related to the surgical procedure from received data can be referred to as “situational awareness.” In one exemplification, the surgical hub 5104 can incorporate a situational awareness system, which is the hardware and/or programming associated with the surgical hub 5104 that derives contextual information pertaining to the surgical procedure from the received data.
The situational awareness system of the surgical hub 5104 can be configured to derive the contextual information from the data received from the data sources 5126 in a variety of different ways. In one exemplification, the situational awareness system includes a pattern recognition system, or machine learning system (e.g., an artificial neural network), that has been trained on training data to correlate various inputs (e.g., data from databases 5122, patient monitoring devices 5124, and/or modular devices 5102) to corresponding contextual information regarding a surgical procedure. In other words, a machine learning system can be trained to accurately derive contextual information regarding a surgical procedure from the provided inputs. In another exemplification, the situational awareness system can include a lookup table storing pre-characterized contextual information regarding a surgical procedure in association with one or more inputs (or ranges of inputs) corresponding to the contextual information. In response to a query with one or more inputs, the lookup table can return the corresponding contextual information for the situational awareness system for controlling the modular devices 5102. In one exemplification, the contextual information received by the situational awareness system of the surgical hub 5104 is associated with a particular control adjustment or set of control adjustments for one or more modular devices 5102. In another exemplification, the situational awareness system includes a further machine learning system, lookup table, or other such system, which generates or retrieves one or more control adjustments for one or more modular devices 5102 when provided the contextual information as input.
A surgical hub 5104 incorporating a situational awareness system provides a number of benefits for the surgical system 5100. One benefit includes improving the interpretation of sensed and collected data, which would in turn improve the processing accuracy and/or the usage of the data during the course of a surgical procedure. To return to a previous example, a situationally aware surgical hub 5104 could determine what type of tissue was being operated on; therefore, when an unexpectedly high force to close the surgical instrument's end effector is detected, the situationally aware surgical hub 5104 could correctly ramp up or ramp down the motor of the surgical instrument for the type of tissue.
As another example, the type of tissue being operated can affect the adjustments that are made to the compression rate and load thresholds of a surgical stapling and cutting instrument for a particular tissue gap measurement. A situationally aware surgical hub 5104 could infer whether a surgical procedure being performed is a thoracic or an abdominal procedure, allowing the surgical hub 5104 to determine whether the tissue clamped by an end effector of the surgical stapling and cutting instrument is lung (for a thoracic procedure) or stomach (for an abdominal procedure) tissue. The surgical hub 5104 could then adjust the compression rate and load thresholds of the surgical stapling and cutting instrument appropriately for the type of tissue.
As yet another example, the type of body cavity being operated in during an insufflation procedure can affect the function of a smoke evacuator. A situationally aware surgical hub 5104 could determine whether the surgical site is under pressure (by determining that the surgical procedure is utilizing insufflation) and determine the procedure type. As a procedure type is generally performed in a specific body cavity, the surgical hub 5104 could then control the motor rate of the smoke evacuator appropriately for the body cavity being operated in. Thus, a situationally aware surgical hub 5104 could provide a consistent amount of smoke evacuation for both thoracic and abdominal procedures.
As yet another example, the type of procedure being performed can affect the optimal energy level for an ultrasonic surgical instrument or radio frequency (RF) electrosurgical instrument to operate at. Arthroscopic procedures, for example, require higher energy levels because the end effector of the ultrasonic surgical instrument or RF electrosurgical instrument is immersed in fluid. A situationally aware surgical hub 5104 could determine whether the surgical procedure is an arthroscopic procedure. The surgical hub 5104 could then adjust the RF power level or the ultrasonic amplitude of the generator (i.e., “energy level”) to compensate for the fluid filled environment. Relatedly, the type of tissue being operated on can affect the optimal energy level for an ultrasonic surgical instrument or RF electrosurgical instrument to operate at. A situationally aware surgical hub 5104 could determine what type of surgical procedure is being performed and then customize the energy level for the ultrasonic surgical instrument or RF electrosurgical instrument, respectively, according to the expected tissue profile for the surgical procedure. Furthermore, a situationally aware surgical hub 5104 can be configured to adjust the energy level for the ultrasonic surgical instrument or RF electrosurgical instrument throughout the course of a surgical procedure, rather than just on a procedure-by-procedure basis. A situationally aware surgical hub 5104 could determine what step of the surgical procedure is being performed or will subsequently be performed and then update the control algorithms for the generator and/or ultrasonic surgical instrument or RF electrosurgical instrument to set the energy level at a value appropriate for the expected tissue type according to the surgical procedure step.
As yet another example, data can be drawn from additional data sources 5126 to improve the conclusions that the surgical hub 5104 draws from one data source 5126. A situationally aware surgical hub 5104 could augment data that it receives from the modular devices 5102 with contextual information that it has built up regarding the surgical procedure from other data sources 5126. For example, a situationally aware surgical hub 5104 can be configured to determine whether hemostasis has occurred (i.e., whether bleeding at a surgical site has stopped) according to video or image data received from a medical imaging device. However, in some cases the video or image data can be inconclusive. Therefore, in one exemplification, the surgical hub 5104 can be further configured to compare a physiologic measurement (e.g., blood pressure sensed by a BP monitor communicably connected to the surgical hub 5104) with the visual or image data of hemostasis (e.g., from a medical imaging device 124 (
Another benefit includes proactively and automatically controlling the paired modular devices 5102 according to the particular step of the surgical procedure that is being performed to reduce the number of times that medical personnel are required to interact with or control the surgical system 5100 during the course of a surgical procedure. For example, a situationally aware surgical hub 5104 could proactively activate the generator to which an RF electrosurgical instrument is connected if it determines that a subsequent step of the procedure requires the use of the instrument. Proactively activating the energy source allows the instrument to be ready for use a soon as the preceding step of the procedure is completed.
As another example, a situationally aware surgical hub 5104 could determine whether the current or subsequent step of the surgical procedure requires a different view or degree of magnification on the display according to the feature(s) at the surgical site that the surgeon is expected to need to view. The surgical hub 5104 could then proactively change the displayed view (supplied by, e.g., a medical imaging device for the visualization system 108) accordingly so that the display automatically adjusts throughout the surgical procedure.
As yet another example, a situationally aware surgical hub 5104 could determine which step of the surgical procedure is being performed or will subsequently be performed and whether particular data or comparisons between data will be required for that step of the surgical procedure. The surgical hub 5104 can be configured to automatically call up data screens based upon the step of the surgical procedure being performed, without waiting for the surgeon to ask for the particular information.
Another benefit includes checking for errors during the setup of the surgical procedure or during the course of the surgical procedure. For example, a situationally aware surgical hub 5104 could determine whether the operating theater is setup properly or optimally for the surgical procedure to be performed. The surgical hub 5104 can be configured to determine the type of surgical procedure being performed, retrieve the corresponding checklists, product location, or setup needs (e.g., from a memory), and then compare the current operating theater layout to the standard layout for the type of surgical procedure that the surgical hub 5104 determines is being performed. In one exemplification, the surgical hub 5104 can be configured to compare the list of items for the procedure scanned by a suitable scanner for example and/or a list of devices paired with the surgical hub 5104 to a recommended or anticipated manifest of items and/or devices for the given surgical procedure. If there are any discontinuities between the lists, the surgical hub 5104 can be configured to provide an alert indicating that a particular modular device 5102, patient monitoring device 5124, and/or other surgical item is missing. In one exemplification, the surgical hub 5104 can be configured to determine the relative distance or position of the modular devices 5102 and patient monitoring devices 5124 via proximity sensors, for example. The surgical hub 5104 can compare the relative positions of the devices to a recommended or anticipated layout for the particular surgical procedure. If there are any discontinuities between the layouts, the surgical hub 5104 can be configured to provide an alert indicating that the current layout for the surgical procedure deviates from the recommended layout.
As another example, a situationally aware surgical hub 5104 could determine whether the surgeon (or other medical personnel) was making an error or otherwise deviating from the expected course of action during the course of a surgical procedure. For example, the surgical hub 5104 can be configured to determine the type of surgical procedure being performed, retrieve the corresponding list of steps or order of equipment usage (e.g., from a memory), and then compare the steps being performed or the equipment being used during the course of the surgical procedure to the expected steps or equipment for the type of surgical procedure that the surgical hub 5104 determined is being performed. In one exemplification, the surgical hub 5104 can be configured to provide an alert indicating that an unexpected action is being performed or an unexpected device is being utilized at the particular step in the surgical procedure.
Overall, the situational awareness system for the surgical hub 5104 improves surgical procedure outcomes by adjusting the surgical instruments (and other modular devices 5102) for the particular context of each surgical procedure (such as adjusting to different tissue types) and validating actions during a surgical procedure. The situational awareness system also improves surgeons' efficiency in performing surgical procedures by automatically suggesting next steps, providing data, and adjusting displays and other modular devices 5102 in the surgical theater according to the specific context of the procedure.
Referring now to
The situationally aware surgical hub 106, 206 receives data from the data sources throughout the course of the surgical procedure, including data generated each time medical personnel utilize a modular device that is paired with the surgical hub 106, 206. The surgical hub 106, 206 can receive this data from the paired modular devices and other data sources and continually derive inferences (i.e., contextual information) about the ongoing procedure as new data is received, such as which step of the procedure is being performed at any given time. The situational awareness system of the surgical hub 106, 206 is able to, for example, record data pertaining to the procedure for generating reports, verify the steps being taken by the medical personnel, provide data or prompts (e.g., via a display screen) that may be pertinent for the particular procedural step, adjust modular devices based on the context (e.g., activate monitors, adjust the field of view (FOV) of the medical imaging device, or change the energy level of an ultrasonic surgical instrument or RF electrosurgical instrument), and take any other such action described above.
As the first step S202 in this illustrative procedure, the hospital staff members retrieve the patient's EMR from the hospital's EMR database. Based on select patient data in the EMR, the surgical hub 106, 206 determines that the procedure to be performed is a thoracic procedure.
Second step S204, the staff members scan the incoming medical supplies for the procedure. The surgical hub 106, 206 cross-references the scanned supplies with a list of supplies that are utilized in various types of procedures and confirms that the mix of supplies corresponds to a thoracic procedure. Further, the surgical hub 106, 206 is also able to determine that the procedure is not a wedge procedure (because the incoming supplies either lack certain supplies that are necessary for a thoracic wedge procedure or do not otherwise correspond to a thoracic wedge procedure).
Third step S206, the medical personnel scan the patient band via a scanner that is communicably connected to the surgical hub 106, 206. The surgical hub 106, 206 can then confirm the patient's identity based on the scanned data.
Fourth step S208, the medical staff turns on the auxiliary equipment. The auxiliary equipment being utilized can vary according to the type of surgical procedure and the techniques to be used by the surgeon, but in this illustrative case they include a smoke evacuator, insufflator, and medical imaging device. When activated, the auxiliary equipment that are modular devices can automatically pair with the surgical hub 106, 206 that is located within a particular vicinity of the modular devices as part of their initialization process. The surgical hub 106, 206 can then derive contextual information about the surgical procedure by detecting the types of modular devices that pair with it during this pre-operative or initialization phase. In this particular example, the surgical hub 106, 206 determines that the surgical procedure is a VATS procedure based on this particular combination of paired modular devices. Based on the combination of the data from the patient's EMR, the list of medical supplies to be used in the procedure, and the type of modular devices that connect to the hub, the surgical hub 106, 206 can generally infer the specific procedure that the surgical team will be performing. Once the surgical hub 106, 206 knows what specific procedure is being performed, the surgical hub 106, 206 can then retrieve the steps of that procedure from a memory or from the cloud and then cross-reference the data it subsequently receives from the connected data sources (e.g., modular devices and patient monitoring devices) to infer what step of the surgical procedure the surgical team is performing.
Fifth step S210, the staff members attach the EKG electrodes and other patient monitoring devices to the patient. The EKG electrodes and other patient monitoring devices are able to pair with the surgical hub 106, 206. As the surgical hub 106, 206 begins receiving data from the patient monitoring devices, the surgical hub 106, 206 thus confirms that the patient is in the operating theater.
Sixth step S212, the medical personnel induce anesthesia in the patient. The surgical hub 106, 206 can infer that the patient is under anesthesia based on data from the modular devices and/or patient monitoring devices, including EKG data, blood pressure data, ventilator data, or combinations thereof, for example. Upon completion of the sixth step S212, the pre-operative portion of the lung segmentectomy procedure is completed and the operative portion begins.
Seventh step S214, the patient's lung that is being operated on is collapsed (while ventilation is switched to the contralateral lung). The surgical hub 106, 206 can infer from the ventilator data that the patient's lung has been collapsed, for example. The surgical hub 106, 206 can infer that the operative portion of the procedure has commenced as it can compare the detection of the patient's lung collapsing to the expected steps of the procedure (which can be accessed or retrieved previously) and thereby determine that collapsing the lung is the first operative step in this particular procedure.
Eighth step S216, the medical imaging device (e.g., a scope) is inserted and video from the medical imaging device is initiated. The surgical hub 106, 206 receives the medical imaging device data (i.e., video or image data) through its connection to the medical imaging device. Upon receipt of the medical imaging device data, the surgical hub 106, 206 can determine that the laparoscopic portion of the surgical procedure has commenced. Further, the surgical hub 106, 206 can determine that the particular procedure being performed is a segmentectomy, as opposed to a lobectomy (note that a wedge procedure has already been discounted by the surgical hub 106, 206 based on data received at the second step S204 of the procedure). The data from the medical imaging device 124 (
Ninth step S218, the surgical team begins the dissection step of the procedure. The surgical hub 106, 206 can infer that the surgeon is in the process of dissecting to mobilize the patient's lung because it receives data from the RF or ultrasonic generator indicating that an energy instrument is being fired. The surgical hub 106, 206 can cross-reference the received data with the retrieved steps of the surgical procedure to determine that an energy instrument being fired at this point in the process (i.e., after the completion of the previously discussed steps of the procedure) corresponds to the dissection step. In certain instances, the energy instrument can be an energy tool mounted to a robotic arm of a robotic surgical system.
Tenth step S220, the surgical team proceeds to the ligation step of the procedure. The surgical hub 106, 206 can infer that the surgeon is ligating arteries and veins because it receives data from the surgical stapling and cutting instrument indicating that the instrument is being fired. Similarly to the prior step, the surgical hub 106, 206 can derive this inference by cross-referencing the receipt of data from the surgical stapling and cutting instrument with the retrieved steps in the process. In certain instances, the surgical instrument can be a surgical tool mounted to a robotic arm of a robotic surgical system.
Eleventh step S222, the segmentectomy portion of the procedure is performed. The surgical hub 106, 206 can infer that the surgeon is transecting the parenchyma based on data from the surgical stapling and cutting instrument, including data from its cartridge. The cartridge data can correspond to the size or type of staple being fired by the instrument, for example. As different types of staples are utilized for different types of tissues, the cartridge data can thus indicate the type of tissue being stapled and/or transected. In this case, the type of staple being fired is utilized for parenchyma (or other similar tissue types), which allows the surgical hub 106, 206 to infer that the segmentectomy portion of the procedure is being performed.
Twelfth step S224, the node dissection step is then performed. The surgical hub 106, 206 can infer that the surgical team is dissecting the node and performing a leak test based on data received from the generator indicating that an RF or ultrasonic instrument is being fired. For this particular procedure, an RF or ultrasonic instrument being utilized after parenchyma was transected corresponds to the node dissection step, which allows the surgical hub 106, 206 to make this inference. It should be noted that surgeons regularly switch back and forth between surgical stapling/cutting instruments and surgical energy (i.e., RF or ultrasonic) instruments depending upon the particular step in the procedure because different instruments are better adapted for particular tasks. Therefore, the particular sequence in which the stapling/cutting instruments and surgical energy instruments are used can indicate what step of the procedure the surgeon is performing. Moreover, in certain instances, robotic tools can be utilized for one or more steps in a surgical procedure and/or handheld surgical instruments can be utilized for one or more steps in the surgical procedure. The surgeon(s) can alternate between robotic tools and handheld surgical instruments and/or can use the devices concurrently, for example. Upon completion of the twelfth step S224, the incisions are closed up and the post-operative portion of the procedure begins.
Thirteenth step S226, the patient's anesthesia is reversed. The surgical hub 106, 206 can infer that the patient is emerging from the anesthesia based on the ventilator data (i.e., the patient's breathing rate begins increasing), for example.
Lastly, the fourteenth step S228 is that the medical personnel remove the various patient monitoring devices from the patient. The surgical hub 106, 206 can thus infer that the patient is being transferred to a recovery room when the hub loses EKG, BP, and other data from the patient monitoring devices. As can be seen from the description of this illustrative procedure, the surgical hub 106, 206 can determine or infer when each step of a given surgical procedure is taking place according to data received from the various data sources that are communicably coupled to the surgical hub 106, 206.
Situational awareness is further described in U.S. Provisional Patent Application Ser. No. 62/659,900, titled METHOD OF HUB COMMUNICATION, filed Apr. 19, 2018, which is herein incorporated by reference in its entirety. In certain instances, operation of a robotic surgical system, including the various robotic surgical systems disclosed herein, for example, can be controlled by the hub 106, 206 based on its situational awareness and/or feedback from the components thereof and/or based on information from the cloud 104.
A variety of computer systems have been described herein, including surgical hubs 106, 206 (
A variety of paradigms or techniques can be utilized to efficiently share data between interrelated or connected databases, such as implementing relational database models or utilizing consistent data formats so that data is portable across the different computer systems in a network. Two general structured data-sharing paradigms described herein are referred to as “data interoperability” and “data fluidity.” These data-sharing paradigms can be characterized as rulesets executed by each of the computer systems within a computer network that define how and in what ways data is shared by and between the computer systems within the computer network. The rule set can be embodied as a set of computer-executable instructions stored in a memory of a computer system (e.g., memory 249 of the surgical hub 206 illustrated in
Data interoperability is defined as the ability of computer or database systems to work cooperatively by having a database automatically transmit particular data to recipient databases according to predefined rules. For each type of data generated by or at a computer system, the rules of the data interoperability paradigm delineate to which recipient database(s) the computer should transmit each type of data and, in some cases, the data format each type of data is to be transmitted in to each particular recipient database. In some aspects, data interoperability can be characterized as a one-way communication of data between computer systems. Further, in some aspects, the computer system transmitting data through the one-way communication channel can lack the ability to accept data of the same type back from the receiving computer system. These aspects can be beneficial in order to, for example, have one database drive or control the data that is stored or presented in another database.
Illustrative of these concepts,
For example, the first database 212002 can include an EHR database, and the second database 212004 can include a pharmacy database. In this implementation, the data interoperability ruleset can dictate that when a patient's EHR is updated in the EHR database to indicate that a new medication has been prescribed to the patient, the relevant prescription data can be automatically transmitted to the pharmacy database as a new prescription request for processing by the pharmacy department. Accordingly, the first database 212002 can be programmed to transmit 212006 data representing a prescription request to the second database 212004. The data in the prescription request can include, for example, drug interaction data and a current drug list from the associated patient's EHRs. Further, the data interoperability ruleset can dictate that when a prescription is prepared in response to a received prescription request, a billing update can be automatically transmitted to the EHR database. Accordingly, the second database 212004 can be programmed to transmit 212008 data representing a billing update to the first database 212002 in response to or upon fulfillment of the prescription request. The transmission of each of these types of data can be unidirectional with respect to the respective databases 212002, 212004.
As another example, the first database 212002 can include an OR scheduling database, and the second database 212004 can include a medical supply database. In this implementation, the data interoperability ruleset can dictate that when a new operation is scheduled or input into the OR scheduling database, relevant data for the scheduled operation can be automatically transmitted to the medical supply database to indicate which supplies should be prepared by the medical supply department and at what time and date they should be prepared by. Accordingly, the OR scheduling database can automatically transmit 212006 data representing a procedure to the medical supply database when a new procedure is scheduled. Accordingly, the employees with access to the medical supply database can automatically receive updates so that they can have the products and instruments needed for the scheduled procedure prepared at the scheduled time.
As yet another example, the first database 212002 can include a lab database, and the second database 212004 can include an EHR database. In this implementation, the data interoperability ruleset can dictate that when a patient's lab results are uploaded to the lab database, the lab results data can be automatically transmitted to the EHR database to be associated with the patient's EHR. Accordingly, the lab database can automatically populate the EHR database with data representing test results and labs when they are completed. Accordingly, physicians and any other individuals with access to the patient EHR can immediately access the results of any ordered tests and labs without the need to take any further action.
As yet another example, the first database 212002 can include a prescription-entering or EHR database, and the second database 212004 can include a medication-dispensing or pharmacy database. In this implementation, the data interoperability ruleset can dictate that when a new prescription is entered for a patient, the relevant prescription data can be automatically transmitted to the pharmacy database as a new prescription request for processing by the pharmacy department. Accordingly, the medication-dispensing database can automatically receive the prescription when entered by the practitioner so that the prescription can be ready as needed.
As yet another example, the first database 212002 can include a pathology database, and the second database 212004 can include an OR database (e.g., stored in a surgical hub 106, 206). In this implementation, the data interoperability ruleset can dictate that when new pathology results are received for a patient, the relevant pathology data can automatically be transmitted to the OR database for review by the surgical staff. Accordingly, data including updates or results stored in the pathology database can be automatically transmitted 212006 to the OR through an update to the OR database. The data can be transmitted 212006 between the pathology database and the OR database in real time, such as during the course or a surgical procedure to inform subsequent steps of the procedure. As a specific illustration, during a wedge resection procedure to remove a small tumor in a patient's lung, the surgical staff sends the resected specimen to the pathology department to check for malignancy while the patient is still in the OR. If the pathology department confirms malignancy, the surgical staff often elects to complete a lobectomy procedure on the lobe from which the wedge was taken. Accordingly, this process of providing notifications from other departments to the surgical staff during the course of a surgical procedure via the surgical hub can be automated by utilizing a data interoperability paradigm between the pathology database and the surgical hubs, as described above.
Data fluidity is defined as the ability of data to flow from one database to another database according to predefined rules that delineate bidirectional relationships between databases for data sets stored therein. In some aspects, the data fluidity paradigm can define whether data is transmitted to particular recipient databases and/or whether data is linked to particular recipient databases. Data can be automatically shared with or transferred to other databases utilizing relational database techniques (i.e., relations defined between the databases), for example. In one aspect, the databases can execute a set of rules that define which types of data are to be automatically transmitted to which particular recipient database. Furthermore, in one aspect, the databases can execute a set of rules that define the format of the data or the database to which the data is transmitted according to surgical contextual data (metadata) associated with the data. The ruleset can be embodied as a set of computer-executable instructions stored in a memory of a computer system (e.g., memory 249 of the surgical hub 206 illustrated in
For example, a surgical hub can utilize situational awareness (described above under the heading SITUATIONAL AWARENESS) to determine the surgical context (e.g., the surgical procedure type or the surgical procedure step being performed) based on the perioperative data received from the surgical instrument, patient monitors, and other surgical devices or databases and then associate the surgical context with the data being generated (e.g., store the surgical context as metadata for the generated data). The determined surgical context can influence which particular database(s) receive particular data, how much of the data is transmitted to the recipient database(s), the data format in which the data is transmitted, and so on. Accordingly, the computer system (e.g., a surgical hub) can then transmit the gathered data (with or without its associated surgical metadata) to particular recipient databases or in particular data formats according to the determined surgical context. In various aspects, the surgical context can influence the bit size, quantity, resolution, and/or time bracket around the transmitted data (e.g., the number of samples of the data captured at a particular sampling rate). Accordingly, the data fluidity paradigm allows interrelated databases to share data relevant to each database according to the needs of each recipient database. In other words, computer systems sharing data according to a data fluidity paradigm can anticipate the potential uses and needs for data received by the computer systems and then automatically route data to recipient databases or computer systems accordingly. Further, the surgical context can dictate the format that a computer system transmits the data in, the breadth of the data transmitted by the computer system, and so on.
Illustrative of these concepts,
The data fluidity rulesets dictating data flow between different databases can be defined (e.g., by administrators of the database system 212020) according to the relationships between the departments represented by the databases 212022, 212024, 212026. For example, some departments (e.g., OR and pathology or OR and supply) routinely collaborate or consult with each other on medical issues occurring with patients in the medical facility. Accordingly, the data fluidity rules can dictate that when an update is made to a particular data type (or a set of data types) in one of these collaborating databases, a substantial portion or all of the updated data can be transmitted or linked to the other collaborating database. Further, the transmitted data can include contextual metadata determined through surgical situational awareness and other additional or associated data, for example. Alternatively, some departments (e.g., billing) only need a small portion of certain data types. Accordingly, the data fluidity rules can dictate that when an update is made to a particular data type (or a set of data types) in a database, only a small portion of the updated data that is relevant to the recipient database is transmitted or linked to the recipient database. For example, if the recipient database is a billing department database, the data shared with the billing database may only include procedure codes, the time, and the expendables consumed during a medical procedure because only that data that is needed by the billing department. As can be seen, only data that is relevant to the recipient database is actually transmitted or linked to the recipient database, which limits access to sensitive patient data, prevents the recipient from being overwhelmed with unneeded data, and minimizes required data transmission bandwidths, while still allowing all connected databases to be seamlessly updated in accordance with each other.
In one implementation, the first database 212022 can include a laboratory database, the second database 212024 can include an EHR database, and the third database 212026 can include a hospital administration database. In this implementation of a data fluidity paradigm, the laboratory database and the administration database can transmit 212028 data 212029 between each other, the laboratory database and the EHR database can transmit 212030 data 212031 between each other, and the laboratory database and the administration database can transmit 212032 data between each other as dictated by the particular data fluidity ruleset defining the relations between the various databases. For example, the laboratory database could automatically transmit 212030 data 212031 including completed lab results to the EHR database to associate the lab results with the corresponding patient, whereafter the lab results can be retrieved from the EHR database. As another example, the laboratory database could automatically transmit 212028 data 212029 including a list of tests performed and other details to the hospital administration database, which can then be utilized to update billing information, reorder test supplies as needed, and so on. Further, each of the connections between the various aforementioned databases can be bidirectional. For example, if a patient's EHR is updated in the EHR database to include additional test results performed outside the given medical facility, those test results can likewise be automatically transmitted to the laboratory database for consideration and evaluation by the laboratory staff.
In another implementation, a computer system and/or network of linked databases can be configured to automatically collect and compile surgical outcomes resulting from specific treatment regimes by connecting the databases of various departments via a data fluidity paradigm, allowing all of the data pertaining to a patient's treatment to be aggregated and seamlessly integrated together. By automatically compiling patient outcome data with patient treatment data, patient care can be tracked more accurately and improvements can be developed for treatment regimes, surgical procedures, and other patient care. In some aspects, by automatically sharing relevant data across departments in a specific format for that department, the data can be more easily communicated, which can in turn allow the data to be presented more easily to patients, at meetings, in clinical papers, and so on. In some aspects, data can be recorded in each database and transmitted to the other connected databases in a standard format, allowing data from any given database to be seamlessly integrated into another compliant database.
In one aspect, collaboration across multiple departments could be increased by allowing or causing the data collected in any given database to easily flow from one group of specialists to another. The data fluidity paradigm allows for data to easily flow between departments at a medical facility by establishing a standard set of rules that all computer systems within the medical facility utilize to transmit or link data that dictates the destinations for any given type of data, the format that the data is to be transmitted in to the recipient database, and so on. The structured data-sharing paradigms described herein are beneficial in this and other contexts because they ensure that the correct data is being collected for physicians' uses. By allowing a computer system to automatically retrieve the necessary data from the relevant database(s) and having the databases update in concert with each other when data is added or changed, human errors in transmitting and transcribing data, errors due to receiving partial incomplete information, and other such errors are avoided.
In one aspect, some or all of the data in particular databases can respond fluidity to requests from users, rather than being automatically transmitted or linked to another database. Accordingly, a first computer system can be programmed to receive data requests from a second computer or database system (which can be initiated by a user, for example) and then transmit the requested data and/or define a relation between the database stored by the first computer system and the second computer system depending upon the identity or the type of request sent by the second computer system. For example, physicians can make data requests from the computer system, which then proceeds to automatically collect and compile the requested data from the relevant databases that the computer system is linked to. Such aspects can be utilized in a variety of applications, such as personalized cancer medicine. For example, the computer system can link the oncologist, surgeon, and histologist collaborating to treat a patient by allowing any of them to retrieve all of the treatment data related to the given patient. This in turn allows the medical personnel to each track the patient's treatment and allows the individual associated with a patient's care to easily retrieve and analyze data regarding the patient, such as a tumor location, margins, nodal dissection, and chemo treatment. By giving each individual associated with the treatment of a patient total access to the patient's data, follow-up and post-surgical treatment can be improved by ensuring that the medical personnel are all fully up to date on the patient's treatment. In some aspects, in addition to defining what information they would like to receive, the computer system can also be programmed to allow users to define the format that they would like the data to be presented in. Accordingly, the computer system can retrieve the identified data from the corresponding databases, convert the data to the desired format, and then present the data to the user.
Accordingly, the processor 244 executing the process 212100 receives 212102 perioperative data from the connected surgical devices and determines 212104 the surgical context based at least in part on the received perioperative data, as discussed above under the heading SITUATIONAL AWARENESS.
What the surgical hub 206 does with the collected data is dictated by the structured data ruleset being implemented by the surgical hub 206. Depending upon the surgical context and the type of data, the surgical hub 206 can transmit the data (or a subset thereof) to another database, set a relation between the database stored in the memory 249 of the surgical hub 206 and another database (i.e., link the relevant data fields of the databases), or take other such actions. In the illustrated aspect, the processor 244 transmits 212106 at least a portion of the collected surgical data to one or more recipient databases based on the determined surgical context and the identities of the recipient databases. The surgical data can include, for example, perioperative data received from the surgical devices, surgical contextual data determined via situational awareness (e.g., the surgery type or the step of the surgical procedure being performed), metadata associated with the surgical devices and/or the surgical context, and so on. Further, the processor 244 sets 212108 a relation between at least a portion of the collected surgical data stored in the surgical hub memory 249 and one or more recipient databases based the determined surgical context and the identities of the recipient databases. In other words, the surgical hub 206 transmits 212106 data and/or sets 212108 relations between its database and other databases according to the structured data-sharing ruleset, which defines which databases are to receive certain types of data or be linked to certain types of data collected by the surgical hub 206 based on the determined surgical context. For example, the surgical hub 206 could determine that a number of nonreusable surgical devices were used during the surgical procedure via situational awareness and accordingly transmit 212106 data indicating the types and numbers of nonreusable devices that were used to a purchasing database communicably connected to the surgical hub 206 for reordering of those nonreusable devices. The structured data-sharing ruleset can thus define that the purchasing database receives data related to consumed nonreusable surgical devices and that data is to be transmitted to the purchasing database. As another example, the surgical hub 206 could determine that the surgical procedure is completed or will be completed soon and accordingly set 212108 a relation between the data in its database storing the patient's biographical information and the surgical procedure type and a recovery department database to notify the recovery staff to prepare to receive the patient. The structured data-sharing ruleset can thus define that the recovery department database receives data related to identifying a patient and the surgery type and that data is to be linked to the recovery department database.
Another illustrative implementation of the process 212100 is depicted in
As discussed above, databases may only share a subset of the data they store with other connected databases. Further, different subsets of the data stored by each database may be shared with different databases, depending upon the data needed by the recipient databases. For example, data stored within each database can be organized into data categories and the structured data-sharing ruleset can dictate, for example, which data categories are shared with which other databases. For example,
The computer systems storing the databases 212130, 212132, 212134 that define a database system 212020 can be communicably linked together via, for example, a network. In some aspects, the computer systems can be cloud computing systems, as described above under the heading CLOUD SYSTEM HARDWARE AND FUNCTIONAL MODULES. In some aspects, multiple databases can be stored by a single computer system. In some aspects, the computer systems can be connected via a distributed computing communication protocol.
In one aspect, users can also define the types of data that they would like the medical facility's computer systems, such as the surgical hubs 106, 206 (
In various aspects, database systems executing a structured data-sharing paradigm can monitor the activities occurring in an OR through a surgical hub 206 therein and automatically route relevant data to relevant departments in order to improve the efficiency and function of the medical facility. In one aspect, a surgical hub 206 can be configured to monitor the progress of a surgical procedure, surgical device success rate, and other OR data via, for example, situational awareness. The ability of the surgical hub 206 to seamlessly share and communicate data with other databases in the medical facility can have a substantial number of benefits. For example, the surgical hub 206 can automatically share data regarding surgical device utilization with the re-ordering department through structured data sharing so that they know, for example, not to reorder surgical devices that have poor success rates. As another example, the surgical hub 206 can automatically share data regarding surgical outcomes with the pharmacy department so that they know, for example, that the patient may require additional pain medication due to a prolonged surgical procedure. As yet another example, the surgical hub 206 can automatically share data regarding any biopsies taken during the surgical procedure or other tissue samples that require testing with the pathology department so that they know, for example, to prepare to receive the tissue. As yet another example, the surgical hub 206 can automatically share data regarding the depletion of fluids (e.g., blood) during a surgical procedure with the medical supplies department so that they know to an order for backup supplies as the OR supply is depleted. As yet another example, the surgical hub 206 can automatically share data regarding an impending procedure with the medical supplies department so that they know, for example, to ready OR-specific drugs, hemostatic agents, and healing impacting agents (e.g., matrix metalloproteinase inhibiters) before the procedure. With the supplies readied ahead of time, they could then be delivered to the OR in a timely manner, allowing the surgical procedure to proceed on time and with the supplies at the correct usage temperature. Usage temperature can be important for certain types of agents, such as fibrin and thrombin. Fibrin and thrombin are refrigerated, biologically active agents that have to be dispensed at room temperature. If the surgical procedure calls for an agent, it can accordingly be critical for the adjunct to be at the correct temperature for the procedure. Through structured data sharing, a scheduling database can share scheduled surgical procedure times with all other relevant databases in the medical facility, ensuring that all relevant departments are fully up to date as to the start time for each procedure. If an agent is needed at the beginning of the procedure, then the medical facility personnel can be provided the precise time that the surgical procedure is to begin and can thus know to deliver the agent at that time. If an agent is needed during a procedure, a surgical hub 206 executing a situational awareness system can further monitor the progress of the surgical procedure after it has begun and update other relevant databases as to the status of the surgical procedure through structured data sharing so that medical facility personnel know the precise time at which they should bring desired agents to the OR so that they are maintained at the proper usage temperature. Accordingly, structured data sharing in the OR context can ensure that the agents are ready at the correct time, at the correct temperature, without risking any damage to the agents. As yet another example, the surgical hub 206 could monitor the progress of the surgical procedure (e.g., via situational awareness) and automatically share the procedural progress with the cleaning department so that they know when to expect to turn over the OR for the next procedure, which in turn aids in overall hospital logistics and scheduling by facilitating the process of cleaning and preparing surgical facilities for subsequent procedures.
In one aspect, a computer system (e.g., a surgical hub 206) can be programmed to track the use of surgical devices and their movement through a medical facility to, for example, collect data on the surgical instruments throughout their life cycle. Such data can include the number of times that a surgical device has been sterilized, repaired, and/or held in inventory or the amount of time that a surgical device has been held in each of the respective departments. A computer system can track surgical devices in this manner through structured data sharing by receiving from the databases of each relevant department location data for a surgical device (e.g., when a surgical device is brought to a department, it can be scanned into that department, which generates a record of the location of the surgical device), repair and maintenance records for the surgical device, and so on. Such data can be utilized to evaluate values, costs, and efficiencies of all of the medical products that are utilized in the medical facility.
In one aspect, a computer system can be programmed to allow patients to contribute self-reported data. In various aspects, the self-reported data could be directly entered into a database of a medical facility computer system via a computer terminal or the patient could cause a personal electronic device (or another personal data collection device) to automatically transmit collected information to a designated recipient database. The self-reported data could include, for example, blood sugar logs from testing equipment, such as a continuous blood glucose monitor, insulin pumps, artificial pancreas data, and so on. The self-reported data can also include, for example, data from activity monitors (e.g., Fitbit or Apple Watch) that are configured to collect activity data, location data, and other types of data. The activity monitors can provide, for example, activity level data (e.g., distance traveled, active minutes, number of steps taken, number of flights of stairs traversed), sleep data (e.g., sleep cycles, duration, and stages), heart rate monitoring data (e.g., resting heart rate, percent of time in specified heart rate zones, which can be determined by age, and heart rate variability), nutritional information, water intake, calories burned, and so on. When uploaded to a recipient database, the recipient database can then, in some aspects, automatically share relevant self-reported patient data with other connected devices according to a structured data-sharing ruleset.
With structured data sharing, one concern is for access to data to only be granted to appropriate recipients. Accordingly, all data requests and all requests to link databases must be verified and authorized to prevent unauthorized recipients from gaining access to the data.
Accordingly, the structured data-sharing paradigms described herein, i.e., data fluidity and data interoperability, can facilitate the movement of data throughout a medical facility (or a network of interconnected medical facilities). By seamlessly sharing data so that every interconnected database always has access to all of the data generated in the medical facility that is relevant to its department, structured data-sharing paradigms allow medical facilities to operate more efficiently and provide better patient outcomes.
In some aspects, the computer systems described herein are programmed to provide clear, holistic analyses of the total costs associated with any given surgical procedure or treatment, such as by calculating the total cost associated with all of the items that are used during a surgical procedure or treatment. Such functionality can provide a range of benefits, including allowing administrators to understand precisely where and how money is being expended in a medical facility, providing suggestions on cost-effective product mixes for particular types of surgical procedures, identifying when reusable items should be replaced, determining the degree of wear and tear on the surgical instruments and other items used during a procedure, and so on. Further, this economic data can be integrated with data on treatment or surgical outcomes so that users can provide additional analyses or so that the systems can provide recommendations to users. The data on treatment or surgical outcomes can be determined by, for example, the cloud computing system described in connection with
Accordingly, systems and methods are described herein for analyzing the total costs of surgical instruments and devices for surgical procedures, including both in-house costs and servicing costs. In one aspect, a computer system (e.g., a surgical hub) can be programmed to provide real-time analyses of the comprehensive costs of all instruments and devices used in a surgical procedure, including the costs associated with both reusable devices (e.g., maintenance, cleaning, and resterilization costs) and non-reusable devices (i.e., replacement costs). In some aspects, the computer system can utilize the data-sharing paradigms described above under the heading STRUCTURED DATA SHARING to determine the replacement costs of non-reusable surgical devices by, for example, receiving or sharing data between a purchasing database. In some aspects, the computer system can utilize the data-sharing paradigms described above under the heading STRUCTURED DATA SHARING to determine the actual maintenance costs of reusable surgical devices by, for example, receiving or sharing data between a variety of medical facility databases to track the devices throughout the medical facility. By tracking the devices as they are transported throughout the medical facility for stocking, sterilization, and other in-house maintenance processes, the computer system can calculate the maintenance costs according to the time and resources actually expended on maintaining the surgical devices.
In one aspect, the various computer systems (e.g., surgical hubs) throughout a medical facility can generate, store, and share metadata indicating when and how each surgical device has interacted with each of the various computer systems. For example, when a surgical device is brought into an OR and connects to the surgical hub located within that OR, the surgical hub can generate metadata associated with that surgical instrument indicating the date, time, and location of the surgical instrument and then store and share that metadata with other computer systems within the network. Accordingly, the computer systems described herein can track surgical instruments according to their associated metadata. In one aspect, a computer system (e.g., a surgical hub) can be programmed to retrieve or otherwise receive metadata for all of the surgical devices utilized during the course of a surgical procedure to track them throughout their pre- and post-operative processes, including their locations, statuses, replacement parts installed in them, repairs applied, and cleaning times. Accordingly, the computer system can track the cost and utilization of the surgical devices as they are circulated through the medical facility.
In one aspect, a computer system (e.g., a surgical hub) can be programmed to track the number of uses of a resterilized or otherwise reused device. The computer system can further be programmed to determine when the device has reached the end of its life according to whether the number of uses meets or exceeds a use threshold. In another aspect, a computer system (e.g., a surgical hub) can be programmed to determine the maintenance costs of a surgical device, determine the replacement cost of the surgical device (e.g., by retrieving the replacement cost from a purchasing database), and then determine whether the surgical device should be replaced according to whether the maintenance costs exceed the replacement costs. Accordingly, the computer system can execute cost analysis algorithms for tracking surgical devices throughout medical facilities, analyze the costs associated with the surgical devices, and provide recommendations to users.
Tracking all of the various costs associated with the total care and maintenance associated with each surgical device allows the cost analysis module 210502 to provide true one-for-one comparisons between different mixes of surgical products. Accordingly, users can utilize the cost analysis module 210502 to perform cost analyses, or the cost analysis module 210502 can automatically perform such analyses and make recommendations to users to more efficiently utilize hospital resources, identify bottlenecks within the medical facility's systems and provide suggestions on how to improve them, identify when there are too few or too many of specific products that are costing time or money, and so on.
As mentioned above, the various computer systems (e.g., surgical hubs) within a medical facility can track each individual surgical device as it is processed through the medical facility's workflow by generating, storing, and sharing metadata indicating when and how each surgical device has interacted with each of the various computer systems. For example,
Additional processes or algorithms can then utilize this location surgical device metadata. For example, a computer system 210704 can determine when a particular surgical device 210702 is at a preceding department in the workflow for the surgical device 210702 and then automatically provide a prompt or notification for the staff to prepare to receive the surgical device 210702 (e.g., prepare sterilization supplies when the surgical device 210702 is in surgical 210706 and is expected to then be sent to sterilization 210708). As another example, a computer system 210704 can determine when a surgical device 210702 has been used in a surgical procedure or cleaned a threshold number of times and then provide a notification for the staff to order replacement parts for the surgical device 210702 or dispose of the surgical device 210702. Alternatively, the computer system 210704 can automatically order replacement parts for the surgical device 210702 after a threshold number of uses. Such processes reduce or eliminate the need for the medical facility 210700 to excessively stock replacement parts, cleaning products, and other such products onsite.
In another aspect, the computer systems 210704 can be programmed to compare and analyze actual postoperative outcomes to predicted postoperative outcomes, incorporating the economic data generated by the cost analysis module 210502. For example, predicted reoperation costs can be calculated based on predicted surgical outcomes. More particularly, the computer systems 210704 can be programmed to retrieve data (e.g., medical literature data surgical outcomes that are uploaded to a database accessible by the computer systems 210704) or determine (e.g., by the cloud computing system described in connection with
As described above under the heading SURGICAL HUBS, surgical hubs 206 can be connected to a variety of surgical devices, such as surgical instruments, generators, smoke evacuators, displays, and so on. Through their connections to these surgical devices, the surgical hubs 206 can receive an array of perioperative data from these paired surgical devices while the devices are in use during a surgical procedure. Further, as described above under the heading SITUATIONAL AWARENESS, surgical hubs 206 can determine the context of the surgical procedure being performed (e.g., the procedure type or the step of the procedure being performed) based on perioperative data received, at least in part, from these connected surgical devices. Accordingly, the processor 244 executing the process 210600 determines 210602 whether a surgical procedure is being performed via, for example, a situational awareness system executed by the surgical hub 206. Accordingly, the processor 244 determines 210604 what surgical devices are being utilized during the surgical procedure. In one aspect, the processor 244 can determine 210604 what surgical devices are being used at any given time by detecting which surgical devices are connected to the surgical hub 206, which devices are actively being powered (e.g., whether energy is being supplied to an ultrasonic or RF electrosurgical instrument), by visually identifying which devices are being held or manipulated by the surgeon through camera systems set up throughout the OR, by determining which step of the procedure the surgical staff is performing and thereby inferring what devices are currently being utilized, and so on.
Accordingly, for each surgical device that is or was used during the surgical procedure, the processor 244 determines 210606 whether the surgical device is reusable or non-reusable. The processor 244 can determine 210606 whether a surgical device is reusable by querying a database listing whether each particular item is reusable, retrieving manufacturer's specifications for the surgical device, or retrieving the metadata associated with the surgical device to ascertain whether the item has previously been or is intended to be used multiple times, for example. If the given surgical device is reusable, then the process proceeds along the YES branch and the processor 244 determines 210608 the maintenance cost for the device. The maintenance cost can include repair costs, resterilization costs, cleaning costs, and so on. The processor 244 can determine 210608 the maintenance cost using the techniques discussed above, i.e., tracking the metadata associated with the given surgical device to determine how often and what types of maintenance steps the surgical device is taken through during its workflow. If the given surgical device is not reusable, then the process proceeds along the NO branch and the processor 244 determines 20610 the replacement cost for the device. The processor 244 can determine 210610 the replacement cost by querying a purchasing database associated with the medical facility 210700 to retrieve the purchase price of the given surgical device, for example.
In various aspects, the process 210600 calculates the costs associated with each surgical device used during the surgical procedure in order to calculate a complete cost associated with the surgical procedure. Accordingly, the processor 244 determines 210612 whether the surgical procedure is completed via, for example, a situational awareness system, as discussed above. If the procedure is not completed, then the process 210600 proceeds along the NO branch and the processor 244 continues a loop of monitoring which surgical devices are being utilized or consumed until the procedure is completed. If the procedure is completed, then the process 210600 proceeds along the YES branch and the processor 244 determines 210614 the total cost for the surgical procedure based on the aggregated maintenance and replacement costs of the surgical devices utilized during the surgical procedure.
Various aspects of the subject matter described herein are set out in the following numbered examples:
Example 1. A computer system configured to be communicably coupled to a plurality of surgical devices. The computer system comprises a processor and a memory coupled to the processor. The memory stores instructions that, when executed by the processor, cause the computer system to: determine which of the plurality of surgical devices are utilized during a surgical procedure based at least in part on perioperative data received from the one or more of the plurality of surgical devices; determine whether each of the plurality of surgical devices utilized during the surgical procedure is a reusable surgical device or a non-reusable surgical device; determine a maintenance cost for each reusable surgical device; determine a replacement cost for each non-reusable surgical device; and determine a total cost of the plurality of surgical devices for the surgical procedure according to the maintenance cost for each reusable surgical device and the replacement cost for each non-reusable surgical device.
Example 2. The computer system of Example 1, wherein the maintenance cost comprises at least one of a cleaning cost, a resterilization cost, a repair cost, or any combination thereof.
Example 3. The computer system of Example 1 or 2, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to: determine whether the maintenance cost exceeds the replacement cost for each reusable surgical device; and provide a replacement recommendation for each reusable surgical device where the maintenance cost exceeds the replacement cost.
Example 4. The computer system of any one of Examples 1-3, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to: determine a number of uses for each reusable surgical device; and provide a replacement recommendation for each reusable surgical device where the number of uses exceeds a threshold.
Example 5. The computer system of any one of Examples 1-4, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to: retrieve metadata associated with each reusable surgical device, the metadata storing at least one of locations of the reusable surgical device, lengths of time for the locations, a number of uses of the reusable surgical device, or any combination thereof; and determine the maintenance cost for each reusable surgical device according to the metadata.
Example 6. The computer system of any one of Examples 1-5, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to retrieve a purchase price associated with each non-reusable surgical device from a purchasing database, wherein the replacement cost corresponds to the purchase price.
Example 7. The computer system of any one of Examples 1-6, wherein the computer system comprises a surgical hub.
Example 8. A computer system comprising a processor and a memory coupled to the processor. The memory stores instructions that, when executed by the processor, cause the computer system to: identify one or more surgical devices utilized during a surgical procedure according to perioperative data received from the one or more surgical devices; and determine a total cost of the one or more surgical devices for the surgical procedure according to a maintenance cost or a replacement cost associated with each of the one or more surgical devices.
Example 9. The computer system of Example 8, wherein the maintenance cost comprises at least one of a cleaning cost, a resterilization cost, a repair cost, or any combination thereof.
Example 10. The computer system of Example 8 or 9, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to: determine whether the maintenance cost exceeds the replacement cost for each reusable surgical device; and provide a replacement recommendation for each reusable surgical device where the maintenance cost exceeds the replacement cost.
Example 11. The computer system of any one of Examples 8-10, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to: determine a number of uses for each reusable surgical device; and provide a replacement recommendation for each reusable surgical device where the number of uses exceeds a threshold.
Example 12. The computer system of any one of Examples 8-11, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to: retrieve metadata associated with each reusable surgical device, the metadata storing at least one of locations of the reusable surgical device, lengths of time for the locations, a number of uses of the reusable surgical device, or any combination thereof; and determine the maintenance cost for each reusable surgical device according to the metadata.
Example 13. The computer system of any one of Examples 8-12, wherein the memory further stores instructions that, when executed by the processor, cause the computer system to retrieve a purchase price associated with each non-reusable surgical device from a purchasing database, wherein the replacement cost corresponds to the purchase price.
Example 14. The computer system of any one of Examples 8-13, wherein the computer system comprises a surgical hub.
Example 15. A computer-implemented method for determining a surgical device cost for a surgical procedure. The method comprises: determining, by a computer system, which of a plurality of surgical devices are utilized during the surgical procedure based at least in part on perioperative data received from one or more of the plurality of surgical devices; determining, by the computer system, whether each of the plurality of surgical devices utilized during the surgical procedure is a reusable surgical device or a non-reusable surgical device; determining, by the computer system, a maintenance cost for each reusable surgical device; determining, by the computer system, a replacement cost for each non-reusable surgical device; and determining, by the computer system, a total cost of the plurality of surgical devices for the surgical procedure according to the maintenance cost for each reusable surgical device and the replacement cost for each non-reusable surgical device.
Example 16. The computer-implemented method of Example 15, wherein the maintenance cost comprises at least one of a cleaning cost, a resterilization cost, a repair cost, or any combination thereof.
Example 17. The computer-implemented method of Example 15 or 16, further comprising: determining, by the computer system, whether the maintenance cost exceeds the replacement cost for each reusable surgical device; and providing, by the computer system, a replacement recommendation for each reusable surgical device where the maintenance cost exceeds the replacement cost.
Example 18. The computer-implemented method of any one of Examples 15-17, further comprising: determining, by the computer system, a number of uses for each reusable surgical device; and providing, by the computer system, a replacement recommendation for each reusable surgical device where the number of uses exceeds a threshold.
Example 19. The computer-implemented method of any one of Examples 15-18, further comprising: retrieving, by the computer system, metadata associated with each reusable surgical device, the metadata storing at least one of locations of the reusable surgical device, lengths of time for the locations, a number of uses of the reusable surgical device, or any combination thereof; and determining, by the computer system, the maintenance cost for each reusable surgical device according to the metadata.
Example 20. The computer-implemented method of any one of Examples 15-19, further comprising retrieving, by the computer system, a purchase price associated with each non-reusable surgical device from a purchasing database, wherein the replacement cost corresponds to the purchase price.
Example 21. The computer-implemented method of any one of Examples 15-20, wherein the computer system comprises a surgical hub.
While several forms have been illustrated and described, it is not the intention of Applicant to restrict or limit the scope of the appended claims to such detail. Numerous modifications, variations, changes, substitutions, combinations, and equivalents to those forms may be implemented and will occur to those skilled in the art without departing from the scope of the present disclosure. Moreover, the structure of each element associated with the described forms can be alternatively described as a means for providing the function performed by the element. Also, where materials are disclosed for certain components, other materials may be used. It is therefore to be understood that the foregoing description and the appended claims are intended to cover all such modifications, combinations, and variations as falling within the scope of the disclosed forms. The appended claims are intended to cover all such modifications, variations, changes, substitutions, modifications, and equivalents.
The foregoing detailed description has set forth various forms of the devices and/or processes via the use of block diagrams, flowcharts, and/or examples. Insofar as such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, it will be understood by those within the art that each function and/or operation within such block diagrams, flowcharts, and/or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. Those skilled in the art will recognize that some aspects of the forms disclosed herein, in whole or in part, can be equivalently implemented in integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and or firmware would be well within the skill of one of skill in the art in light of this disclosure. In addition, those skilled in the art will appreciate that the mechanisms of the subject matter described herein are capable of being distributed as one or more program products in a variety of forms, and that an illustrative form of the subject matter described herein applies regardless of the particular type of signal bearing medium used to actually carry out the distribution.
Instructions used to program logic to perform various disclosed aspects can be stored within a memory in the system, such as dynamic random access memory (DRAM), cache, flash memory, or other storage. Furthermore, the instructions can be distributed via a network or by way of other computer readable media. Thus a machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer), but is not limited to, floppy diskettes, optical disks, compact disc, read-only memory (CD-ROMs), and magneto-optical disks, read-only memory (ROMs), random access memory (RAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic or optical cards, flash memory, or a tangible, machine-readable storage used in the transmission of information over the Internet via electrical, optical, acoustical or other forms of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Accordingly, the non-transitory computer-readable medium includes any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).
As used in any aspect herein, the term “control circuit” may refer to, for example, hardwired circuitry, programmable circuitry (e.g., a computer processor including one or more individual instruction processing cores, processing unit, processor, microcontroller, microcontroller unit, controller, digital signal processor (DSP), programmable logic device (PLD), programmable logic array (PLA), or field programmable gate array (FPGA)), state machine circuitry, firmware that stores instructions executed by programmable circuitry, and any combination thereof. The control circuit may, collectively or individually, be embodied as circuitry that forms part of a larger system, for example, an integrated circuit (IC), an application-specific integrated circuit (ASIC), a system on-chip (SoC), desktop computers, laptop computers, tablet computers, servers, smart phones, etc. Accordingly, as used herein “control circuit” includes, but is not limited to, electrical circuitry having at least one discrete electrical circuit, electrical circuitry having at least one integrated circuit, electrical circuitry having at least one application specific integrated circuit, electrical circuitry forming a general purpose computing device configured by a computer program (e.g., a general purpose computer configured by a computer program which at least partially carries out processes and/or devices described herein, or a microprocessor configured by a computer program which at least partially carries out processes and/or devices described herein), electrical circuitry forming a memory device (e.g., forms of random access memory), and/or electrical circuitry forming a communications device (e.g., a modem, communications switch, or optical-electrical equipment). Those having skill in the art will recognize that the subject matter described herein may be implemented in an analog or digital fashion or some combination thereof.
As used in any aspect herein, the term “logic” may refer to an app, software, firmware and/or circuitry configured to perform any of the aforementioned operations. Software may be embodied as a software package, code, instructions, instruction sets and/or data recorded on non-transitory computer readable storage medium. Firmware may be embodied as code, instructions or instruction sets and/or data that are hard-coded (e.g., nonvolatile) in memory devices.
As used in any aspect herein, the terms “component,” “system,” “module” and the like can refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution.
As used in any aspect herein, an “algorithm” refers to a self-consistent sequence of steps leading to a desired result, where a “step” refers to a manipulation of physical quantities and/or logic states which may, though need not necessarily, take the form of electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated. It is common usage to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. These and similar terms may be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities and/or states.
A network may include a packet switched network. The communication devices may be capable of communicating with each other using a selected packet switched network communications protocol. One example communications protocol may include an Ethernet communications protocol which may be capable permitting communication using a Transmission Control Protocol/Internet Protocol (TCP/IP). The Ethernet protocol may comply or be compatible with the Ethernet standard published by the Institute of Electrical and Electronics Engineers (IEEE) titled “IEEE 802.3 Standard”, published in December, 2008 and/or later versions of this standard. Alternatively or additionally, the communication devices may be capable of communicating with each other using an X.25 communications protocol. The X.25 communications protocol may comply or be compatible with a standard promulgated by the International Telecommunication Union-Telecommunication Standardization Sector (ITU-T). Alternatively or additionally, the communication devices may be capable of communicating with each other using a frame relay communications protocol. The frame relay communications protocol may comply or be compatible with a standard promulgated by Consultative Committee for International Telegraph and Telephone (CCITT) and/or the American National Standards Institute (ANSI). Alternatively or additionally, the transceivers may be capable of communicating with each other using an Asynchronous Transfer Mode (ATM) communications protocol. The ATM communications protocol may comply or be compatible with an ATM standard published by the ATM Forum titled “ATM-MPLS Network Interworking 2.0” published August 2001, and/or later versions of this standard. Of course, different and/or after-developed connection-oriented network communication protocols are equally contemplated herein.
Unless specifically stated otherwise as apparent from the foregoing disclosure, it is appreciated that, throughout the foregoing disclosure, discussions using terms such as “processing,” “computing,” “calculating,” “determining,” “displaying,” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.
One or more components may be referred to herein as “configured to,” “configurable to,” “operable/operative to,” “adapted/adaptable,” “able to,” “conformable/conformed to,” etc. Those skilled in the art will recognize that “configured to” can generally encompass active-state components and/or inactive-state components and/or standby-state components, unless context requires otherwise.
The terms “proximal” and “distal” are used herein with reference to a clinician manipulating the handle portion of the surgical instrument. The term “proximal” refers to the portion closest to the clinician and the term “distal” refers to the portion located away from the clinician. It will be further appreciated that, for convenience and clarity, spatial terms such as “vertical”, “horizontal”, “up”, and “down” may be used herein with respect to the drawings. However, surgical instruments are used in many orientations and positions, and these terms are not intended to be limiting and/or absolute.
Those skilled in the art will recognize that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as “open” terms (e.g., the term “including” should be interpreted as “including but not limited to,” the term “having” should be interpreted as “having at least,” the term “includes” should be interpreted as “includes but is not limited to,” etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases “at least one” and “one or more” to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles “a” or “an” limits any particular claim containing such introduced claim recitation to claims containing only one such recitation, even when the same claim includes the introductory phrases “one or more” or “at least one” and indefinite articles such as “a” or “an” (e.g., “a” and/or “an” should typically be interpreted to mean “at least one” or “one or more”); the same holds true for the use of definite articles used to introduce claim recitations.
In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be interpreted to mean at least the recited number (e.g., the bare recitation of “two recitations,” without other modifiers, typically means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to “at least one of A, B, or C, etc.” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., “a system having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that typically a disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms unless context dictates otherwise. For example, the phrase “A or B” will be typically understood to include the possibilities of “A” or “B” or “A and B.”
With respect to the appended claims, those skilled in the art will appreciate that recited operations therein may generally be performed in any order. Also, although various operational flow diagrams are presented in a sequence(s), it should be understood that the various operations may be performed in other orders than those which are illustrated, or may be performed concurrently. Examples of such alternate orderings may include overlapping, interleaved, interrupted, reordered, incremental, preparatory, supplemental, simultaneous, reverse, or other variant orderings, unless context dictates otherwise. Furthermore, terms like “responsive to,” “related to,” or other past-tense adjectives are generally not intended to exclude such variants, unless context dictates otherwise.
It is worthy to note that any reference to “one aspect,” “an aspect,” “an exemplification,” “one exemplification,” and the like means that a particular feature, structure, or characteristic described in connection with the aspect is included in at least one aspect. Thus, appearances of the phrases “in one aspect,” “in an aspect,” “in an exemplification,” and “in one exemplification” in various places throughout the specification are not necessarily all referring to the same aspect. Furthermore, the particular features, structures or characteristics may be combined in any suitable manner in one or more aspects.
Any patent application, patent, non-patent publication, or other disclosure material referred to in this specification and/or listed in any Application Data Sheet is incorporated by reference herein, to the extent that the incorporated materials is not inconsistent herewith. As such, and to the extent necessary, the disclosure as explicitly set forth herein supersedes any conflicting material incorporated herein by reference. Any material, or portion thereof, that is said to be incorporated by reference herein, but which conflicts with existing definitions, statements, or other disclosure material set forth herein will only be incorporated to the extent that no conflict arises between that incorporated material and the existing disclosure material.
In summary, numerous benefits have been described which result from employing the concepts described herein. The foregoing description of the one or more forms has been presented for purposes of illustration and description. It is not intended to be exhaustive or limiting to the precise form disclosed. Modifications or variations are possible in light of the above teachings. The one or more forms were chosen and described in order to illustrate principles and practical application to thereby enable one of ordinary skill in the art to utilize the various forms and with various modifications as are suited to the particular use contemplated. It is intended that the claims submitted herewith define the overall scope.
The present application is a continuation application claiming priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 16/182,242, titled REAL-TIME ANALYSIS OF COMPREHENSIVE COST OF ALL INSTRUMENTATION USED IN SURGERY UTILIZING DATA FLUIDITY TO TRACK INSTRUMENTS THROUGH STOCKING AND IN-HOUSE PROCESSES, filed on Nov. 6, 2018, now U.S. Patent Application Publication No. 2019/0206556, which claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No. 62/729,191, titled SURGICAL NETWORK RECOMMENDATIONS FROM REAL TIME ANALYSIS OF PROCEDURE VARIABLES AGAINST A BASELINE HIGHLIGHTING DIFFERENCES FROM THE OPTIMAL SOLUTION, filed on Sep. 10, 2018, the disclosure of each of which is herein incorporated by reference in its entirety. The present application is a continuation application claiming priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 16/182,242, titled REAL-TIME ANALYSIS OF COMPREHENSIVE COST OF ALL INSTRUMENTATION USED IN SURGERY UTILIZING DATA FLUIDITY TO TRACK INSTRUMENTS THROUGH STOCKING AND IN-HOUSE PROCESSES, filed on Nov. 6, 2018, now U.S. Patent Application Publication No. 2019/0206556, which also claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No. 62/692,747, titled SMART ACTIVATION OF AN ENERGY DEVICE BY ANOTHER DEVICE, filed on Jun. 30, 2018, to U.S. Provisional Patent Application Ser. No. 62/692,748, titled SMART ENERGY ARCHITECTURE, filed on Jun. 30, 2018, and to U.S. Provisional Patent Application Ser. No. 62/692,768, titled SMART ENERGY DEVICES, filed on Jun. 30, 2018, the disclosure of each of which is herein incorporated by reference in its entirety. The present application is a continuation application claiming priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 16/182,242, titled REAL-TIME ANALYSIS OF COMPREHENSIVE COST OF ALL INSTRUMENTATION USED IN SURGERY UTILIZING DATA FLUIDITY TO TRACK INSTRUMENTS THROUGH STOCKING AND IN-HOUSE PROCESSES, filed on Nov. 6, 2018, now U.S. Patent Application Publication No. 2019/0206556, which also claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No. 62/659,900, titled METHOD OF HUB COMMUNICATION, filed on Apr. 19, 2018, the disclosure of each of which is herein incorporated by reference in its entirety. The present application is a continuation application claiming priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 16/182,242, titled REAL-TIME ANALYSIS OF COMPREHENSIVE COST OF ALL INSTRUMENTATION USED IN SURGERY UTILIZING DATA FLUIDITY TO TRACK INSTRUMENTS THROUGH STOCKING AND IN-HOUSE PROCESSES, filed on Nov. 6, 2018, now U.S. Patent Application Publication No. 2019/0206556, which also claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No. 62/650,898 filed on Mar. 30, 2018, titled CAPACITIVE COUPLED RETURN PATH PAD WITH SEPARABLE ARRAY ELEMENTS, to U.S. Provisional Patent Application Ser. No. 62/650,887, titled SURGICAL SYSTEMS WITH OPTIMIZED SENSING CAPABILITIES, filed Mar. 30, 2018, to U.S. Provisional Patent Application Ser. No. 62/650,882, titled SMOKE EVACUATION MODULE FOR INTERACTIVE SURGICAL PLATFORM, filed Mar. 30, 2018, and to U.S. Provisional Patent Application Ser. No. 62/650,877, titled SURGICAL SMOKE EVACUATION SENSING AND CONTROLS, filed Mar. 30, 2018, the disclosure of each of which is herein incorporated by reference in its entirety. The present application is a continuation application claiming priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 16/182,242, titled REAL-TIME ANALYSIS OF COMPREHENSIVE COST OF ALL INSTRUMENTATION USED IN SURGERY UTILIZING DATA FLUIDITY TO TRACK INSTRUMENTS THROUGH STOCKING AND IN-HOUSE PROCESSES, filed on Nov. 6, 2018, now U.S. Patent Application Publication No. 2019/0206556, which also claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No. 62/640,417, titled TEMPERATURE CONTROL IN ULTRASONIC DEVICE AND CONTROL SYSTEM THEREFOR, filed Mar. 8, 2018, and to U.S. Provisional Patent Application Ser. No. 62/640,415, titled ESTIMATING STATE OF ULTRASONIC END EFFECTOR AND CONTROL SYSTEM THEREFOR, filed Mar. 8, 2018, the disclosure of each of which is herein incorporated by reference in its entirety. The present application is a continuation application claiming priority under 35 U.S.C. § 120 to U.S. patent application Ser. No. 16/182,242, titled REAL-TIME ANALYSIS OF COMPREHENSIVE COST OF ALL INSTRUMENTATION USED IN SURGERY UTILIZING DATA FLUIDITY TO TRACK INSTRUMENTS THROUGH STOCKING AND IN-HOUSE PROCESSES, filed on Nov. 6, 2018, now U.S. Patent Application Publication No. 2019/0206556, which also claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application Ser. No. 62/611,341, titled INTERACTIVE SURGICAL PLATFORM, filed Dec. 28, 2017, to U.S. Provisional Patent Application Ser. No. 62/611,340, titled CLOUD-BASED MEDICAL ANALYTICS, filed Dec. 28, 2017, and to U.S. Provisional Patent Application Ser. No. 62/611,339, titled ROBOT ASSISTED SURGICAL PLATFORM, filed Dec. 28, 2017, the disclosure of each of which is herein incorporated by reference in its entirety.
| Number | Name | Date | Kind |
|---|---|---|---|
| 1853416 | Hall | Apr 1932 | A |
| 2222125 | Stehlik | Nov 1940 | A |
| 3082426 | Miles | Mar 1963 | A |
| 3503396 | Pierie et al. | Mar 1970 | A |
| 3584628 | Green | Jun 1971 | A |
| 3626457 | Duerr et al. | Dec 1971 | A |
| 3633584 | Farrell | Jan 1972 | A |
| 3759017 | Young | Sep 1973 | A |
| 3863118 | Lander et al. | Jan 1975 | A |
| 3898545 | Coppa et al. | Aug 1975 | A |
| 3912121 | Steffen | Oct 1975 | A |
| 3915271 | Harper | Oct 1975 | A |
| 3932812 | Milligan | Jan 1976 | A |
| 4041362 | Ichiyanagi | Aug 1977 | A |
| 4052649 | Greenwell et al. | Oct 1977 | A |
| 4087730 | Goles | May 1978 | A |
| 4157859 | Terry | Jun 1979 | A |
| 4171700 | Farin | Oct 1979 | A |
| 4202722 | Paquin | May 1980 | A |
| 4412539 | Jarvik | Nov 1983 | A |
| 4448193 | Ivanov | May 1984 | A |
| 4523695 | Braun et al. | Jun 1985 | A |
| 4608160 | Zoch | Aug 1986 | A |
| 4614366 | North et al. | Sep 1986 | A |
| 4633874 | Chow et al. | Jan 1987 | A |
| 4701193 | Robertson et al. | Oct 1987 | A |
| 4735603 | Goodson et al. | Apr 1988 | A |
| 4779687 | Schreiber et al. | Oct 1988 | A |
| 4788977 | Farin et al. | Dec 1988 | A |
| 4827911 | Broadwin et al. | May 1989 | A |
| 4849752 | Bryant | Jul 1989 | A |
| D303787 | Messenger et al. | Oct 1989 | S |
| 4892244 | Fox et al. | Jan 1990 | A |
| 4962681 | Yang | Oct 1990 | A |
| 4976173 | Yang | Dec 1990 | A |
| 5010341 | Huntley et al. | Apr 1991 | A |
| 5026387 | Thomas | Jun 1991 | A |
| 5035692 | Lyon et al. | Jul 1991 | A |
| 5042460 | Sakurai et al. | Aug 1991 | A |
| 5047043 | Kubota et al. | Sep 1991 | A |
| 5084057 | Green et al. | Jan 1992 | A |
| 5100402 | Fan | Mar 1992 | A |
| D327061 | Soren et al. | Jun 1992 | S |
| 5129570 | Schulze et al. | Jul 1992 | A |
| 5151102 | Kamiyama et al. | Sep 1992 | A |
| 5156315 | Green et al. | Oct 1992 | A |
| 5158585 | Saho et al. | Oct 1992 | A |
| 5160334 | Billings et al. | Nov 1992 | A |
| 5171247 | Hughett et al. | Dec 1992 | A |
| 5189277 | Boisvert et al. | Feb 1993 | A |
| 5197962 | Sansom et al. | Mar 1993 | A |
| 5204669 | Dorfe et al. | Apr 1993 | A |
| 5217003 | Wilk | Jun 1993 | A |
| 5242474 | Herbst et al. | Sep 1993 | A |
| 5253793 | Green et al. | Oct 1993 | A |
| 5271543 | Grant et al. | Dec 1993 | A |
| RE34519 | Fox et al. | Jan 1994 | E |
| 5275323 | Schulze et al. | Jan 1994 | A |
| 5318516 | Cosmescu | Jun 1994 | A |
| 5318563 | Malis et al. | Jun 1994 | A |
| 5322055 | Davison et al. | Jun 1994 | A |
| 5342349 | Kaufman | Aug 1994 | A |
| 5364003 | Williamson, IV | Nov 1994 | A |
| 5383880 | Hooven | Jan 1995 | A |
| 5385544 | Edwards et al. | Jan 1995 | A |
| 5391144 | Sakurai et al. | Feb 1995 | A |
| 5396900 | Slater et al. | Mar 1995 | A |
| 5397046 | Savage et al. | Mar 1995 | A |
| 5403312 | Yates et al. | Apr 1995 | A |
| 5403327 | Thornton et al. | Apr 1995 | A |
| 5413267 | Solyntjes et al. | May 1995 | A |
| 5415335 | Knodell, Jr. | May 1995 | A |
| 5417699 | Klein et al. | May 1995 | A |
| 5439468 | Schulze et al. | Aug 1995 | A |
| 5445304 | Plyley et al. | Aug 1995 | A |
| 5462545 | Wang et al. | Oct 1995 | A |
| 5465895 | Knodel et al. | Nov 1995 | A |
| 5467911 | Tsuruta et al. | Nov 1995 | A |
| 5474566 | Alesi et al. | Dec 1995 | A |
| 5485947 | Olson et al. | Jan 1996 | A |
| 5496315 | Weaver et al. | Mar 1996 | A |
| 5496317 | Goble et al. | Mar 1996 | A |
| 5503320 | Webster et al. | Apr 1996 | A |
| 5507773 | Huitema et al. | Apr 1996 | A |
| 5529235 | Boiarski et al. | Jun 1996 | A |
| 5531743 | Nettekoven et al. | Jul 1996 | A |
| 5545148 | Wurster | Aug 1996 | A |
| 5552685 | Young et al. | Sep 1996 | A |
| 5560372 | Cory | Oct 1996 | A |
| 5584425 | Savage et al. | Dec 1996 | A |
| 5607436 | Pratt et al. | Mar 1997 | A |
| 5610379 | Muz et al. | Mar 1997 | A |
| 5610811 | Honda | Mar 1997 | A |
| 5613966 | Makower et al. | Mar 1997 | A |
| 5619881 | Morikawa et al. | Apr 1997 | A |
| 5624452 | Yates | Apr 1997 | A |
| D379346 | Mieki | May 1997 | S |
| 5626587 | Bishop et al. | May 1997 | A |
| 5643291 | Pier et al. | Jul 1997 | A |
| 5654750 | Weil et al. | Aug 1997 | A |
| 5673841 | Schulze et al. | Oct 1997 | A |
| 5673842 | Bittner et al. | Oct 1997 | A |
| 5675227 | Roos et al. | Oct 1997 | A |
| 5693042 | Boiarski et al. | Dec 1997 | A |
| 5693052 | Weaver | Dec 1997 | A |
| 5695502 | Pier et al. | Dec 1997 | A |
| 5697926 | Weaver | Dec 1997 | A |
| 5706998 | Plyley et al. | Jan 1998 | A |
| 5718359 | Palmer et al. | Feb 1998 | A |
| 5720287 | Chapelon et al. | Feb 1998 | A |
| 5724468 | Leone et al. | Mar 1998 | A |
| 5725536 | Oberlin et al. | Mar 1998 | A |
| 5725542 | Yoon | Mar 1998 | A |
| 5735445 | Vidal et al. | Apr 1998 | A |
| 5735848 | Yates et al. | Apr 1998 | A |
| 5746209 | Yost et al. | May 1998 | A |
| 5749362 | Funda et al. | May 1998 | A |
| 5749893 | Vidal et al. | May 1998 | A |
| 5752644 | Bolanos et al. | May 1998 | A |
| 5762255 | Chrisman et al. | Jun 1998 | A |
| 5762458 | Wang et al. | Jun 1998 | A |
| 5766186 | Faraz et al. | Jun 1998 | A |
| 5769791 | Benaron et al. | Jun 1998 | A |
| 5775331 | Raymond et al. | Jul 1998 | A |
| 5796188 | Bays | Aug 1998 | A |
| 5797537 | Oberlin et al. | Aug 1998 | A |
| 5800350 | Coppleson et al. | Sep 1998 | A |
| 5807393 | Williamson, IV et al. | Sep 1998 | A |
| D399561 | Ellingson | Oct 1998 | S |
| 5817093 | Williamson, IV et al. | Oct 1998 | A |
| 5820009 | Melling et al. | Oct 1998 | A |
| 5833690 | Yates et al. | Nov 1998 | A |
| 5836849 | Mathiak et al. | Nov 1998 | A |
| 5836869 | Kudo et al. | Nov 1998 | A |
| 5836909 | Cosmescu | Nov 1998 | A |
| 5843080 | Fleenor et al. | Dec 1998 | A |
| 5846237 | Nettekoven | Dec 1998 | A |
| 5849022 | Sakashita et al. | Dec 1998 | A |
| 5873873 | Smith et al. | Feb 1999 | A |
| 5878938 | Bittner et al. | Mar 1999 | A |
| 5893849 | Weaver | Apr 1999 | A |
| 5906625 | Bito et al. | May 1999 | A |
| 5942333 | Arnett et al. | Aug 1999 | A |
| 5947996 | Logeman | Sep 1999 | A |
| 5968032 | Sleister | Oct 1999 | A |
| 5980510 | Tsonton et al. | Nov 1999 | A |
| 5987346 | Benaron et al. | Nov 1999 | A |
| 5997528 | Bisch et al. | Dec 1999 | A |
| 6004269 | Crowley et al. | Dec 1999 | A |
| 6010054 | Johnson et al. | Jan 2000 | A |
| 6030437 | Gourrier et al. | Feb 2000 | A |
| 6036637 | Kudo | Mar 2000 | A |
| 6039734 | Goble | Mar 2000 | A |
| 6039735 | Greep | Mar 2000 | A |
| 6059799 | Aranyi et al. | May 2000 | A |
| 6066137 | Greep | May 2000 | A |
| 6079606 | Milliman et al. | Jun 2000 | A |
| 6090107 | Borgmeier et al. | Jul 2000 | A |
| 6099537 | Sugai et al. | Aug 2000 | A |
| 6102907 | Smethers et al. | Aug 2000 | A |
| 6109500 | Alli et al. | Aug 2000 | A |
| 6113598 | Baker | Sep 2000 | A |
| 6126592 | Proch et al. | Oct 2000 | A |
| 6126658 | Baker | Oct 2000 | A |
| 6131789 | Schulze et al. | Oct 2000 | A |
| 6139561 | Shibata et al. | Oct 2000 | A |
| 6155473 | Tompkins et al. | Dec 2000 | A |
| 6214000 | Fleenor et al. | Apr 2001 | B1 |
| 6258105 | Hart et al. | Jul 2001 | B1 |
| 6269411 | Reasoner | Jul 2001 | B1 |
| 6273887 | Yamauchi et al. | Aug 2001 | B1 |
| 6283960 | Ashley | Sep 2001 | B1 |
| 6301495 | Gueziec et al. | Oct 2001 | B1 |
| 6302881 | Farin | Oct 2001 | B1 |
| 6308089 | von der Ruhr | Oct 2001 | B1 |
| 6325808 | Bernard et al. | Dec 2001 | B1 |
| 6325811 | Messerly | Dec 2001 | B1 |
| 6331181 | Tierney et al. | Dec 2001 | B1 |
| 6341164 | Dilkie et al. | Jan 2002 | B1 |
| 6391102 | Bodden et al. | May 2002 | B1 |
| 6423057 | He et al. | Jul 2002 | B1 |
| 6434416 | Mizoguchi et al. | Aug 2002 | B1 |
| 6443973 | Whitman | Sep 2002 | B1 |
| 6451015 | Rittman, III et al. | Sep 2002 | B1 |
| 6454781 | Witt et al. | Sep 2002 | B1 |
| 6457625 | Tormala et al. | Oct 2002 | B1 |
| 6461352 | Morgan et al. | Oct 2002 | B2 |
| 6466817 | Kaula et al. | Oct 2002 | B1 |
| 6480796 | Wiener | Nov 2002 | B2 |
| 6482217 | Pintor et al. | Nov 2002 | B1 |
| 6524307 | Palmerton et al. | Feb 2003 | B1 |
| 6530933 | Yeung et al. | Mar 2003 | B1 |
| 6551243 | Bocionek et al. | Apr 2003 | B2 |
| 6569109 | Sakurai et al. | May 2003 | B2 |
| 6582424 | Fleenor et al. | Jun 2003 | B2 |
| 6584358 | Carter et al. | Jun 2003 | B2 |
| 6585791 | Garito et al. | Jul 2003 | B1 |
| 6611793 | Burnside et al. | Aug 2003 | B1 |
| 6618626 | West, Jr. et al. | Sep 2003 | B2 |
| 6628989 | Penner et al. | Sep 2003 | B1 |
| 6633234 | Wiener et al. | Oct 2003 | B2 |
| 6648223 | Boukhny et al. | Nov 2003 | B2 |
| 6678552 | Pearlman | Jan 2004 | B2 |
| 6679899 | Wiener et al. | Jan 2004 | B2 |
| 6685704 | Greep | Feb 2004 | B2 |
| 6695199 | Whitman | Feb 2004 | B2 |
| 6699187 | Webb et al. | Mar 2004 | B2 |
| 6731514 | Evans | May 2004 | B2 |
| 6742895 | Robin | Jun 2004 | B2 |
| 6752816 | Culp et al. | Jun 2004 | B2 |
| 6760616 | Hoey et al. | Jul 2004 | B2 |
| 6770072 | Truckai et al. | Aug 2004 | B1 |
| 6773444 | Messerly | Aug 2004 | B2 |
| 6775575 | Bommannan et al. | Aug 2004 | B2 |
| 6778846 | Martinez et al. | Aug 2004 | B1 |
| 6781683 | Kacyra et al. | Aug 2004 | B2 |
| 6783524 | Anderson et al. | Aug 2004 | B2 |
| 6783525 | Greep et al. | Aug 2004 | B2 |
| 6793652 | Whitman et al. | Sep 2004 | B1 |
| 6793663 | Kneifel et al. | Sep 2004 | B2 |
| 6824539 | Novak | Nov 2004 | B2 |
| 6846308 | Whitman et al. | Jan 2005 | B2 |
| 6849071 | Whitman et al. | Feb 2005 | B2 |
| 6849074 | Chen et al. | Feb 2005 | B2 |
| 6852219 | Hammond | Feb 2005 | B2 |
| 6863650 | Irion | Mar 2005 | B1 |
| 6869430 | Balbierz et al. | Mar 2005 | B2 |
| 6869435 | Blake, III | Mar 2005 | B2 |
| 6911033 | de Guillebon et al. | Jun 2005 | B2 |
| 6913471 | Smith | Jul 2005 | B2 |
| 6937892 | Leyde et al. | Aug 2005 | B2 |
| 6945981 | Donofrio et al. | Sep 2005 | B2 |
| 6951559 | Greep | Oct 2005 | B1 |
| 6962587 | Johnson et al. | Nov 2005 | B2 |
| 6978921 | Shelton, IV et al. | Dec 2005 | B2 |
| 6988649 | Shelton, IV et al. | Jan 2006 | B2 |
| 7000818 | Shelton, IV et al. | Feb 2006 | B2 |
| 7009511 | Mazar et al. | Mar 2006 | B2 |
| 7030146 | Baynes et al. | Apr 2006 | B2 |
| 7032798 | Whitman et al. | Apr 2006 | B2 |
| 7041941 | Faries, Jr. et al. | May 2006 | B2 |
| 7044352 | Shelton, IV et al. | May 2006 | B2 |
| 7044911 | Drinan et al. | May 2006 | B2 |
| 7044949 | Orszulak et al. | May 2006 | B2 |
| 7048775 | Jornitz et al. | May 2006 | B2 |
| 7053752 | Wang et al. | May 2006 | B2 |
| 7055730 | Ehrenfels et al. | Jun 2006 | B2 |
| 7073765 | Newkirk | Jul 2006 | B2 |
| 7077853 | Kramer et al. | Jul 2006 | B2 |
| 7077856 | Whitman | Jul 2006 | B2 |
| 7081096 | Brister et al. | Jul 2006 | B2 |
| 7094231 | Ellman et al. | Aug 2006 | B1 |
| 7097640 | Wang et al. | Aug 2006 | B2 |
| 7103688 | Strong | Sep 2006 | B2 |
| 7104949 | Anderson et al. | Sep 2006 | B2 |
| 7118564 | Ritchie et al. | Oct 2006 | B2 |
| 7121460 | Parsons et al. | Oct 2006 | B1 |
| 7137980 | Buysse et al. | Nov 2006 | B2 |
| 7140528 | Shelton, IV | Nov 2006 | B2 |
| 7143923 | Shelton, IV et al. | Dec 2006 | B2 |
| 7143925 | Shelton, IV et al. | Dec 2006 | B2 |
| 7147139 | Schwemberger et al. | Dec 2006 | B2 |
| 7155316 | Sutherland et al. | Dec 2006 | B2 |
| 7164940 | Hareyama et al. | Jan 2007 | B2 |
| 7169145 | Isaacson et al. | Jan 2007 | B2 |
| 7177533 | McFarlin et al. | Feb 2007 | B2 |
| 7182775 | de Guillebon et al. | Feb 2007 | B2 |
| 7207472 | Wukusick et al. | Apr 2007 | B2 |
| 7208005 | Frecker et al. | Apr 2007 | B2 |
| 7217269 | El-Galley et al. | May 2007 | B2 |
| 7230529 | Ketcherside, Jr. et al. | Jun 2007 | B2 |
| 7232447 | Gellman et al. | Jun 2007 | B2 |
| 7236817 | Papas et al. | Jun 2007 | B2 |
| 7246734 | Shelton, IV | Jul 2007 | B2 |
| 7252664 | Nasab et al. | Aug 2007 | B2 |
| 7278563 | Green | Oct 2007 | B1 |
| 7294106 | Birkenbach et al. | Nov 2007 | B2 |
| 7294116 | Ellman et al. | Nov 2007 | B1 |
| 7296724 | Green et al. | Nov 2007 | B2 |
| 7317955 | McGreevy | Jan 2008 | B2 |
| 7328828 | Ortiz et al. | Feb 2008 | B2 |
| 7334717 | Rethy et al. | Feb 2008 | B2 |
| 7343565 | Ying et al. | Mar 2008 | B2 |
| 7344532 | Goble et al. | Mar 2008 | B2 |
| 7353068 | Tanaka et al. | Apr 2008 | B2 |
| 7362228 | Nycz et al. | Apr 2008 | B2 |
| 7371227 | Zeiner | May 2008 | B2 |
| 7380695 | Doll et al. | Jun 2008 | B2 |
| 7383088 | Spinelli et al. | Jun 2008 | B2 |
| 7391173 | Schena | Jun 2008 | B2 |
| 7407074 | Ortiz et al. | Aug 2008 | B2 |
| 7408439 | Wang et al. | Aug 2008 | B2 |
| 7413541 | Konishi | Aug 2008 | B2 |
| 7422136 | Marczyk | Sep 2008 | B1 |
| 7422139 | Shelton, IV et al. | Sep 2008 | B2 |
| 7422586 | Morris et al. | Sep 2008 | B2 |
| 7423972 | Shaham et al. | Sep 2008 | B2 |
| D579876 | Novotney et al. | Nov 2008 | S |
| 7445620 | Kefer | Nov 2008 | B2 |
| 7457804 | Uber, III et al. | Nov 2008 | B2 |
| D583328 | Chiang | Dec 2008 | S |
| 7464847 | Viola et al. | Dec 2008 | B2 |
| 7464849 | Shelton, IV et al. | Dec 2008 | B2 |
| 7496418 | Kim et al. | Feb 2009 | B2 |
| D589447 | Sasada et al. | Mar 2009 | S |
| 7515961 | Germanson et al. | Apr 2009 | B2 |
| 7518502 | Austin et al. | Apr 2009 | B2 |
| 7554343 | Bromfield | Jun 2009 | B2 |
| 7563259 | Takahashi | Jul 2009 | B2 |
| 7568604 | Ehrenfels et al. | Aug 2009 | B2 |
| 7575144 | Ortiz et al. | Aug 2009 | B2 |
| 7597731 | Palmerton et al. | Oct 2009 | B2 |
| 7621192 | Conti et al. | Nov 2009 | B2 |
| 7621898 | Lalomia et al. | Nov 2009 | B2 |
| 7631793 | Rethy et al. | Dec 2009 | B2 |
| 7637410 | Marczyk | Dec 2009 | B2 |
| 7637907 | Blaha | Dec 2009 | B2 |
| 7641092 | Kruszynski et al. | Jan 2010 | B2 |
| 7644848 | Swayze et al. | Jan 2010 | B2 |
| 7667592 | Ohyama et al. | Feb 2010 | B2 |
| 7667839 | Bates | Feb 2010 | B2 |
| 7670334 | Hueil et al. | Mar 2010 | B2 |
| 7694865 | Scirica | Apr 2010 | B2 |
| 7699772 | Pauker et al. | Apr 2010 | B2 |
| 7699860 | Huitema et al. | Apr 2010 | B2 |
| 7717312 | Beetel | May 2010 | B2 |
| 7720306 | Gardiner et al. | May 2010 | B2 |
| 7721934 | Shelton, IV et al. | May 2010 | B2 |
| 7721936 | Shalton, IV et al. | May 2010 | B2 |
| 7722603 | McPherson | May 2010 | B2 |
| 7736357 | Lee, Jr. et al. | Jun 2010 | B2 |
| 7742176 | Braunecker et al. | Jun 2010 | B2 |
| 7743960 | Whitman et al. | Jun 2010 | B2 |
| 7753245 | Boudreaux et al. | Jul 2010 | B2 |
| 7757028 | Druke et al. | Jul 2010 | B2 |
| 7766207 | Mather et al. | Aug 2010 | B2 |
| 7766905 | Paterson et al. | Aug 2010 | B2 |
| 7770773 | Whitman et al. | Aug 2010 | B2 |
| 7771429 | Ballard et al. | Aug 2010 | B2 |
| 7776037 | Odom | Aug 2010 | B2 |
| 7782789 | Stultz et al. | Aug 2010 | B2 |
| 7784663 | Shelton, IV | Aug 2010 | B2 |
| 7803151 | Whitman | Sep 2010 | B2 |
| 7810692 | Hall et al. | Oct 2010 | B2 |
| 7818041 | Kim et al. | Oct 2010 | B2 |
| 7819298 | Hall et al. | Oct 2010 | B2 |
| 7832612 | Baxter, III et al. | Nov 2010 | B2 |
| 7833219 | Tashiro et al. | Nov 2010 | B2 |
| 7836085 | Petakov et al. | Nov 2010 | B2 |
| 7837079 | Holsten et al. | Nov 2010 | B2 |
| 7837680 | Isaacson et al. | Nov 2010 | B2 |
| 7841980 | Minosawa et al. | Nov 2010 | B2 |
| 7845537 | Shelton, IV et al. | Dec 2010 | B2 |
| 7857185 | Swayze et al. | Dec 2010 | B2 |
| D631252 | Leslie | Jan 2011 | S |
| 7862560 | Marion | Jan 2011 | B2 |
| 7862579 | Ortiz et al. | Jan 2011 | B2 |
| 7865236 | Cory et al. | Jan 2011 | B2 |
| 7884735 | Newkirk | Feb 2011 | B2 |
| 7887530 | Zemlok et al. | Feb 2011 | B2 |
| 7892337 | Palmerton et al. | Feb 2011 | B2 |
| 7907166 | Lamprecht et al. | Mar 2011 | B2 |
| 7913891 | Doll et al. | Mar 2011 | B2 |
| 7918230 | Whitman et al. | Apr 2011 | B2 |
| 7918377 | Measamer et al. | Apr 2011 | B2 |
| 7920706 | Asokan et al. | Apr 2011 | B2 |
| 7922063 | Zemlok et al. | Apr 2011 | B2 |
| 7927014 | Dehler | Apr 2011 | B2 |
| 7932826 | Fritchie et al. | Apr 2011 | B2 |
| 7942300 | Rethy et al. | May 2011 | B2 |
| 7945065 | Menzl et al. | May 2011 | B2 |
| 7945342 | Tsai et al. | May 2011 | B2 |
| 7950560 | Zemlok et al. | May 2011 | B2 |
| 7951148 | McClurken | May 2011 | B2 |
| 7954682 | Giordano et al. | Jun 2011 | B2 |
| 7954687 | Zemlok et al. | Jun 2011 | B2 |
| 7955322 | Devengenzo et al. | Jun 2011 | B2 |
| 7956620 | Gilbert | Jun 2011 | B2 |
| 7963433 | Whitman et al. | Jun 2011 | B2 |
| 7966269 | Bauer et al. | Jun 2011 | B2 |
| 7967180 | Scirica | Jun 2011 | B2 |
| 7976553 | Shelton, IV et al. | Jul 2011 | B2 |
| 7979157 | Anvari | Jul 2011 | B2 |
| 7980443 | Scheib et al. | Jul 2011 | B2 |
| 7982776 | Dunki-Jacobs et al. | Jul 2011 | B2 |
| 7988028 | Farascioni et al. | Aug 2011 | B2 |
| 7993140 | Sakezles | Aug 2011 | B2 |
| 7993354 | Brecher et al. | Aug 2011 | B1 |
| 7993954 | Wieting | Aug 2011 | B2 |
| 7995045 | Dunki-Jacobs | Aug 2011 | B2 |
| 8005947 | Morris et al. | Aug 2011 | B2 |
| 8007494 | Taylor et al. | Aug 2011 | B1 |
| 8007513 | Nalagatla et al. | Aug 2011 | B2 |
| 8010180 | Quaid et al. | Aug 2011 | B2 |
| 8012170 | Whitman et al. | Sep 2011 | B2 |
| 8015976 | Shah | Sep 2011 | B2 |
| 8016855 | Whitman et al. | Sep 2011 | B2 |
| 8019094 | Hsieh et al. | Sep 2011 | B2 |
| 8025199 | Whitman et al. | Sep 2011 | B2 |
| 8027710 | Dannan | Sep 2011 | B1 |
| 8035685 | Jensen | Oct 2011 | B2 |
| 8038686 | Huitema et al. | Oct 2011 | B2 |
| 8038693 | Allen | Oct 2011 | B2 |
| 8043560 | Okumoto et al. | Oct 2011 | B2 |
| 8054184 | Cline et al. | Nov 2011 | B2 |
| 8054752 | Druke et al. | Nov 2011 | B2 |
| 8062306 | Nobis et al. | Nov 2011 | B2 |
| 8062330 | Prommersberger et al. | Nov 2011 | B2 |
| 8066721 | Kortenbach et al. | Nov 2011 | B2 |
| 8074861 | Ehrenfels et al. | Dec 2011 | B2 |
| 8075571 | Vitali et al. | Dec 2011 | B2 |
| 8095327 | Tahara et al. | Jan 2012 | B2 |
| 8096459 | Ortiz et al. | Jan 2012 | B2 |
| 8116848 | Shahidi | Feb 2012 | B2 |
| 8118206 | Zand et al. | Feb 2012 | B2 |
| 8120301 | Goldberg et al. | Feb 2012 | B2 |
| 8123764 | Meade et al. | Feb 2012 | B2 |
| D655678 | Kobayashi et al. | Mar 2012 | S |
| 8128625 | Odom | Mar 2012 | B2 |
| 8131565 | Dicks et al. | Mar 2012 | B2 |
| 8136712 | Zingman | Mar 2012 | B2 |
| 8146149 | Steinkogler et al. | Mar 2012 | B2 |
| D657368 | Magee et al. | Apr 2012 | S |
| 8147486 | Honour et al. | Apr 2012 | B2 |
| 8155479 | Hoffman et al. | Apr 2012 | B2 |
| 8157145 | Shelton, IV et al. | Apr 2012 | B2 |
| 8157150 | Viola et al. | Apr 2012 | B2 |
| 8157151 | Ingmanson et al. | Apr 2012 | B2 |
| 8160098 | Yan et al. | Apr 2012 | B1 |
| 8160690 | Wilfley et al. | Apr 2012 | B2 |
| 8161977 | Shelton, IV et al. | Apr 2012 | B2 |
| 8170396 | Kuspa et al. | May 2012 | B2 |
| 8172836 | Ward | May 2012 | B2 |
| 8181839 | Beetel | May 2012 | B2 |
| 8185409 | Putnam et al. | May 2012 | B2 |
| 8206345 | Abboud et al. | Jun 2012 | B2 |
| 8208707 | Mendonca et al. | Jun 2012 | B2 |
| 8210411 | Yates et al. | Jul 2012 | B2 |
| 8211100 | Podhajsky et al. | Jul 2012 | B2 |
| 8214007 | Baker et al. | Jul 2012 | B2 |
| 8216849 | Petty | Jul 2012 | B2 |
| 8220688 | Laurent et al. | Jul 2012 | B2 |
| 8225643 | Abboud et al. | Jul 2012 | B2 |
| 8225979 | Farascioni et al. | Jul 2012 | B2 |
| 8229549 | Whitman et al. | Jul 2012 | B2 |
| 8231042 | Hessler et al. | Jul 2012 | B2 |
| 8239066 | Jennings et al. | Aug 2012 | B2 |
| 8241322 | Whitman et al. | Aug 2012 | B2 |
| 8255045 | Gharib et al. | Aug 2012 | B2 |
| D667838 | Magee et al. | Sep 2012 | S |
| 8257387 | Cunningham | Sep 2012 | B2 |
| 8260016 | Maeda et al. | Sep 2012 | B2 |
| 8262560 | Whitman | Sep 2012 | B2 |
| 8292639 | Achammer et al. | Oct 2012 | B2 |
| 8292888 | Whitman | Oct 2012 | B2 |
| 8295902 | Salahieh et al. | Oct 2012 | B2 |
| 8308040 | Huang et al. | Nov 2012 | B2 |
| 8321581 | Katis et al. | Nov 2012 | B2 |
| 8322590 | Patel et al. | Dec 2012 | B2 |
| 8328065 | Shah | Dec 2012 | B2 |
| 8335590 | Costa et al. | Dec 2012 | B2 |
| D675164 | Kobayashi et al. | Jan 2013 | S |
| 8343065 | Bartol et al. | Jan 2013 | B2 |
| 8346392 | Walser et al. | Jan 2013 | B2 |
| 8360299 | Zemlok et al. | Jan 2013 | B2 |
| 8364222 | Cook et al. | Jan 2013 | B2 |
| D676392 | Gassauer | Feb 2013 | S |
| 8365975 | Manoux et al. | Feb 2013 | B1 |
| D678196 | Miyauchi et al. | Mar 2013 | S |
| D678304 | Yakoub et al. | Mar 2013 | S |
| 8388652 | Viola | Mar 2013 | B2 |
| 8393514 | Shelton, IV et al. | Mar 2013 | B2 |
| 8397972 | Kostrzewski | Mar 2013 | B2 |
| 8398541 | DiMaio et al. | Mar 2013 | B2 |
| 8403944 | Pain et al. | Mar 2013 | B2 |
| 8403945 | Whitfield et al. | Mar 2013 | B2 |
| 8403946 | Whitfield et al. | Mar 2013 | B2 |
| 8406859 | Zuzak et al. | Mar 2013 | B2 |
| 8411034 | Boillot et al. | Apr 2013 | B2 |
| 8413871 | Racenet et al. | Apr 2013 | B2 |
| 8422035 | Hinderling et al. | Apr 2013 | B2 |
| 8423182 | Robinson et al. | Apr 2013 | B2 |
| 8428722 | Verhoef et al. | Apr 2013 | B2 |
| 8429153 | Birdwell et al. | Apr 2013 | B2 |
| 8439910 | Greep et al. | May 2013 | B2 |
| 8444663 | Houser et al. | May 2013 | B2 |
| 8452615 | Abri | May 2013 | B2 |
| 8453906 | Huang et al. | Jun 2013 | B2 |
| 8454506 | Rothman et al. | Jun 2013 | B2 |
| 8461744 | Wiener et al. | Jun 2013 | B2 |
| 8468030 | Stroup et al. | Jun 2013 | B2 |
| 8469973 | Meade et al. | Jun 2013 | B2 |
| 8472630 | Konrad et al. | Jun 2013 | B2 |
| 8473066 | Aghassian et al. | Jun 2013 | B2 |
| D687146 | Juzkiw et al. | Jul 2013 | S |
| 8476227 | Kaplan et al. | Jul 2013 | B2 |
| 8478418 | Fahey | Jul 2013 | B2 |
| 8489235 | Moll et al. | Jul 2013 | B2 |
| 8499992 | Whitman et al. | Aug 2013 | B2 |
| 8500728 | Newton et al. | Aug 2013 | B2 |
| 8500756 | Papa et al. | Aug 2013 | B2 |
| 8503759 | Greer et al. | Aug 2013 | B2 |
| 8505801 | Ehrenfels et al. | Aug 2013 | B2 |
| 8506478 | Mizuyoshi | Aug 2013 | B2 |
| 8512325 | Mathonnet | Aug 2013 | B2 |
| 8512365 | Wiener et al. | Aug 2013 | B2 |
| 8515520 | Brunnett et al. | Aug 2013 | B2 |
| 8517239 | Scheib et al. | Aug 2013 | B2 |
| 8521331 | Itkowitz | Aug 2013 | B2 |
| 8523043 | Ullrich et al. | Sep 2013 | B2 |
| 8533475 | Frikart et al. | Sep 2013 | B2 |
| 8535342 | Malackowski et al. | Sep 2013 | B2 |
| 8540709 | Allen | Sep 2013 | B2 |
| 8543240 | Itkowitz et al. | Sep 2013 | B2 |
| 8546996 | Messerly et al. | Oct 2013 | B2 |
| 8554697 | Claus et al. | Oct 2013 | B2 |
| 8560047 | Haider et al. | Oct 2013 | B2 |
| 8561870 | Baxter, III et al. | Oct 2013 | B2 |
| 8562598 | Falkenstein et al. | Oct 2013 | B2 |
| 8566115 | Moore | Oct 2013 | B2 |
| 8567393 | Hickle et al. | Oct 2013 | B2 |
| 8568411 | Falkenstein et al. | Oct 2013 | B2 |
| 8571598 | Valavi | Oct 2013 | B2 |
| 8573459 | Smith et al. | Nov 2013 | B2 |
| 8573465 | Shelton, IV | Nov 2013 | B2 |
| 8574229 | Eder et al. | Nov 2013 | B2 |
| 8585631 | Dacquay | Nov 2013 | B2 |
| 8585694 | Amoah et al. | Nov 2013 | B2 |
| 8590762 | Hess et al. | Nov 2013 | B2 |
| 8591536 | Robertson | Nov 2013 | B2 |
| 8595607 | Nekoomaram et al. | Nov 2013 | B2 |
| 8596513 | Olson et al. | Dec 2013 | B2 |
| 8596515 | Okoniewski | Dec 2013 | B2 |
| 8604709 | Jalbout et al. | Dec 2013 | B2 |
| 8608044 | Hueil et al. | Dec 2013 | B2 |
| 8608045 | Smith et al. | Dec 2013 | B2 |
| 8616431 | Timm et al. | Dec 2013 | B2 |
| 8617155 | Johnson et al. | Dec 2013 | B2 |
| 8620055 | Barratt et al. | Dec 2013 | B2 |
| 8620473 | Diolaiti et al. | Dec 2013 | B2 |
| 8622275 | Baxter, III et al. | Jan 2014 | B2 |
| 8623027 | Price et al. | Jan 2014 | B2 |
| 8627483 | Rachlin et al. | Jan 2014 | B2 |
| 8627993 | Smith et al. | Jan 2014 | B2 |
| 8627995 | Smith et al. | Jan 2014 | B2 |
| 8628518 | Blumenkranz et al. | Jan 2014 | B2 |
| 8628545 | Cabrera et al. | Jan 2014 | B2 |
| 8631987 | Shelton, IV et al. | Jan 2014 | B2 |
| 8632525 | Kerr et al. | Jan 2014 | B2 |
| 8636190 | Zemlok et al. | Jan 2014 | B2 |
| 8636736 | Yates et al. | Jan 2014 | B2 |
| 8641621 | Razzaque et al. | Feb 2014 | B2 |
| 8652086 | Gerg et al. | Feb 2014 | B2 |
| 8652121 | Quick et al. | Feb 2014 | B2 |
| 8652128 | Ward | Feb 2014 | B2 |
| 8657176 | Shelton, IV et al. | Feb 2014 | B2 |
| 8657177 | Scirica et al. | Feb 2014 | B2 |
| 8663220 | Wiener et al. | Mar 2014 | B2 |
| 8663222 | Anderson et al. | Mar 2014 | B2 |
| 8666544 | Moll et al. | Mar 2014 | B2 |
| 8679114 | Chapman et al. | Mar 2014 | B2 |
| 8682049 | Zhao et al. | Mar 2014 | B2 |
| 8682489 | Itkowitz et al. | Mar 2014 | B2 |
| 8685056 | Evans et al. | Apr 2014 | B2 |
| 8688188 | Heller et al. | Apr 2014 | B2 |
| 8690864 | Hoarau | Apr 2014 | B2 |
| 8701962 | Kostrzewski | Apr 2014 | B2 |
| 8708213 | Shelton, IV et al. | Apr 2014 | B2 |
| D704839 | Juzkiw et al. | May 2014 | S |
| 8719061 | Birchall | May 2014 | B2 |
| 8720766 | Hess et al. | May 2014 | B2 |
| 8733613 | Huitema et al. | May 2014 | B2 |
| 8740840 | Foley et al. | Jun 2014 | B2 |
| 8740866 | Reasoner et al. | Jun 2014 | B2 |
| 8747238 | Shelton, IV et al. | Jun 2014 | B2 |
| 8752749 | Moore et al. | Jun 2014 | B2 |
| 8757465 | Woodard, Jr. et al. | Jun 2014 | B2 |
| 8761717 | Buchheit | Jun 2014 | B1 |
| 8763879 | Shelton, IV et al. | Jul 2014 | B2 |
| 8768251 | Claus et al. | Jul 2014 | B2 |
| 8771270 | Burbank | Jul 2014 | B2 |
| 8775196 | Simpson et al. | Jul 2014 | B2 |
| 8779648 | Giordano et al. | Jul 2014 | B2 |
| 8790253 | Sunagawa et al. | Jul 2014 | B2 |
| 8794497 | Zingman | Aug 2014 | B2 |
| 8795001 | Lam et al. | Aug 2014 | B1 |
| 8799008 | Johnson et al. | Aug 2014 | B2 |
| 8799009 | Mellin et al. | Aug 2014 | B2 |
| 8800838 | Shelton, IV | Aug 2014 | B2 |
| 8801703 | Gregg et al. | Aug 2014 | B2 |
| 8814996 | Giurgiutiu et al. | Aug 2014 | B2 |
| 8818556 | Sanchez et al. | Aug 2014 | B2 |
| 8819581 | Nakamura et al. | Aug 2014 | B2 |
| 8820603 | Shelton, IV et al. | Sep 2014 | B2 |
| 8820607 | Marczyk | Sep 2014 | B2 |
| 8820608 | Miyamoto | Sep 2014 | B2 |
| 8827134 | Viola et al. | Sep 2014 | B2 |
| 8827136 | Hessler | Sep 2014 | B2 |
| 8840003 | Morgan et al. | Sep 2014 | B2 |
| D716333 | Chotin et al. | Oct 2014 | S |
| 8851354 | Swensgard et al. | Oct 2014 | B2 |
| 8852174 | Burbank | Oct 2014 | B2 |
| 8864747 | Merchant et al. | Oct 2014 | B2 |
| 8875973 | Whitman | Nov 2014 | B2 |
| 8876857 | Burbank | Nov 2014 | B2 |
| 8882662 | Charles | Nov 2014 | B2 |
| 8885032 | Igarashi et al. | Nov 2014 | B2 |
| 8886790 | Harrang et al. | Nov 2014 | B2 |
| 8893946 | Boudreaux et al. | Nov 2014 | B2 |
| 8893949 | Shelton, IV et al. | Nov 2014 | B2 |
| 8899479 | Cappuzzo et al. | Dec 2014 | B2 |
| 8905977 | Shelton et al. | Dec 2014 | B2 |
| 8912746 | Reid et al. | Dec 2014 | B2 |
| 8914098 | Brennan et al. | Dec 2014 | B2 |
| 8917513 | Hazzard | Dec 2014 | B1 |
| 8918207 | Prisco | Dec 2014 | B2 |
| 8920186 | Shishikura | Dec 2014 | B2 |
| 8920414 | Stone et al. | Dec 2014 | B2 |
| 8920433 | Barrier et al. | Dec 2014 | B2 |
| 8930203 | Kiaie et al. | Jan 2015 | B2 |
| 8930214 | Woolford | Jan 2015 | B2 |
| 8931679 | Kostrzewski | Jan 2015 | B2 |
| 8934684 | Mohamed | Jan 2015 | B2 |
| 8936614 | Allen, IV | Jan 2015 | B2 |
| 8945095 | Blumenkranz et al. | Feb 2015 | B2 |
| 8945163 | Voegele et al. | Feb 2015 | B2 |
| 8955732 | Zemlok et al. | Feb 2015 | B2 |
| 8956581 | Rosenbaum et al. | Feb 2015 | B2 |
| 8960519 | Whitman et al. | Feb 2015 | B2 |
| 8960520 | McCuen | Feb 2015 | B2 |
| 8962062 | Podhajsky et al. | Feb 2015 | B2 |
| 8967443 | McCuen | Mar 2015 | B2 |
| 8967455 | Zhou | Mar 2015 | B2 |
| 8968276 | Zemlok et al. | Mar 2015 | B2 |
| 8968296 | McPherson | Mar 2015 | B2 |
| 8968309 | Roy et al. | Mar 2015 | B2 |
| 8968312 | Marczyk et al. | Mar 2015 | B2 |
| 8968337 | Whitfield et al. | Mar 2015 | B2 |
| 8968358 | Reschke | Mar 2015 | B2 |
| 8974429 | Gordon et al. | Mar 2015 | B2 |
| 8979890 | Boudreaux | Mar 2015 | B2 |
| 8986288 | Konishi | Mar 2015 | B2 |
| 8986302 | Aldridge et al. | Mar 2015 | B2 |
| 8989903 | Weir et al. | Mar 2015 | B2 |
| 8991678 | Wellman et al. | Mar 2015 | B2 |
| 8992565 | Brisson et al. | Mar 2015 | B2 |
| 8998797 | Omori | Apr 2015 | B2 |
| 9002518 | Manzo et al. | Apr 2015 | B2 |
| 9005230 | Yates et al. | Apr 2015 | B2 |
| 9010608 | Casasanta, Jr. et al. | Apr 2015 | B2 |
| 9010611 | Ross et al. | Apr 2015 | B2 |
| 9011366 | Dean et al. | Apr 2015 | B2 |
| 9011427 | Price et al. | Apr 2015 | B2 |
| 9016539 | Kostrzewski et al. | Apr 2015 | B2 |
| 9017326 | DiNardo et al. | Apr 2015 | B2 |
| 9020240 | Pettersson et al. | Apr 2015 | B2 |
| D729267 | Yoo et al. | May 2015 | S |
| 9023032 | Robinson | May 2015 | B2 |
| 9023071 | Miller et al. | May 2015 | B2 |
| 9023079 | Boulnois et al. | May 2015 | B2 |
| 9027431 | Tang et al. | May 2015 | B2 |
| 9028494 | Shelton, IV et al. | May 2015 | B2 |
| 9033973 | Krapohl et al. | May 2015 | B2 |
| 9035568 | Ganton et al. | May 2015 | B2 |
| 9038882 | Racenet et al. | May 2015 | B2 |
| 9043027 | Durant et al. | May 2015 | B2 |
| 9044227 | Shelton, IV et al. | Jun 2015 | B2 |
| 9044244 | Ludwin et al. | Jun 2015 | B2 |
| 9044261 | Houser | Jun 2015 | B2 |
| 9050063 | Roe et al. | Jun 2015 | B2 |
| 9050083 | Yates et al. | Jun 2015 | B2 |
| 9050120 | Swarup et al. | Jun 2015 | B2 |
| 9052809 | Vesto | Jun 2015 | B2 |
| 9055035 | Porsch et al. | Jun 2015 | B2 |
| 9055870 | Meador et al. | Jun 2015 | B2 |
| 9060770 | Shelton, IV et al. | Jun 2015 | B2 |
| 9060775 | Wiener et al. | Jun 2015 | B2 |
| 9066650 | Sekiguchi | Jun 2015 | B2 |
| 9072523 | Houser et al. | Jul 2015 | B2 |
| 9072535 | Shelton, IV et al. | Jul 2015 | B2 |
| 9072536 | Shelton, IV et al. | Jul 2015 | B2 |
| 9078653 | Leimbach et al. | Jul 2015 | B2 |
| 9078727 | Miller | Jul 2015 | B2 |
| 9084606 | Greep | Jul 2015 | B2 |
| 9089360 | Messerly et al. | Jul 2015 | B2 |
| 9095362 | Dachs, II et al. | Aug 2015 | B2 |
| 9095367 | Olson et al. | Aug 2015 | B2 |
| 9099863 | Smith et al. | Aug 2015 | B2 |
| 9101358 | Kerr et al. | Aug 2015 | B2 |
| 9101359 | Smith et al. | Aug 2015 | B2 |
| 9101374 | Hoch et al. | Aug 2015 | B1 |
| 9106270 | Puterbaugh et al. | Aug 2015 | B2 |
| 9107573 | Birnkrant | Aug 2015 | B2 |
| 9107662 | Kostrzewski | Aug 2015 | B2 |
| 9107684 | Ma | Aug 2015 | B2 |
| 9107688 | Kimball et al. | Aug 2015 | B2 |
| 9107689 | Robertson et al. | Aug 2015 | B2 |
| 9107694 | Hendriks et al. | Aug 2015 | B2 |
| 9111548 | Nandy et al. | Aug 2015 | B2 |
| 9113880 | Zemlok et al. | Aug 2015 | B2 |
| 9114494 | Mah | Aug 2015 | B1 |
| 9116597 | Gulasky | Aug 2015 | B1 |
| 9119617 | Souls et al. | Sep 2015 | B2 |
| 9119655 | Bowling et al. | Sep 2015 | B2 |
| 9119657 | Shelton, IV et al. | Sep 2015 | B2 |
| 9123155 | Cunningham et al. | Sep 2015 | B2 |
| 9125644 | Lane et al. | Sep 2015 | B2 |
| 9129054 | Nawana et al. | Sep 2015 | B2 |
| 9131957 | Skarbnik et al. | Sep 2015 | B2 |
| 9137254 | Bilbrey et al. | Sep 2015 | B2 |
| 9138129 | Diolaiti | Sep 2015 | B2 |
| 9138225 | Huang et al. | Sep 2015 | B2 |
| 9141758 | Kress et al. | Sep 2015 | B2 |
| 9149322 | Knowlton | Oct 2015 | B2 |
| 9155503 | Cadwell | Oct 2015 | B2 |
| 9160853 | Daddi et al. | Oct 2015 | B1 |
| 9161803 | Yates et al. | Oct 2015 | B2 |
| 9168054 | Turner et al. | Oct 2015 | B2 |
| 9168091 | Janssen et al. | Oct 2015 | B2 |
| 9168104 | Dein | Oct 2015 | B2 |
| 9179912 | Yates et al. | Nov 2015 | B2 |
| 9183723 | Sherman et al. | Nov 2015 | B2 |
| 9186143 | Timm et al. | Nov 2015 | B2 |
| 9192375 | Skinlo et al. | Nov 2015 | B2 |
| 9192447 | Choi et al. | Nov 2015 | B2 |
| 9192707 | Gerber et al. | Nov 2015 | B2 |
| 9198711 | Joseph | Dec 2015 | B2 |
| 9198835 | Swisher et al. | Dec 2015 | B2 |
| 9202078 | Abuelsaad et al. | Dec 2015 | B2 |
| 9204830 | Zand et al. | Dec 2015 | B2 |
| 9204879 | Shelton, IV | Dec 2015 | B2 |
| 9204995 | Scheller et al. | Dec 2015 | B2 |
| 9211120 | Scheib et al. | Dec 2015 | B2 |
| 9216062 | Duque et al. | Dec 2015 | B2 |
| 9218053 | Komuro et al. | Dec 2015 | B2 |
| 9220502 | Zemlok et al. | Dec 2015 | B2 |
| 9220505 | Vasudevan et al. | Dec 2015 | B2 |
| 9226689 | Jacobsen et al. | Jan 2016 | B2 |
| 9226751 | Shelton, IV et al. | Jan 2016 | B2 |
| 9226766 | Aldridge et al. | Jan 2016 | B2 |
| 9226767 | Stulen et al. | Jan 2016 | B2 |
| 9226791 | McCarthy et al. | Jan 2016 | B2 |
| 9232883 | Ozawa et al. | Jan 2016 | B2 |
| 9237891 | Shelton, IV | Jan 2016 | B2 |
| 9237921 | Messerly et al. | Jan 2016 | B2 |
| 9241728 | Price et al. | Jan 2016 | B2 |
| 9241730 | Babaev | Jan 2016 | B2 |
| 9241731 | Boudreaux et al. | Jan 2016 | B2 |
| 9247996 | Merana et al. | Feb 2016 | B1 |
| 9250172 | Harris et al. | Feb 2016 | B2 |
| 9255907 | Heanue et al. | Feb 2016 | B2 |
| 9259282 | Azizian et al. | Feb 2016 | B2 |
| 9265429 | St. Pierre et al. | Feb 2016 | B2 |
| 9265585 | Wingardner et al. | Feb 2016 | B2 |
| 9265959 | Drew et al. | Feb 2016 | B2 |
| 9272406 | Aronhalt et al. | Mar 2016 | B2 |
| 9277956 | Zhang | Mar 2016 | B2 |
| 9277961 | Panescu et al. | Mar 2016 | B2 |
| 9277969 | Brannan et al. | Mar 2016 | B2 |
| 9280884 | Schultz et al. | Mar 2016 | B1 |
| 9282962 | Schmid et al. | Mar 2016 | B2 |
| 9282974 | Shelton, IV | Mar 2016 | B2 |
| 9283045 | Rhee et al. | Mar 2016 | B2 |
| 9283054 | Morgan et al. | Mar 2016 | B2 |
| 9289211 | Williams et al. | Mar 2016 | B2 |
| 9289212 | Shelton, IV et al. | Mar 2016 | B2 |
| 9295514 | Shelton, IV et al. | Mar 2016 | B2 |
| 9299138 | Zellner et al. | Mar 2016 | B2 |
| 9301691 | Hufnagel et al. | Apr 2016 | B2 |
| 9301753 | Aldridge et al. | Apr 2016 | B2 |
| 9301755 | Shelton, IV et al. | Apr 2016 | B2 |
| 9301759 | Spivey et al. | Apr 2016 | B2 |
| 9301810 | Amiri et al. | Apr 2016 | B2 |
| 9302213 | Manahan et al. | Apr 2016 | B2 |
| 9307894 | von Grunberg et al. | Apr 2016 | B2 |
| 9307914 | Fahey | Apr 2016 | B2 |
| 9307986 | Hall et al. | Apr 2016 | B2 |
| 9314246 | Shelton, IV et al. | Apr 2016 | B2 |
| 9314308 | Parihar et al. | Apr 2016 | B2 |
| 9320563 | Brustad et al. | Apr 2016 | B2 |
| 9325732 | Stickle et al. | Apr 2016 | B1 |
| 9326767 | Koch, Jr. et al. | May 2016 | B2 |
| 9326770 | Shelton, IV et al. | May 2016 | B2 |
| 9331422 | Nazzaro et al. | May 2016 | B2 |
| 9332987 | Leimbach et al. | May 2016 | B2 |
| 9333042 | Diolaiti et al. | May 2016 | B2 |
| 9336385 | Spencer et al. | May 2016 | B1 |
| 9341704 | Picard et al. | May 2016 | B2 |
| 9345481 | Hall et al. | May 2016 | B2 |
| 9345490 | Ippisch | May 2016 | B2 |
| 9345544 | Hourtash et al. | May 2016 | B2 |
| 9345546 | Toth et al. | May 2016 | B2 |
| 9345900 | Wu et al. | May 2016 | B2 |
| 9351726 | Leimbach et al. | May 2016 | B2 |
| 9351727 | Leimbach et al. | May 2016 | B2 |
| 9358003 | Hall et al. | Jun 2016 | B2 |
| 9358685 | Meier et al. | Jun 2016 | B2 |
| 9360449 | Duric | Jun 2016 | B2 |
| 9364200 | Whitman et al. | Jun 2016 | B2 |
| 9364230 | Shelton, IV et al. | Jun 2016 | B2 |
| 9364231 | Wenchell | Jun 2016 | B2 |
| 9364249 | Kimball et al. | Jun 2016 | B2 |
| 9364294 | Razzaque et al. | Jun 2016 | B2 |
| 9370400 | Parihar | Jun 2016 | B2 |
| 9375282 | Nau, Jr. et al. | Jun 2016 | B2 |
| 9375539 | Stearns et al. | Jun 2016 | B2 |
| 9381003 | Todor et al. | Jul 2016 | B2 |
| 9381058 | Houser et al. | Jul 2016 | B2 |
| 9386984 | Aronhalt et al. | Jul 2016 | B2 |
| 9386988 | Baxter, III et al. | Jul 2016 | B2 |
| 9387295 | Mastri et al. | Jul 2016 | B1 |
| 9393017 | Flanagan et al. | Jul 2016 | B2 |
| 9393037 | Olson et al. | Jul 2016 | B2 |
| 9398905 | Martin | Jul 2016 | B2 |
| 9398911 | Auld | Jul 2016 | B2 |
| 9402629 | Ehrenfels et al. | Aug 2016 | B2 |
| 9404868 | Yamanaka et al. | Aug 2016 | B2 |
| 9414776 | Sillay et al. | Aug 2016 | B2 |
| 9414940 | Stein et al. | Aug 2016 | B2 |
| 9419018 | Sasagawa et al. | Aug 2016 | B2 |
| 9421014 | Ingmanson et al. | Aug 2016 | B2 |
| 9433470 | Choi | Sep 2016 | B2 |
| 9439622 | Case et al. | Sep 2016 | B2 |
| 9439668 | Timm et al. | Sep 2016 | B2 |
| 9439736 | Olson | Sep 2016 | B2 |
| 9445764 | Gross et al. | Sep 2016 | B2 |
| 9445813 | Shelton, IV et al. | Sep 2016 | B2 |
| 9450701 | Do et al. | Sep 2016 | B2 |
| 9451949 | Gorek et al. | Sep 2016 | B2 |
| 9451958 | Shelton, IV et al. | Sep 2016 | B2 |
| 9463022 | Swayze et al. | Oct 2016 | B2 |
| 9463646 | Payne et al. | Oct 2016 | B2 |
| 9468438 | Baber et al. | Oct 2016 | B2 |
| 9474565 | Shikhman et al. | Oct 2016 | B2 |
| D772252 | Myers et al. | Nov 2016 | S |
| 9480492 | Aranyi et al. | Nov 2016 | B2 |
| 9485475 | Speier et al. | Nov 2016 | B2 |
| 9486271 | Dunning | Nov 2016 | B2 |
| 9492146 | Kostrzewski et al. | Nov 2016 | B2 |
| 9492237 | Kang et al. | Nov 2016 | B2 |
| 9493807 | Little et al. | Nov 2016 | B2 |
| 9498182 | Case et al. | Nov 2016 | B2 |
| 9498215 | Duque et al. | Nov 2016 | B2 |
| 9498219 | Moore et al. | Nov 2016 | B2 |
| 9498231 | Haider et al. | Nov 2016 | B2 |
| 9498279 | Artale et al. | Nov 2016 | B2 |
| 9498291 | Balaji et al. | Nov 2016 | B2 |
| 9509566 | Chu et al. | Nov 2016 | B2 |
| 9516239 | Blanquart et al. | Dec 2016 | B2 |
| 9519753 | Gerdeman et al. | Dec 2016 | B1 |
| 9522003 | Weir et al. | Dec 2016 | B2 |
| 9526407 | Hoeg et al. | Dec 2016 | B2 |
| 9526499 | Kostrzewski et al. | Dec 2016 | B2 |
| 9526580 | Humayun et al. | Dec 2016 | B2 |
| 9526587 | Zhao et al. | Dec 2016 | B2 |
| 9532827 | Morgan et al. | Jan 2017 | B2 |
| 9532845 | Dossett et al. | Jan 2017 | B1 |
| 9539007 | Dhakad et al. | Jan 2017 | B2 |
| 9539020 | Conlon et al. | Jan 2017 | B2 |
| 9542481 | Halter et al. | Jan 2017 | B2 |
| 9545216 | D'Angelo et al. | Jan 2017 | B2 |
| 9546662 | Shener-Irmakoglu et al. | Jan 2017 | B2 |
| 9549781 | He et al. | Jan 2017 | B2 |
| 9554692 | Levy | Jan 2017 | B2 |
| 9554794 | Baber et al. | Jan 2017 | B2 |
| 9554854 | Yates et al. | Jan 2017 | B2 |
| 9561038 | Shelton, IV et al. | Feb 2017 | B2 |
| 9561045 | Hinman et al. | Feb 2017 | B2 |
| 9561082 | Yen et al. | Feb 2017 | B2 |
| 9561982 | Enicks et al. | Feb 2017 | B2 |
| 9566708 | Kurnianto | Feb 2017 | B2 |
| 9572592 | Price et al. | Feb 2017 | B2 |
| 9579099 | Penna et al. | Feb 2017 | B2 |
| 9579503 | McKinney et al. | Feb 2017 | B2 |
| 9585657 | Shelton, IV et al. | Mar 2017 | B2 |
| 9585658 | Shelton, IV | Mar 2017 | B2 |
| 9592095 | Panescu et al. | Mar 2017 | B2 |
| 9597081 | Swayze et al. | Mar 2017 | B2 |
| 9600031 | Kaneko et al. | Mar 2017 | B2 |
| 9600138 | Thomas et al. | Mar 2017 | B2 |
| 9603024 | Wang et al. | Mar 2017 | B2 |
| 9603277 | Morgan et al. | Mar 2017 | B2 |
| 9603609 | Kawashima et al. | Mar 2017 | B2 |
| D783675 | Yagisawa et al. | Apr 2017 | S |
| D784270 | Bhattacharya | Apr 2017 | S |
| 9610114 | Baxter, III et al. | Apr 2017 | B2 |
| 9610412 | Zemlok et al. | Apr 2017 | B2 |
| 9615877 | Tyrrell et al. | Apr 2017 | B2 |
| 9622684 | Wybo | Apr 2017 | B2 |
| 9622808 | Beller et al. | Apr 2017 | B2 |
| 9628501 | Datta Ray et al. | Apr 2017 | B2 |
| 9629560 | Joseph | Apr 2017 | B2 |
| 9629623 | Lytle, IV et al. | Apr 2017 | B2 |
| 9629628 | Aranyi | Apr 2017 | B2 |
| 9629629 | Leimbach et al. | Apr 2017 | B2 |
| 9630318 | Ibarz Gabardos et al. | Apr 2017 | B2 |
| 9636096 | Heaton, II et al. | May 2017 | B1 |
| 9636112 | Penna et al. | May 2017 | B2 |
| 9636188 | Gattani et al. | May 2017 | B2 |
| 9636239 | Durand et al. | May 2017 | B2 |
| 9636825 | Penn et al. | May 2017 | B2 |
| 9641596 | Unagami et al. | May 2017 | B2 |
| 9641815 | Richardson et al. | May 2017 | B2 |
| 9642620 | Baxter, III et al. | May 2017 | B2 |
| 9643022 | Mashiach et al. | May 2017 | B2 |
| 9649089 | Smith et al. | May 2017 | B2 |
| 9649110 | Parihar et al. | May 2017 | B2 |
| 9649111 | Shelton, IV et al. | May 2017 | B2 |
| 9649126 | Robertson et al. | May 2017 | B2 |
| 9649169 | Cinquin et al. | May 2017 | B2 |
| 9652655 | Satish et al. | May 2017 | B2 |
| 9655614 | Swensgard et al. | May 2017 | B2 |
| 9655616 | Aranyi | May 2017 | B2 |
| 9656092 | Golden | May 2017 | B2 |
| 9662104 | Nobles et al. | May 2017 | B1 |
| 9662116 | Smith et al. | May 2017 | B2 |
| 9662177 | Weir et al. | May 2017 | B2 |
| 9668729 | Williams et al. | Jun 2017 | B2 |
| 9668732 | Patel et al. | Jun 2017 | B2 |
| 9668765 | Grace et al. | Jun 2017 | B2 |
| 9671860 | Ogawa et al. | Jun 2017 | B2 |
| 9675264 | Acquista et al. | Jun 2017 | B2 |
| 9675354 | Weir et al. | Jun 2017 | B2 |
| 9681870 | Baxter, III et al. | Jun 2017 | B2 |
| 9686306 | Chizeck et al. | Jun 2017 | B2 |
| 9687230 | Leimbach et al. | Jun 2017 | B2 |
| 9690362 | Leimbach et al. | Jun 2017 | B2 |
| 9700292 | Nawana et al. | Jul 2017 | B2 |
| 9700309 | Jaworek et al. | Jul 2017 | B2 |
| 9700312 | Kostrzewski et al. | Jul 2017 | B2 |
| 9700320 | Dinardo et al. | Jul 2017 | B2 |
| 9706993 | Hessler et al. | Jul 2017 | B2 |
| 9710214 | Lin et al. | Jul 2017 | B2 |
| 9710644 | Reybok et al. | Jul 2017 | B2 |
| 9713424 | Spaide | Jul 2017 | B2 |
| 9713503 | Goldschmidt | Jul 2017 | B2 |
| 9717141 | Tegg | Jul 2017 | B1 |
| 9717498 | Aranyi et al. | Aug 2017 | B2 |
| 9717525 | Ahluwalia et al. | Aug 2017 | B2 |
| 9717548 | Couture | Aug 2017 | B2 |
| 9724094 | Baber et al. | Aug 2017 | B2 |
| 9724100 | Scheib et al. | Aug 2017 | B2 |
| 9724118 | Schulte et al. | Aug 2017 | B2 |
| 9733663 | Leimbach et al. | Aug 2017 | B2 |
| 9737301 | Baber et al. | Aug 2017 | B2 |
| 9737310 | Whitfield et al. | Aug 2017 | B2 |
| 9737335 | Butler et al. | Aug 2017 | B2 |
| 9737355 | Yates et al. | Aug 2017 | B2 |
| 9737371 | Romo et al. | Aug 2017 | B2 |
| 9740826 | Raghavan et al. | Aug 2017 | B2 |
| 9743016 | Nestares et al. | Aug 2017 | B2 |
| 9743929 | Leimbach et al. | Aug 2017 | B2 |
| 9743946 | Faller et al. | Aug 2017 | B2 |
| 9743947 | Price et al. | Aug 2017 | B2 |
| 9750499 | Leimbach et al. | Sep 2017 | B2 |
| 9750500 | Malkowski | Sep 2017 | B2 |
| 9750522 | Scheib et al. | Sep 2017 | B2 |
| 9750523 | Tsubuku | Sep 2017 | B2 |
| 9750560 | Ballakur et al. | Sep 2017 | B2 |
| 9750563 | Shikhman et al. | Sep 2017 | B2 |
| 9753135 | Bosch | Sep 2017 | B2 |
| 9753568 | McMillen | Sep 2017 | B2 |
| 9757126 | Cappola | Sep 2017 | B2 |
| 9757128 | Baber et al. | Sep 2017 | B2 |
| 9757142 | Shimizu | Sep 2017 | B2 |
| 9757152 | Ogilvie et al. | Sep 2017 | B2 |
| 9763741 | Alvarez et al. | Sep 2017 | B2 |
| 9764164 | Wiener et al. | Sep 2017 | B2 |
| 9770541 | Carr et al. | Sep 2017 | B2 |
| 9775611 | Kostrzewski | Oct 2017 | B2 |
| 9775623 | Zammataro et al. | Oct 2017 | B2 |
| 9777913 | Talbert et al. | Oct 2017 | B2 |
| 9782164 | Mumaw et al. | Oct 2017 | B2 |
| 9782169 | Kimsey et al. | Oct 2017 | B2 |
| 9782212 | Wham et al. | Oct 2017 | B2 |
| 9782214 | Houser et al. | Oct 2017 | B2 |
| 9788835 | Morgan et al. | Oct 2017 | B2 |
| 9788836 | Overmyer et al. | Oct 2017 | B2 |
| 9788851 | Dannaher et al. | Oct 2017 | B2 |
| 9788902 | Inoue et al. | Oct 2017 | B2 |
| 9788907 | Alvi et al. | Oct 2017 | B1 |
| 9795436 | Yates et al. | Oct 2017 | B2 |
| 9797486 | Zergiebel et al. | Oct 2017 | B2 |
| 9801531 | Morita et al. | Oct 2017 | B2 |
| 9801626 | Parihar et al. | Oct 2017 | B2 |
| 9801627 | Harris et al. | Oct 2017 | B2 |
| 9801679 | Trees et al. | Oct 2017 | B2 |
| 9802033 | Hibner et al. | Oct 2017 | B2 |
| 9804618 | Leimbach et al. | Oct 2017 | B2 |
| 9805472 | Chou et al. | Oct 2017 | B2 |
| 9808244 | Leimbach et al. | Nov 2017 | B2 |
| 9808245 | Richard et al. | Nov 2017 | B2 |
| 9808246 | Shelton, IV et al. | Nov 2017 | B2 |
| 9808248 | Hoffman | Nov 2017 | B2 |
| 9808249 | Shelton, IV | Nov 2017 | B2 |
| 9808305 | Hareyama et al. | Nov 2017 | B2 |
| 9814457 | Martin et al. | Nov 2017 | B2 |
| 9814460 | Kimsey et al. | Nov 2017 | B2 |
| 9814462 | Woodard, Jr. et al. | Nov 2017 | B2 |
| 9814463 | Williams et al. | Nov 2017 | B2 |
| 9820699 | Bingley et al. | Nov 2017 | B2 |
| 9820738 | Lytle, IV et al. | Nov 2017 | B2 |
| 9820741 | Kostrzewski | Nov 2017 | B2 |
| 9820768 | Gee et al. | Nov 2017 | B2 |
| 9826976 | Parihar et al. | Nov 2017 | B2 |
| 9826977 | Leimbach et al. | Nov 2017 | B2 |
| 9827054 | Richmond et al. | Nov 2017 | B2 |
| 9827059 | Robinson et al. | Nov 2017 | B2 |
| 9830424 | Dixon et al. | Nov 2017 | B2 |
| 9833241 | Huitema et al. | Dec 2017 | B2 |
| 9833254 | Barral et al. | Dec 2017 | B1 |
| 9839419 | Deck et al. | Dec 2017 | B2 |
| 9839424 | Zergiebel et al. | Dec 2017 | B2 |
| 9839428 | Baxter, III et al. | Dec 2017 | B2 |
| 9839467 | Harper et al. | Dec 2017 | B2 |
| 9839470 | Gilbert et al. | Dec 2017 | B2 |
| 9839487 | Dachs, II | Dec 2017 | B2 |
| 9844321 | Ekvall et al. | Dec 2017 | B1 |
| 9844368 | Boudreaux et al. | Dec 2017 | B2 |
| 9844369 | Huitema et al. | Dec 2017 | B2 |
| 9844374 | Lytle, IV et al. | Dec 2017 | B2 |
| 9844375 | Overmyer et al. | Dec 2017 | B2 |
| 9844376 | Baxter, III et al. | Dec 2017 | B2 |
| 9844379 | Shelton, IV et al. | Dec 2017 | B2 |
| 9848058 | Johnson et al. | Dec 2017 | B2 |
| 9848877 | Shelton, IV et al. | Dec 2017 | B2 |
| 9861354 | Saliman et al. | Jan 2018 | B2 |
| 9861363 | Chen et al. | Jan 2018 | B2 |
| 9861428 | Trees et al. | Jan 2018 | B2 |
| 9864839 | Baym et al. | Jan 2018 | B2 |
| 9867612 | Parihar et al. | Jan 2018 | B2 |
| 9867651 | Wham | Jan 2018 | B2 |
| 9867670 | Brannan et al. | Jan 2018 | B2 |
| 9867914 | Bonano et al. | Jan 2018 | B2 |
| 9872609 | Levy | Jan 2018 | B2 |
| 9872683 | Hopkins et al. | Jan 2018 | B2 |
| 9877718 | Weir et al. | Jan 2018 | B2 |
| 9877721 | Schellin et al. | Jan 2018 | B2 |
| 9883860 | Leimbach et al. | Feb 2018 | B2 |
| 9888864 | Rondoni et al. | Feb 2018 | B2 |
| 9888914 | Martin et al. | Feb 2018 | B2 |
| 9888919 | Leimbach et al. | Feb 2018 | B2 |
| 9888921 | Williams et al. | Feb 2018 | B2 |
| 9888975 | Auld | Feb 2018 | B2 |
| 9895148 | Shelton, IV et al. | Feb 2018 | B2 |
| 9900787 | Ou | Feb 2018 | B2 |
| 9901342 | Shelton, IV et al. | Feb 2018 | B2 |
| 9901406 | State et al. | Feb 2018 | B2 |
| 9901411 | Gombert et al. | Feb 2018 | B2 |
| 9905000 | Chou et al. | Feb 2018 | B2 |
| 9907196 | Susini et al. | Feb 2018 | B2 |
| 9907550 | Sniffin et al. | Mar 2018 | B2 |
| 9913642 | Leimbach et al. | Mar 2018 | B2 |
| 9913645 | Zerkle et al. | Mar 2018 | B2 |
| 9918326 | Gilson et al. | Mar 2018 | B2 |
| 9918730 | Trees et al. | Mar 2018 | B2 |
| 9918778 | Walberg et al. | Mar 2018 | B2 |
| 9918788 | Paul et al. | Mar 2018 | B2 |
| 9922304 | DeBusk et al. | Mar 2018 | B2 |
| 9924941 | Burbank | Mar 2018 | B2 |
| 9924944 | Shelton, IV et al. | Mar 2018 | B2 |
| 9924961 | Shelton, IV et al. | Mar 2018 | B2 |
| 9931040 | Homyk et al. | Apr 2018 | B2 |
| 9931118 | Shelton, IV et al. | Apr 2018 | B2 |
| 9931124 | Gokharu | Apr 2018 | B2 |
| 9936863 | Tesar | Apr 2018 | B2 |
| 9936942 | Chin et al. | Apr 2018 | B2 |
| 9936955 | Miller et al. | Apr 2018 | B2 |
| 9936961 | Chien et al. | Apr 2018 | B2 |
| 9937012 | Hares et al. | Apr 2018 | B2 |
| 9937014 | Bowling et al. | Apr 2018 | B2 |
| 9937626 | Rockrohr | Apr 2018 | B2 |
| 9938972 | Walley | Apr 2018 | B2 |
| 9943230 | Kaku et al. | Apr 2018 | B2 |
| 9943309 | Shelton, IV et al. | Apr 2018 | B2 |
| 9943312 | Posada et al. | Apr 2018 | B2 |
| 9943377 | Yates et al. | Apr 2018 | B2 |
| 9943379 | Gregg, II et al. | Apr 2018 | B2 |
| 9943918 | Grogan et al. | Apr 2018 | B2 |
| 9943964 | Hares | Apr 2018 | B2 |
| 9949785 | Price et al. | Apr 2018 | B2 |
| 9962157 | Sapre | May 2018 | B2 |
| 9968355 | Shelton, IV et al. | May 2018 | B2 |
| 9974595 | Anderson et al. | May 2018 | B2 |
| 9976259 | Tan et al. | May 2018 | B2 |
| 9980140 | Spencer et al. | May 2018 | B1 |
| 9980769 | Trees et al. | May 2018 | B2 |
| 9980778 | Ohline et al. | May 2018 | B2 |
| 9987000 | Shelton, IV et al. | Jun 2018 | B2 |
| 9987068 | Anderson et al. | Jun 2018 | B2 |
| 9987072 | McPherson | Jun 2018 | B2 |
| 9990856 | Kuchenbecker et al. | Jun 2018 | B2 |
| 9993248 | Shelton, IV et al. | Jun 2018 | B2 |
| 9993258 | Shelton, IV et al. | Jun 2018 | B2 |
| 9993305 | Andersson | Jun 2018 | B2 |
| 10004491 | Martin et al. | Jun 2018 | B2 |
| 10004497 | Overmyer et al. | Jun 2018 | B2 |
| 10004500 | Shelton, IV et al. | Jun 2018 | B2 |
| 10004501 | Shelton, IV et al. | Jun 2018 | B2 |
| 10004527 | Gee et al. | Jun 2018 | B2 |
| 10004557 | Gross | Jun 2018 | B2 |
| D822206 | Shelton, IV et al. | Jul 2018 | S |
| 10010322 | Shelton, IV et al. | Jul 2018 | B2 |
| 10010324 | Huitema et al. | Jul 2018 | B2 |
| 10013049 | Leimbach et al. | Jul 2018 | B2 |
| 10016199 | Baber et al. | Jul 2018 | B2 |
| 10016538 | Locke et al. | Jul 2018 | B2 |
| 10021318 | Hugosson et al. | Jul 2018 | B2 |
| 10022090 | Whitman | Jul 2018 | B2 |
| 10022120 | Martin et al. | Jul 2018 | B2 |
| 10022391 | Ruderman Chen et al. | Jul 2018 | B2 |
| 10022568 | Messerly et al. | Jul 2018 | B2 |
| 10028402 | Walker | Jul 2018 | B1 |
| 10028744 | Shelton, IV et al. | Jul 2018 | B2 |
| 10028761 | Leimbach et al. | Jul 2018 | B2 |
| 10028788 | Kang | Jul 2018 | B2 |
| 10034704 | Asher et al. | Jul 2018 | B2 |
| 10037641 | Hyde et al. | Jul 2018 | B2 |
| 10037715 | Toly et al. | Jul 2018 | B2 |
| D826405 | Shelton, IV et al. | Aug 2018 | S |
| 10039546 | Williams et al. | Aug 2018 | B2 |
| 10039564 | Hibner et al. | Aug 2018 | B2 |
| 10039565 | Vezzu | Aug 2018 | B2 |
| 10039589 | Virshek et al. | Aug 2018 | B2 |
| 10041822 | Zemlok | Aug 2018 | B2 |
| 10044791 | Kamen et al. | Aug 2018 | B2 |
| 10045704 | Fagin et al. | Aug 2018 | B2 |
| 10045776 | Shelton, IV et al. | Aug 2018 | B2 |
| 10045779 | Savage et al. | Aug 2018 | B2 |
| 10045781 | Cropper et al. | Aug 2018 | B2 |
| 10045782 | Murthy Aravalli | Aug 2018 | B2 |
| 10045813 | Mueller | Aug 2018 | B2 |
| 10048379 | Markendorf et al. | Aug 2018 | B2 |
| 10052044 | Shelton, IV et al. | Aug 2018 | B2 |
| 10052102 | Baxter, III et al. | Aug 2018 | B2 |
| 10052104 | Shelton, IV et al. | Aug 2018 | B2 |
| 10052147 | Merschon et al. | Aug 2018 | B2 |
| 10054441 | Schorr et al. | Aug 2018 | B2 |
| 10058393 | Bonutti et al. | Aug 2018 | B2 |
| 10069633 | Gulati et al. | Sep 2018 | B2 |
| 10076326 | Yates et al. | Sep 2018 | B2 |
| 10080618 | Marshall et al. | Sep 2018 | B2 |
| 10084833 | McDonnell et al. | Sep 2018 | B2 |
| D831209 | Huitema et al. | Oct 2018 | S |
| 10085748 | Morgan et al. | Oct 2018 | B2 |
| 10085749 | Cappola et al. | Oct 2018 | B2 |
| 10092355 | Hannaford et al. | Oct 2018 | B1 |
| 10095942 | Mentese et al. | Oct 2018 | B2 |
| 10097578 | Baldonado et al. | Oct 2018 | B2 |
| 10098527 | Weisenburgh, II et al. | Oct 2018 | B2 |
| 10098635 | Burbank | Oct 2018 | B2 |
| 10098642 | Baxter, III et al. | Oct 2018 | B2 |
| 10098705 | Brisson et al. | Oct 2018 | B2 |
| 10102926 | Leonardi | Oct 2018 | B1 |
| 10105140 | Malinouskas et al. | Oct 2018 | B2 |
| 10105142 | Baxter, III et al. | Oct 2018 | B2 |
| 10105470 | Reasoner et al. | Oct 2018 | B2 |
| 10111658 | Chowaniec et al. | Oct 2018 | B2 |
| 10111665 | Aranyi et al. | Oct 2018 | B2 |
| 10111679 | Baber et al. | Oct 2018 | B2 |
| 10111703 | Cosman, Jr. et al. | Oct 2018 | B2 |
| D834541 | You et al. | Nov 2018 | S |
| 10117649 | Baxter, III et al. | Nov 2018 | B2 |
| 10117651 | Whitman et al. | Nov 2018 | B2 |
| 10117702 | Danziger et al. | Nov 2018 | B2 |
| 10118119 | Sappok et al. | Nov 2018 | B2 |
| 10130359 | Hess et al. | Nov 2018 | B2 |
| 10130360 | Olson et al. | Nov 2018 | B2 |
| 10130361 | Yates et al. | Nov 2018 | B2 |
| 10130367 | Cappola et al. | Nov 2018 | B2 |
| 10130373 | Castro et al. | Nov 2018 | B2 |
| 10130432 | Auld et al. | Nov 2018 | B2 |
| 10133248 | Fitzsimmons et al. | Nov 2018 | B2 |
| 10135242 | Baber et al. | Nov 2018 | B2 |
| 10136246 | Yamada | Nov 2018 | B2 |
| 10136887 | Shelton, IV et al. | Nov 2018 | B2 |
| 10136891 | Shelton, IV et al. | Nov 2018 | B2 |
| 10136949 | Felder et al. | Nov 2018 | B2 |
| 10136954 | Johnson et al. | Nov 2018 | B2 |
| 10137245 | Melker et al. | Nov 2018 | B2 |
| 10143526 | Walker et al. | Dec 2018 | B2 |
| 10143948 | Bonifas et al. | Dec 2018 | B2 |
| 10147148 | Wu et al. | Dec 2018 | B2 |
| 10149680 | Parihar et al. | Dec 2018 | B2 |
| 10152789 | Carnes et al. | Dec 2018 | B2 |
| 10154841 | Weaner et al. | Dec 2018 | B2 |
| 10159044 | Hrabak | Dec 2018 | B2 |
| 10159481 | Whitman et al. | Dec 2018 | B2 |
| 10159483 | Beckman et al. | Dec 2018 | B2 |
| 10164466 | Calderoni | Dec 2018 | B2 |
| 10166025 | Leimbach et al. | Jan 2019 | B2 |
| 10166061 | Berry et al. | Jan 2019 | B2 |
| 10169862 | Andre et al. | Jan 2019 | B2 |
| 10172618 | Shelton, IV et al. | Jan 2019 | B2 |
| 10172687 | Garbus et al. | Jan 2019 | B2 |
| 10175096 | Dickerson | Jan 2019 | B2 |
| 10175127 | Collins et al. | Jan 2019 | B2 |
| 10178992 | Wise et al. | Jan 2019 | B2 |
| 10179413 | Rockrohr | Jan 2019 | B2 |
| 10180463 | Beckman et al. | Jan 2019 | B2 |
| 10182814 | Okoniewski | Jan 2019 | B2 |
| 10182816 | Shelton, IV et al. | Jan 2019 | B2 |
| 10182818 | Hensel et al. | Jan 2019 | B2 |
| 10187742 | Dor et al. | Jan 2019 | B2 |
| 10188385 | Kerr et al. | Jan 2019 | B2 |
| 10189157 | Schlegel et al. | Jan 2019 | B2 |
| 10190888 | Hryb et al. | Jan 2019 | B2 |
| 10194891 | Jeong et al. | Feb 2019 | B2 |
| 10194907 | Marczyk et al. | Feb 2019 | B2 |
| 10194913 | Nalagatla et al. | Feb 2019 | B2 |
| 10194972 | Yates et al. | Feb 2019 | B2 |
| 10197803 | Badiali et al. | Feb 2019 | B2 |
| 10198965 | Hart | Feb 2019 | B2 |
| 10201311 | Chou et al. | Feb 2019 | B2 |
| 10201349 | Leimbach et al. | Feb 2019 | B2 |
| 10201364 | Leimbach et al. | Feb 2019 | B2 |
| 10201365 | Boudreaux et al. | Feb 2019 | B2 |
| 10205708 | Fletcher et al. | Feb 2019 | B1 |
| 10206605 | Shelton, IV et al. | Feb 2019 | B2 |
| 10206752 | Hares et al. | Feb 2019 | B2 |
| 10213201 | Shelton, IV et al. | Feb 2019 | B2 |
| 10213203 | Swayze et al. | Feb 2019 | B2 |
| 10213266 | Zemlok et al. | Feb 2019 | B2 |
| 10213268 | Dachs, II | Feb 2019 | B2 |
| 10219491 | Stiles, Jr. et al. | Mar 2019 | B2 |
| 10220522 | Rockrohr | Mar 2019 | B2 |
| 10222750 | Bang et al. | Mar 2019 | B2 |
| 10226249 | Jaworek et al. | Mar 2019 | B2 |
| 10226250 | Beckman et al. | Mar 2019 | B2 |
| 10226254 | Cabrera et al. | Mar 2019 | B2 |
| 10226302 | Lacal et al. | Mar 2019 | B2 |
| 10231634 | Zand et al. | Mar 2019 | B2 |
| 10231733 | Ehrenfels et al. | Mar 2019 | B2 |
| 10231775 | Shelton, IV et al. | Mar 2019 | B2 |
| 10238413 | Hibner et al. | Mar 2019 | B2 |
| 10245027 | Shelton, IV et al. | Apr 2019 | B2 |
| 10245028 | Shelton, IV et al. | Apr 2019 | B2 |
| 10245029 | Hunter et al. | Apr 2019 | B2 |
| 10245030 | Hunter et al. | Apr 2019 | B2 |
| 10245033 | Overmyer et al. | Apr 2019 | B2 |
| 10245037 | Conklin et al. | Apr 2019 | B2 |
| 10245038 | Hopkins et al. | Apr 2019 | B2 |
| 10245040 | Milliman | Apr 2019 | B2 |
| 10251661 | Collings et al. | Apr 2019 | B2 |
| 10251725 | Valentine et al. | Apr 2019 | B2 |
| 10255995 | Ingmanson | Apr 2019 | B2 |
| 10258331 | Shelton, IV et al. | Apr 2019 | B2 |
| 10258359 | Kapadia | Apr 2019 | B2 |
| 10258362 | Conlon | Apr 2019 | B2 |
| 10258363 | Worrell et al. | Apr 2019 | B2 |
| 10258415 | Harrah et al. | Apr 2019 | B2 |
| 10258418 | Shelton, IV et al. | Apr 2019 | B2 |
| 10258425 | Mustufa et al. | Apr 2019 | B2 |
| 10263171 | Wiener et al. | Apr 2019 | B2 |
| 10265004 | Yamaguchi et al. | Apr 2019 | B2 |
| 10265035 | Fehre et al. | Apr 2019 | B2 |
| 10265066 | Measamer et al. | Apr 2019 | B2 |
| 10265068 | Harris et al. | Apr 2019 | B2 |
| 10265072 | Shelton, IV et al. | Apr 2019 | B2 |
| 10265090 | Ingmanson et al. | Apr 2019 | B2 |
| 10265130 | Hess et al. | Apr 2019 | B2 |
| 10271840 | Sapre | Apr 2019 | B2 |
| 10271844 | Valentine et al. | Apr 2019 | B2 |
| 10271846 | Shelton, IV et al. | Apr 2019 | B2 |
| 10271850 | Williams | Apr 2019 | B2 |
| 10271851 | Shelton, IV et al. | Apr 2019 | B2 |
| D847989 | Shelton, IV et al. | May 2019 | S |
| 10278698 | Racenet | May 2019 | B2 |
| 10278778 | State et al. | May 2019 | B2 |
| 10282963 | Fahey | May 2019 | B2 |
| 10283220 | Azizian et al. | May 2019 | B2 |
| 10285694 | Viola et al. | May 2019 | B2 |
| 10285698 | Cappola et al. | May 2019 | B2 |
| 10285700 | Scheib | May 2019 | B2 |
| 10285705 | Shelton, IV et al. | May 2019 | B2 |
| 10292610 | Srivastava | May 2019 | B2 |
| 10292704 | Harris et al. | May 2019 | B2 |
| 10292707 | Shelton, IV et al. | May 2019 | B2 |
| 10292758 | Boudreaux et al. | May 2019 | B2 |
| 10292769 | Yu | May 2019 | B1 |
| 10292771 | Wood et al. | May 2019 | B2 |
| 10293129 | Fox et al. | May 2019 | B2 |
| 10299792 | Huitema et al. | May 2019 | B2 |
| 10299868 | Tsuboi et al. | May 2019 | B2 |
| 10299870 | Connolly et al. | May 2019 | B2 |
| 10305926 | Mihan et al. | May 2019 | B2 |
| D850617 | Shelton, IV et al. | Jun 2019 | S |
| 10307159 | Harris et al. | Jun 2019 | B2 |
| 10307170 | Parfett et al. | Jun 2019 | B2 |
| 10307199 | Farritor et al. | Jun 2019 | B2 |
| 10311036 | Hussam et al. | Jun 2019 | B1 |
| 10313137 | Aarnio et al. | Jun 2019 | B2 |
| 10314577 | Laurent et al. | Jun 2019 | B2 |
| 10314582 | Shelton, IV et al. | Jun 2019 | B2 |
| 10318928 | Kestone et al. | Jun 2019 | B1 |
| 10321907 | Shelton, IV et al. | Jun 2019 | B2 |
| 10321964 | Grover et al. | Jun 2019 | B2 |
| 10327764 | Harris et al. | Jun 2019 | B2 |
| 10327779 | Richard et al. | Jun 2019 | B2 |
| 10335042 | Schoenle et al. | Jul 2019 | B2 |
| 10335147 | Rector et al. | Jul 2019 | B2 |
| 10335149 | Baxter, III et al. | Jul 2019 | B2 |
| 10335180 | Johnson et al. | Jul 2019 | B2 |
| 10335227 | Heard | Jul 2019 | B2 |
| 10339496 | Matson et al. | Jul 2019 | B2 |
| 10342543 | Shelton, IV et al. | Jul 2019 | B2 |
| 10342602 | Strobl et al. | Jul 2019 | B2 |
| 10342623 | Huelman et al. | Jul 2019 | B2 |
| 10343102 | Reasoner et al. | Jul 2019 | B2 |
| 10349824 | Claude et al. | Jul 2019 | B2 |
| 10349939 | Shelton, IV et al. | Jul 2019 | B2 |
| 10349941 | Marczyk et al. | Jul 2019 | B2 |
| 10350016 | Burbank et al. | Jul 2019 | B2 |
| 10357184 | Crawford et al. | Jul 2019 | B2 |
| 10357246 | Shelton, IV et al. | Jul 2019 | B2 |
| 10357247 | Shelton, IV et al. | Jul 2019 | B2 |
| 10362179 | Harris | Jul 2019 | B2 |
| 10363032 | Scheib et al. | Jul 2019 | B2 |
| 10363037 | Aronhalt et al. | Jul 2019 | B2 |
| 10368861 | Baxter, III et al. | Aug 2019 | B2 |
| 10368865 | Harris et al. | Aug 2019 | B2 |
| 10368867 | Harris et al. | Aug 2019 | B2 |
| 10368876 | Bhatnagar et al. | Aug 2019 | B2 |
| 10368894 | Madan et al. | Aug 2019 | B2 |
| 10368903 | Morales et al. | Aug 2019 | B2 |
| 10376263 | Morgan et al. | Aug 2019 | B2 |
| 10376305 | Yates et al. | Aug 2019 | B2 |
| 10376337 | Kilroy et al. | Aug 2019 | B2 |
| 10376338 | Taylor et al. | Aug 2019 | B2 |
| 10378893 | Mankovskii | Aug 2019 | B2 |
| 10383518 | Abu-Tarif et al. | Aug 2019 | B2 |
| 10383699 | Kilroy et al. | Aug 2019 | B2 |
| 10384021 | Koeth et al. | Aug 2019 | B2 |
| 10386990 | Shikhman et al. | Aug 2019 | B2 |
| 10390718 | Chen et al. | Aug 2019 | B2 |
| 10390794 | Kuroiwa et al. | Aug 2019 | B2 |
| 10390825 | Shelton, IV et al. | Aug 2019 | B2 |
| 10390831 | Holsten et al. | Aug 2019 | B2 |
| 10390895 | Henderson et al. | Aug 2019 | B2 |
| 10398348 | Osadchy et al. | Sep 2019 | B2 |
| 10398434 | Shelton, IV et al. | Sep 2019 | B2 |
| 10398517 | Eckert et al. | Sep 2019 | B2 |
| 10398521 | Itkowitz et al. | Sep 2019 | B2 |
| 10404521 | McChord et al. | Sep 2019 | B2 |
| 10404801 | Martch | Sep 2019 | B2 |
| 10405857 | Shelton, IV et al. | Sep 2019 | B2 |
| 10405859 | Harris et al. | Sep 2019 | B2 |
| 10405863 | Wise et al. | Sep 2019 | B2 |
| 10413291 | Worthington et al. | Sep 2019 | B2 |
| 10413293 | Shelton, IV et al. | Sep 2019 | B2 |
| 10413297 | Harris et al. | Sep 2019 | B2 |
| 10417446 | Takeyama | Sep 2019 | B2 |
| 10420552 | Shelton, IV et al. | Sep 2019 | B2 |
| 10420558 | Nalagatla et al. | Sep 2019 | B2 |
| 10420559 | Marczyk et al. | Sep 2019 | B2 |
| 10420620 | Rockrohr | Sep 2019 | B2 |
| 10420865 | Reasoner et al. | Sep 2019 | B2 |
| 10422727 | Pliskin | Sep 2019 | B2 |
| 10426466 | Contini et al. | Oct 2019 | B2 |
| 10426467 | Miller et al. | Oct 2019 | B2 |
| 10426468 | Contini et al. | Oct 2019 | B2 |
| 10426471 | Shelton, IV et al. | Oct 2019 | B2 |
| 10426481 | Aronhalt et al. | Oct 2019 | B2 |
| 10433837 | Worthington et al. | Oct 2019 | B2 |
| 10433844 | Shelton, IV et al. | Oct 2019 | B2 |
| 10433849 | Shelton, IV et al. | Oct 2019 | B2 |
| 10433918 | Shelton, IV et al. | Oct 2019 | B2 |
| 10441279 | Shelton, IV et al. | Oct 2019 | B2 |
| 10441281 | Shelton, IV et al. | Oct 2019 | B2 |
| 10441344 | Notz et al. | Oct 2019 | B2 |
| 10441345 | Aldridge et al. | Oct 2019 | B2 |
| 10448948 | Shelton, IV et al. | Oct 2019 | B2 |
| 10448950 | Shelton, IV et al. | Oct 2019 | B2 |
| 10456137 | Vendely et al. | Oct 2019 | B2 |
| 10456140 | Shelton, IV et al. | Oct 2019 | B2 |
| 10456193 | Yates et al. | Oct 2019 | B2 |
| 10463365 | Williams | Nov 2019 | B2 |
| 10463367 | Kostrzewski et al. | Nov 2019 | B2 |
| 10463371 | Kostrzewski | Nov 2019 | B2 |
| 10463436 | Jackson et al. | Nov 2019 | B2 |
| 10470684 | Toth et al. | Nov 2019 | B2 |
| 10470762 | Leimbach et al. | Nov 2019 | B2 |
| 10470764 | Baxter, III et al. | Nov 2019 | B2 |
| 10470768 | Harris et al. | Nov 2019 | B2 |
| 10470791 | Houser | Nov 2019 | B2 |
| 10471254 | Sano et al. | Nov 2019 | B2 |
| 10478181 | Shelton, IV et al. | Nov 2019 | B2 |
| 10478182 | Taylor | Nov 2019 | B2 |
| 10478185 | Nicholas | Nov 2019 | B2 |
| 10478189 | Bear et al. | Nov 2019 | B2 |
| 10478190 | Miller et al. | Nov 2019 | B2 |
| 10478544 | Friederichs et al. | Nov 2019 | B2 |
| 10485450 | Gupta et al. | Nov 2019 | B2 |
| 10485542 | Shelton, IV et al. | Nov 2019 | B2 |
| 10485543 | Shelton, IV et al. | Nov 2019 | B2 |
| 10492783 | Shelton, IV et al. | Dec 2019 | B2 |
| 10492784 | Beardsley et al. | Dec 2019 | B2 |
| 10492785 | Overmyer et al. | Dec 2019 | B2 |
| 10496788 | Amarasingham et al. | Dec 2019 | B2 |
| 10498269 | Zemlok et al. | Dec 2019 | B2 |
| 10499847 | Latimer et al. | Dec 2019 | B2 |
| 10499891 | Chaplin et al. | Dec 2019 | B2 |
| 10499914 | Huang et al. | Dec 2019 | B2 |
| 10499915 | Aranyi | Dec 2019 | B2 |
| 10499994 | Luks et al. | Dec 2019 | B2 |
| 10507068 | Kopp et al. | Dec 2019 | B2 |
| 10507278 | Gao et al. | Dec 2019 | B2 |
| 10510267 | Jarc et al. | Dec 2019 | B2 |
| 10512413 | Schepis et al. | Dec 2019 | B2 |
| 10512461 | Gupta et al. | Dec 2019 | B2 |
| 10512499 | McHenry et al. | Dec 2019 | B2 |
| 10512509 | Bowling et al. | Dec 2019 | B2 |
| 10512514 | Nowlin et al. | Dec 2019 | B2 |
| 10517588 | Gupta et al. | Dec 2019 | B2 |
| 10517595 | Hunter et al. | Dec 2019 | B2 |
| 10517596 | Hunter et al. | Dec 2019 | B2 |
| 10517686 | Vokrot et al. | Dec 2019 | B2 |
| 10524789 | Swayze et al. | Jan 2020 | B2 |
| 10531579 | Hsiao et al. | Jan 2020 | B2 |
| 10531874 | Morgan et al. | Jan 2020 | B2 |
| 10531929 | Widenhouse et al. | Jan 2020 | B2 |
| 10532330 | Diallo et al. | Jan 2020 | B2 |
| 10536617 | Liang et al. | Jan 2020 | B2 |
| 10537324 | Shelton, IV et al. | Jan 2020 | B2 |
| 10537325 | Bakos et al. | Jan 2020 | B2 |
| 10537351 | Shelton, IV et al. | Jan 2020 | B2 |
| 10537396 | Zingaretti et al. | Jan 2020 | B2 |
| 10537667 | Anim | Jan 2020 | B2 |
| 10542978 | Chowaniec et al. | Jan 2020 | B2 |
| 10542979 | Shelton, IV et al. | Jan 2020 | B2 |
| 10542982 | Beckman et al. | Jan 2020 | B2 |
| 10542991 | Shelton, IV et al. | Jan 2020 | B2 |
| D876466 | Kobayashi et al. | Feb 2020 | S |
| 10548504 | Shelton, IV et al. | Feb 2020 | B2 |
| 10548612 | Martinez et al. | Feb 2020 | B2 |
| 10548673 | Harris et al. | Feb 2020 | B2 |
| 10552574 | Sweeney | Feb 2020 | B2 |
| 10555675 | Satish et al. | Feb 2020 | B2 |
| 10555748 | Yates et al. | Feb 2020 | B2 |
| 10555750 | Conlon et al. | Feb 2020 | B2 |
| 10555769 | Worrell et al. | Feb 2020 | B2 |
| 10561349 | Wedekind et al. | Feb 2020 | B2 |
| 10561422 | Schellin et al. | Feb 2020 | B2 |
| 10561470 | Hourtash et al. | Feb 2020 | B2 |
| 10561471 | Nichogi | Feb 2020 | B2 |
| 10561560 | Boutoussov et al. | Feb 2020 | B2 |
| 10561753 | Thompson et al. | Feb 2020 | B2 |
| 10565170 | Walling et al. | Feb 2020 | B2 |
| 10568625 | Harris et al. | Feb 2020 | B2 |
| 10568626 | Shelton, IV et al. | Feb 2020 | B2 |
| 10568632 | Miller et al. | Feb 2020 | B2 |
| 10568704 | Savall et al. | Feb 2020 | B2 |
| 10575868 | Hall et al. | Mar 2020 | B2 |
| 10582928 | Hunter et al. | Mar 2020 | B2 |
| 10582931 | Mujawar | Mar 2020 | B2 |
| 10582962 | Friedrichs et al. | Mar 2020 | B2 |
| 10582964 | Weinberg et al. | Mar 2020 | B2 |
| 10586074 | Rose et al. | Mar 2020 | B2 |
| 10588623 | Schmid et al. | Mar 2020 | B2 |
| 10588625 | Weaner et al. | Mar 2020 | B2 |
| 10588629 | Malinouskas et al. | Mar 2020 | B2 |
| 10588630 | Shelton, IV et al. | Mar 2020 | B2 |
| 10588631 | Shelton, IV et al. | Mar 2020 | B2 |
| 10588632 | Shelton, IV et al. | Mar 2020 | B2 |
| 10588711 | DiCarlo et al. | Mar 2020 | B2 |
| 10592067 | Merdan et al. | Mar 2020 | B2 |
| 10595844 | Nawana et al. | Mar 2020 | B2 |
| 10595882 | Parfett et al. | Mar 2020 | B2 |
| 10595887 | Shelton, IV et al. | Mar 2020 | B2 |
| 10595930 | Scheib et al. | Mar 2020 | B2 |
| 10595952 | Forrest et al. | Mar 2020 | B2 |
| 10602007 | Takano | Mar 2020 | B2 |
| 10602848 | Magana | Mar 2020 | B2 |
| 10603036 | Hunter et al. | Mar 2020 | B2 |
| 10603128 | Zergiebel et al. | Mar 2020 | B2 |
| 10610223 | Wellman et al. | Apr 2020 | B2 |
| 10610224 | Shelton, IV et al. | Apr 2020 | B2 |
| 10610286 | Wiener et al. | Apr 2020 | B2 |
| 10610313 | Bailey et al. | Apr 2020 | B2 |
| 10617412 | Shelton, IV et al. | Apr 2020 | B2 |
| 10617413 | Shelton, IV et al. | Apr 2020 | B2 |
| 10617414 | Shelton, IV et al. | Apr 2020 | B2 |
| 10617482 | Houser et al. | Apr 2020 | B2 |
| 10617484 | Kilroy et al. | Apr 2020 | B2 |
| 10624635 | Harris et al. | Apr 2020 | B2 |
| 10624667 | Faller et al. | Apr 2020 | B2 |
| 10624691 | Wiener et al. | Apr 2020 | B2 |
| 10631423 | Collins et al. | Apr 2020 | B2 |
| 10631858 | Burbank | Apr 2020 | B2 |
| 10631912 | McFarlin et al. | Apr 2020 | B2 |
| 10631916 | Horner et al. | Apr 2020 | B2 |
| 10631917 | Ineson | Apr 2020 | B2 |
| 10631939 | Dachs, II et al. | Apr 2020 | B2 |
| 10639027 | Shelton, IV et al. | May 2020 | B2 |
| 10639034 | Harris et al. | May 2020 | B2 |
| 10639035 | Shelton, IV et al. | May 2020 | B2 |
| 10639036 | Yates et al. | May 2020 | B2 |
| 10639037 | Shelton, IV et al. | May 2020 | B2 |
| 10639039 | Vendely et al. | May 2020 | B2 |
| 10639098 | Cosman et al. | May 2020 | B2 |
| 10639111 | Kopp | May 2020 | B2 |
| 10639185 | Agrawal et al. | May 2020 | B2 |
| 10653413 | Worthington et al. | May 2020 | B2 |
| 10653476 | Ross | May 2020 | B2 |
| 10653489 | Kopp | May 2020 | B2 |
| 10656720 | Holz | May 2020 | B1 |
| 10660705 | Piron et al. | May 2020 | B2 |
| 10667809 | Bakos et al. | Jun 2020 | B2 |
| 10667810 | Shelton, IV et al. | Jun 2020 | B2 |
| 10667811 | Harris et al. | Jun 2020 | B2 |
| 10667877 | Kapadia | Jun 2020 | B2 |
| 10674897 | Levy | Jun 2020 | B2 |
| 10675021 | Harris et al. | Jun 2020 | B2 |
| 10675023 | Cappola | Jun 2020 | B2 |
| 10675024 | Shelton, IV et al. | Jun 2020 | B2 |
| 10675025 | Swayze et al. | Jun 2020 | B2 |
| 10675026 | Harris et al. | Jun 2020 | B2 |
| 10675035 | Zingman | Jun 2020 | B2 |
| 10675100 | Frushour | Jun 2020 | B2 |
| 10675104 | Kapadia | Jun 2020 | B2 |
| 10677764 | Ross et al. | Jun 2020 | B2 |
| 10679758 | Fox et al. | Jun 2020 | B2 |
| 10682136 | Harris et al. | Jun 2020 | B2 |
| 10682138 | Shelton, IV et al. | Jun 2020 | B2 |
| 10686805 | Reybok, Jr. et al. | Jun 2020 | B2 |
| 10687806 | Shelton, IV et al. | Jun 2020 | B2 |
| 10687809 | Shelton, IV et al. | Jun 2020 | B2 |
| 10687810 | Shelton, IV et al. | Jun 2020 | B2 |
| 10687884 | Wiener et al. | Jun 2020 | B2 |
| 10687905 | Kostrzewski | Jun 2020 | B2 |
| 10695055 | Shelton, IV et al. | Jun 2020 | B2 |
| 10695081 | Shelton, IV et al. | Jun 2020 | B2 |
| 10695134 | Barral et al. | Jun 2020 | B2 |
| 10702270 | Shelton, IV et al. | Jul 2020 | B2 |
| 10702271 | Aranyi et al. | Jul 2020 | B2 |
| 10709446 | Harris et al. | Jul 2020 | B2 |
| 10716473 | Greiner | Jul 2020 | B2 |
| 10716489 | Kalvoy et al. | Jul 2020 | B2 |
| 10716583 | Look et al. | Jul 2020 | B2 |
| 10716615 | Shelton, IV et al. | Jul 2020 | B2 |
| 10716639 | Kapadia et al. | Jul 2020 | B2 |
| 10717194 | Griffiths et al. | Jul 2020 | B2 |
| 10722222 | Aranyi | Jul 2020 | B2 |
| 10722233 | Wellman | Jul 2020 | B2 |
| 10722292 | Arya et al. | Jul 2020 | B2 |
| D893717 | Messerly et al. | Aug 2020 | S |
| 10729458 | Stoddard et al. | Aug 2020 | B2 |
| 10729509 | Shelton, IV et al. | Aug 2020 | B2 |
| 10733267 | Pedersen | Aug 2020 | B2 |
| 10736219 | Seow et al. | Aug 2020 | B2 |
| 10736498 | Watanabe et al. | Aug 2020 | B2 |
| 10736616 | Scheib et al. | Aug 2020 | B2 |
| 10736628 | Yates et al. | Aug 2020 | B2 |
| 10736629 | Shelton, IV et al. | Aug 2020 | B2 |
| 10736636 | Baxter, III et al. | Aug 2020 | B2 |
| 10736705 | Scheib et al. | Aug 2020 | B2 |
| 10743872 | Leimbach et al. | Aug 2020 | B2 |
| 10748115 | Laster et al. | Aug 2020 | B2 |
| 10751052 | Stokes et al. | Aug 2020 | B2 |
| 10751136 | Farritor et al. | Aug 2020 | B2 |
| 10751239 | Volek et al. | Aug 2020 | B2 |
| 10751768 | Hersey et al. | Aug 2020 | B2 |
| 10755813 | Shelton, IV et al. | Aug 2020 | B2 |
| D896379 | Shelton, IV et al. | Sep 2020 | S |
| 10758229 | Shelton, IV et al. | Sep 2020 | B2 |
| 10758230 | Shelton, IV et al. | Sep 2020 | B2 |
| 10758294 | Jones | Sep 2020 | B2 |
| 10758310 | Shelton, IV et al. | Sep 2020 | B2 |
| 10765376 | Brown, III et al. | Sep 2020 | B2 |
| 10765424 | Baxter, III et al. | Sep 2020 | B2 |
| 10765427 | Shelton, IV et al. | Sep 2020 | B2 |
| 10765470 | Yates et al. | Sep 2020 | B2 |
| 10772630 | Wixey | Sep 2020 | B2 |
| 10772651 | Shelton, IV et al. | Sep 2020 | B2 |
| 10772673 | Allen, IV et al. | Sep 2020 | B2 |
| 10772688 | Peine et al. | Sep 2020 | B2 |
| 10779818 | Zemlok et al. | Sep 2020 | B2 |
| 10779821 | Harris et al. | Sep 2020 | B2 |
| 10779823 | Shelton, IV et al. | Sep 2020 | B2 |
| 10779897 | Rockrohr | Sep 2020 | B2 |
| 10779900 | Pedros et al. | Sep 2020 | B2 |
| 10783634 | Nye et al. | Sep 2020 | B2 |
| 10786298 | Johnson | Sep 2020 | B2 |
| 10786317 | Zhou et al. | Sep 2020 | B2 |
| 10786327 | Anderson et al. | Sep 2020 | B2 |
| 10792038 | Becerra et al. | Oct 2020 | B2 |
| 10792118 | Prpa et al. | Oct 2020 | B2 |
| 10792422 | Douglas et al. | Oct 2020 | B2 |
| 10799304 | Kapadia et al. | Oct 2020 | B2 |
| 10803977 | Sanmugalingham | Oct 2020 | B2 |
| 10806445 | Penna et al. | Oct 2020 | B2 |
| 10806453 | Chen et al. | Oct 2020 | B2 |
| 10806454 | Kopp | Oct 2020 | B2 |
| 10806499 | Castaneda et al. | Oct 2020 | B2 |
| 10806506 | Gaspredes et al. | Oct 2020 | B2 |
| 10806532 | Grubbs et al. | Oct 2020 | B2 |
| 10811131 | Schneider et al. | Oct 2020 | B2 |
| 10813638 | Shelton, IV et al. | Oct 2020 | B2 |
| 10813703 | Swayze et al. | Oct 2020 | B2 |
| 10818383 | Sharifi Sedeh et al. | Oct 2020 | B2 |
| 10828028 | Harris et al. | Nov 2020 | B2 |
| 10828030 | Weir et al. | Nov 2020 | B2 |
| 10835206 | Bell et al. | Nov 2020 | B2 |
| 10835245 | Swayze et al. | Nov 2020 | B2 |
| 10835246 | Shelton, IV et al. | Nov 2020 | B2 |
| 10835247 | Shelton, IV et al. | Nov 2020 | B2 |
| 10838210 | Robaina et al. | Nov 2020 | B2 |
| 10842473 | Scheib et al. | Nov 2020 | B2 |
| 10842490 | DiNardo et al. | Nov 2020 | B2 |
| 10842492 | Shelton, IV et al. | Nov 2020 | B2 |
| 10842522 | Messerly et al. | Nov 2020 | B2 |
| 10842523 | Shelton, IV et al. | Nov 2020 | B2 |
| 10842575 | Panescu et al. | Nov 2020 | B2 |
| 10842897 | Schwartz et al. | Nov 2020 | B2 |
| D904612 | Wynn et al. | Dec 2020 | S |
| 10849697 | Yates et al. | Dec 2020 | B2 |
| 10849700 | Kopp et al. | Dec 2020 | B2 |
| 10856768 | Osadchy et al. | Dec 2020 | B2 |
| 10856867 | Shelton, IV et al. | Dec 2020 | B2 |
| 10856868 | Shelton, IV et al. | Dec 2020 | B2 |
| 10856870 | Harris et al. | Dec 2020 | B2 |
| 10863984 | Shelton, IV et al. | Dec 2020 | B2 |
| 10864037 | Mun et al. | Dec 2020 | B2 |
| 10864050 | Tabandeh et al. | Dec 2020 | B2 |
| 10872684 | McNutt et al. | Dec 2020 | B2 |
| 10874396 | Moore et al. | Dec 2020 | B2 |
| 10881399 | Shelton, IV et al. | Jan 2021 | B2 |
| 10881401 | Baber et al. | Jan 2021 | B2 |
| 10881446 | Strobl | Jan 2021 | B2 |
| 10881464 | Odermatt et al. | Jan 2021 | B2 |
| 10888321 | Shelton, IV et al. | Jan 2021 | B2 |
| 10888322 | Morgan et al. | Jan 2021 | B2 |
| 10892899 | Shelton, IV et al. | Jan 2021 | B2 |
| 10892995 | Shelton, IV et al. | Jan 2021 | B2 |
| 10893863 | Shelton, IV et al. | Jan 2021 | B2 |
| 10893864 | Harris et al. | Jan 2021 | B2 |
| 10893884 | Stoddard et al. | Jan 2021 | B2 |
| 10898105 | Weprin et al. | Jan 2021 | B2 |
| 10898183 | Shelton, IV et al. | Jan 2021 | B2 |
| 10898186 | Bakos et al. | Jan 2021 | B2 |
| 10898189 | Mcdonald, II | Jan 2021 | B2 |
| 10898256 | Yates et al. | Jan 2021 | B2 |
| 10898280 | Kopp | Jan 2021 | B2 |
| 10898622 | Shelton, IV et al. | Jan 2021 | B2 |
| 10902944 | Casey et al. | Jan 2021 | B1 |
| 10903685 | Yates et al. | Jan 2021 | B2 |
| 10905415 | DiNardo et al. | Feb 2021 | B2 |
| 10905418 | Shelton, IV et al. | Feb 2021 | B2 |
| 10905420 | Jasemian et al. | Feb 2021 | B2 |
| 10912559 | Harris et al. | Feb 2021 | B2 |
| 10912567 | Shelton, IV et al. | Feb 2021 | B2 |
| 10912580 | Green et al. | Feb 2021 | B2 |
| 10912619 | Jarc et al. | Feb 2021 | B2 |
| 10916415 | Karancsi et al. | Feb 2021 | B2 |
| 10918385 | Overmyer et al. | Feb 2021 | B2 |
| 10930400 | Robbins et al. | Feb 2021 | B2 |
| D914878 | Shelton, IV et al. | Mar 2021 | S |
| 10932705 | Muhsin et al. | Mar 2021 | B2 |
| 10932772 | Shelton, IV et al. | Mar 2021 | B2 |
| 10932784 | Mozdzierz et al. | Mar 2021 | B2 |
| 10932804 | Scheib et al. | Mar 2021 | B2 |
| 10932806 | Shelton, IV et al. | Mar 2021 | B2 |
| 10932872 | Shelton, IV et al. | Mar 2021 | B2 |
| 10939313 | Eom et al. | Mar 2021 | B2 |
| 10943454 | Shelton, IV et al. | Mar 2021 | B2 |
| 10944728 | Wiener et al. | Mar 2021 | B2 |
| 10945727 | Shelton, IV et al. | Mar 2021 | B2 |
| 10950982 | Regnier et al. | Mar 2021 | B2 |
| 10952708 | Scheib et al. | Mar 2021 | B2 |
| 10952732 | Binmoeller et al. | Mar 2021 | B2 |
| 10954935 | O'Shea et al. | Mar 2021 | B2 |
| 10959727 | Hunter et al. | Mar 2021 | B2 |
| 10959729 | Ehrenfels et al. | Mar 2021 | B2 |
| 10959744 | Shelton, IV et al. | Mar 2021 | B2 |
| 10959788 | Grover et al. | Mar 2021 | B2 |
| 10960150 | Zergiebel et al. | Mar 2021 | B2 |
| 10962449 | Unuma et al. | Mar 2021 | B2 |
| 10966590 | Takahashi et al. | Apr 2021 | B2 |
| 10966791 | Harris et al. | Apr 2021 | B2 |
| 10966798 | Tesar et al. | Apr 2021 | B2 |
| 10973516 | Shelton, IV et al. | Apr 2021 | B2 |
| 10973517 | Wixey | Apr 2021 | B2 |
| 10973520 | Shelton, IV et al. | Apr 2021 | B2 |
| 10973682 | Vezzu et al. | Apr 2021 | B2 |
| 10980536 | Weaner et al. | Apr 2021 | B2 |
| 10980537 | Shelton, IV et al. | Apr 2021 | B2 |
| 10980560 | Shelton, IV et al. | Apr 2021 | B2 |
| 10980595 | Wham | Apr 2021 | B2 |
| 10980610 | Rosenberg et al. | Apr 2021 | B2 |
| 10987102 | Gonzalez et al. | Apr 2021 | B2 |
| 10987178 | Shelton, IV et al. | Apr 2021 | B2 |
| 10992698 | Patel et al. | Apr 2021 | B2 |
| 10993715 | Shelton, IV et al. | May 2021 | B2 |
| 10998098 | Greene et al. | May 2021 | B2 |
| 11000276 | Shelton, IV et al. | May 2021 | B2 |
| 11000278 | Shelton, IV et al. | May 2021 | B2 |
| 11007004 | Shelton, IV et al. | May 2021 | B2 |
| 11007022 | Shelton, IV et al. | May 2021 | B2 |
| 11013563 | Shelton, IV et al. | May 2021 | B2 |
| 11020115 | Scheib et al. | Jun 2021 | B2 |
| 11026687 | Shelton, IV et al. | Jun 2021 | B2 |
| 11026712 | Shelton, IV et al. | Jun 2021 | B2 |
| 11026713 | Stokes et al. | Jun 2021 | B2 |
| 11026751 | Shelton, IV et al. | Jun 2021 | B2 |
| 11039834 | Harris et al. | Jun 2021 | B2 |
| 11045191 | Shelton, IV et al. | Jun 2021 | B2 |
| 11045192 | Harris et al. | Jun 2021 | B2 |
| 11045197 | Shelton, IV et al. | Jun 2021 | B2 |
| 11045591 | Shelton, IV et al. | Jun 2021 | B2 |
| 11051817 | Shelton, IV et al. | Jul 2021 | B2 |
| 11051836 | Shelton, IV et al. | Jul 2021 | B2 |
| 11051873 | Wiener et al. | Jul 2021 | B2 |
| 11051876 | Shelton, IV et al. | Jul 2021 | B2 |
| 11051902 | Kruecker et al. | Jul 2021 | B2 |
| 11056244 | Shelton, IV et al. | Jul 2021 | B2 |
| 11058423 | Shelton, IV et al. | Jul 2021 | B2 |
| 11058498 | Shelton, IV et al. | Jul 2021 | B2 |
| 11058501 | Tokarchuk et al. | Jul 2021 | B2 |
| 11064997 | Shelton, IV et al. | Jul 2021 | B2 |
| 11069012 | Shelton, IV et al. | Jul 2021 | B2 |
| 11071560 | Deck et al. | Jul 2021 | B2 |
| 11071595 | Johnson et al. | Jul 2021 | B2 |
| 11076921 | Shelton, IV et al. | Aug 2021 | B2 |
| 11083458 | Harris et al. | Aug 2021 | B2 |
| 11090047 | Shelton, IV et al. | Aug 2021 | B2 |
| 11090048 | Fanelli et al. | Aug 2021 | B2 |
| 11090075 | Hunter et al. | Aug 2021 | B2 |
| 11096688 | Shelton, IV et al. | Aug 2021 | B2 |
| 11096693 | Shelton, IV et al. | Aug 2021 | B2 |
| 11100631 | Yates et al. | Aug 2021 | B2 |
| 11103246 | Marczyk et al. | Aug 2021 | B2 |
| 11103268 | Shelton, IV et al. | Aug 2021 | B2 |
| 11109866 | Shelton, IV et al. | Sep 2021 | B2 |
| 11109878 | Shelton, IV et al. | Sep 2021 | B2 |
| 11114195 | Shelton, IV et al. | Sep 2021 | B2 |
| 11116485 | Scheib et al. | Sep 2021 | B2 |
| 11123070 | Shelton, IV et al. | Sep 2021 | B2 |
| 11129611 | Shelton, IV et al. | Sep 2021 | B2 |
| 11129634 | Scheib et al. | Sep 2021 | B2 |
| 11129636 | Shelton, IV et al. | Sep 2021 | B2 |
| 11129669 | Stulen et al. | Sep 2021 | B2 |
| 11129670 | Shelton, IV et al. | Sep 2021 | B2 |
| 11132462 | Shelton, IV et al. | Sep 2021 | B2 |
| 11134942 | Harris et al. | Oct 2021 | B2 |
| 11141160 | Shelton, IV et al. | Oct 2021 | B2 |
| 11141213 | Yates et al. | Oct 2021 | B2 |
| 11147607 | Yates et al. | Oct 2021 | B2 |
| 11160551 | Shelton, IV et al. | Nov 2021 | B2 |
| 11160605 | Shelton, IV et al. | Nov 2021 | B2 |
| 11166716 | Shelton, IV et al. | Nov 2021 | B2 |
| 11166772 | Shelton, IV et al. | Nov 2021 | B2 |
| 11179150 | Yates et al. | Nov 2021 | B2 |
| 11179151 | Shelton, IV et al. | Nov 2021 | B2 |
| 11179155 | Shelton, IV et al. | Nov 2021 | B2 |
| 11179175 | Houser et al. | Nov 2021 | B2 |
| 11179204 | Shelton, IV et al. | Nov 2021 | B2 |
| 11179208 | Yates et al. | Nov 2021 | B2 |
| 11183293 | Lu et al. | Nov 2021 | B2 |
| 11185325 | Shelton, IV et al. | Nov 2021 | B2 |
| 11185330 | Huitema et al. | Nov 2021 | B2 |
| 11191539 | Overmyer et al. | Dec 2021 | B2 |
| 11191540 | Aronhalt et al. | Dec 2021 | B2 |
| 11197668 | Shelton, IV et al. | Dec 2021 | B2 |
| 11197731 | Hoffman et al. | Dec 2021 | B2 |
| 11202570 | Shelton, IV et al. | Dec 2021 | B2 |
| 11207065 | Harris et al. | Dec 2021 | B2 |
| 11207067 | Shelton, IV et al. | Dec 2021 | B2 |
| 11207090 | Shelton, IV et al. | Dec 2021 | B2 |
| 11213293 | Worthington et al. | Jan 2022 | B2 |
| 11213294 | Shelton, IV et al. | Jan 2022 | B2 |
| 11213359 | Shelton, IV et al. | Jan 2022 | B2 |
| 11218822 | Morgan et al. | Jan 2022 | B2 |
| 11219453 | Shelton, IV et al. | Jan 2022 | B2 |
| 11224426 | Shelton, IV et al. | Jan 2022 | B2 |
| 11229436 | Shelton, IV et al. | Jan 2022 | B2 |
| 11229471 | Shelton, IV et al. | Jan 2022 | B2 |
| 11234756 | Shelton, IV et al. | Feb 2022 | B2 |
| 11241230 | Shelton, IV et al. | Feb 2022 | B2 |
| 11253256 | Harris et al. | Feb 2022 | B2 |
| 11253315 | Yates et al. | Feb 2022 | B2 |
| 11257589 | Shelton, IV et al. | Feb 2022 | B2 |
| 11259806 | Shelton, IV et al. | Mar 2022 | B2 |
| 11259807 | Shelton, IV et al. | Mar 2022 | B2 |
| 11259830 | Nott et al. | Mar 2022 | B2 |
| 11266409 | Huitema et al. | Mar 2022 | B2 |
| 11266468 | Shelton, IV et al. | Mar 2022 | B2 |
| 11272931 | Boudreaux et al. | Mar 2022 | B2 |
| 11273001 | Shelton, IV et al. | Mar 2022 | B2 |
| 11273290 | Kowshik | Mar 2022 | B2 |
| 11278280 | Shelton, IV et al. | Mar 2022 | B2 |
| 11278281 | Shelton, IV et al. | Mar 2022 | B2 |
| 11284890 | Nalagatla et al. | Mar 2022 | B2 |
| 11284936 | Shelton, IV et al. | Mar 2022 | B2 |
| 11289188 | Mabotuwana et al. | Mar 2022 | B2 |
| 11291440 | Harris et al. | Apr 2022 | B2 |
| 11291441 | Giordano et al. | Apr 2022 | B2 |
| 11291444 | Boudreaux et al. | Apr 2022 | B2 |
| 11291445 | Shelton, IV et al. | Apr 2022 | B2 |
| 11291465 | Parihar et al. | Apr 2022 | B2 |
| 11291495 | Yates et al. | Apr 2022 | B2 |
| 11291510 | Shelton, IV et al. | Apr 2022 | B2 |
| 11298128 | Messerly et al. | Apr 2022 | B2 |
| 11298129 | Bakos et al. | Apr 2022 | B2 |
| 11298130 | Bakos et al. | Apr 2022 | B2 |
| 11298148 | Jayme et al. | Apr 2022 | B2 |
| 11304699 | Shelton, IV et al. | Apr 2022 | B2 |
| 11304720 | Kimball et al. | Apr 2022 | B2 |
| 11304745 | Shelton, IV et al. | Apr 2022 | B2 |
| 11304763 | Shelton, IV et al. | Apr 2022 | B2 |
| 11308075 | Shelton, IV et al. | Apr 2022 | B2 |
| 11311306 | Shelton, IV et al. | Apr 2022 | B2 |
| 11311342 | Parihar et al. | Apr 2022 | B2 |
| D950728 | Bakos et al. | May 2022 | S |
| D952144 | Boudreaux | May 2022 | S |
| 11317915 | Boudreaux et al. | May 2022 | B2 |
| 11317919 | Shelton, IV et al. | May 2022 | B2 |
| 11317937 | Nott et al. | May 2022 | B2 |
| 11322248 | Grantcharov et al. | May 2022 | B2 |
| 11324557 | Shelton, IV et al. | May 2022 | B2 |
| 11331100 | Boudreaux et al. | May 2022 | B2 |
| 11331101 | Harris et al. | May 2022 | B2 |
| 11337746 | Boudreaux | May 2022 | B2 |
| 11344326 | Faller et al. | May 2022 | B2 |
| 11350932 | Shelton, IV et al. | Jun 2022 | B2 |
| 11350959 | Messerly et al. | Jun 2022 | B2 |
| 11350978 | Henderson et al. | Jun 2022 | B2 |
| 11357503 | Bakos et al. | Jun 2022 | B2 |
| 11364075 | Yates et al. | Jun 2022 | B2 |
| 11369377 | Boudreaux et al. | Jun 2022 | B2 |
| 11373755 | Shelton, IV et al. | Jun 2022 | B2 |
| 11376002 | Shelton, IV et al. | Jul 2022 | B2 |
| 11376098 | Shelton, IV et al. | Jul 2022 | B2 |
| 11382697 | Shelton, IV et al. | Jul 2022 | B2 |
| 11382715 | Arai et al. | Jul 2022 | B2 |
| 11389164 | Yates et al. | Jul 2022 | B2 |
| 11389188 | Gee et al. | Jul 2022 | B2 |
| 11399858 | Sawhney et al. | Aug 2022 | B2 |
| 11406382 | Shelton, IV et al. | Aug 2022 | B2 |
| 11406390 | Shelton, IV et al. | Aug 2022 | B2 |
| 11410259 | Harris et al. | Aug 2022 | B2 |
| 11413042 | Shelton, IV et al. | Aug 2022 | B2 |
| 11419606 | Overmyer et al. | Aug 2022 | B2 |
| 11419630 | Yates et al. | Aug 2022 | B2 |
| 11419667 | Messerly et al. | Aug 2022 | B2 |
| 11423007 | Shelton, IV et al. | Aug 2022 | B2 |
| 11424027 | Shelton, IV | Aug 2022 | B2 |
| D964564 | Boudreaux | Sep 2022 | S |
| 11432885 | Shelton, IV et al. | Sep 2022 | B2 |
| 11446052 | Shelton, IV et al. | Sep 2022 | B2 |
| 11457944 | Scoggins | Oct 2022 | B2 |
| 11464511 | Timm et al. | Oct 2022 | B2 |
| 11464513 | Shelton, IV et al. | Oct 2022 | B2 |
| 11464514 | Yates et al. | Oct 2022 | B2 |
| 11464532 | Nott et al. | Oct 2022 | B2 |
| 11464535 | Shelton, IV et al. | Oct 2022 | B2 |
| 11464559 | Nott et al. | Oct 2022 | B2 |
| 11464971 | Schepis et al. | Oct 2022 | B2 |
| 11471156 | Shelton, IV et al. | Oct 2022 | B2 |
| 11471206 | Henderson et al. | Oct 2022 | B2 |
| 11478244 | DiNardo et al. | Oct 2022 | B2 |
| 11504191 | Mccloud et al. | Nov 2022 | B2 |
| 11504192 | Shelton, IV et al. | Nov 2022 | B2 |
| 11510671 | Shelton, IV et al. | Nov 2022 | B2 |
| 11510675 | Shelton, IV et al. | Nov 2022 | B2 |
| 11510720 | Morgan et al. | Nov 2022 | B2 |
| 11510741 | Shelton, IV et al. | Nov 2022 | B2 |
| 11517309 | Bakos et al. | Dec 2022 | B2 |
| 11517315 | Huitema et al. | Dec 2022 | B2 |
| 11529187 | Shelton, IV et al. | Dec 2022 | B2 |
| 11534196 | Black | Dec 2022 | B2 |
| 11540824 | Shelton, IV et al. | Jan 2023 | B2 |
| 11540855 | Messerly et al. | Jan 2023 | B2 |
| 11547468 | Shelton, IV et al. | Jan 2023 | B2 |
| 11559307 | Shelton, IV et al. | Jan 2023 | B2 |
| 11559308 | Yates et al. | Jan 2023 | B2 |
| 11564703 | Shelton, IV et al. | Jan 2023 | B2 |
| 11564756 | Shelton, IV et al. | Jan 2023 | B2 |
| 11571210 | Shelton, IV et al. | Feb 2023 | B2 |
| 11571212 | Yates et al. | Feb 2023 | B2 |
| 11571234 | Nott et al. | Feb 2023 | B2 |
| 11576677 | Shelton, IV et al. | Feb 2023 | B2 |
| 11589865 | Shelton, IV et al. | Feb 2023 | B2 |
| 11589888 | Shelton, IV et al. | Feb 2023 | B2 |
| 11589915 | Stulen | Feb 2023 | B2 |
| 11589932 | Shelton, IV et al. | Feb 2023 | B2 |
| 11596291 | Harris et al. | Mar 2023 | B2 |
| 11601371 | Shelton, IV | Mar 2023 | B2 |
| 11602366 | Shelton, IV et al. | Mar 2023 | B2 |
| 11602393 | Shelton, IV et al. | Mar 2023 | B2 |
| 11602612 | Hara et al. | Mar 2023 | B2 |
| 11607239 | Swensgard et al. | Mar 2023 | B2 |
| 11612408 | Yates et al. | Mar 2023 | B2 |
| 11612444 | Shelton, IV et al. | Mar 2023 | B2 |
| 11617597 | Sawhney et al. | Apr 2023 | B2 |
| 11628006 | Henderson et al. | Apr 2023 | B2 |
| 11633237 | Shelton, IV et al. | Apr 2023 | B2 |
| 11638602 | Henderson et al. | May 2023 | B2 |
| 11648022 | Shelton, IV | May 2023 | B2 |
| 11653917 | Scott et al. | May 2023 | B2 |
| 11659023 | Shelton, IV et al. | May 2023 | B2 |
| 11666331 | Shelton, IV et al. | Jun 2023 | B2 |
| 11666368 | Henderson et al. | Jun 2023 | B2 |
| 11672605 | Messerly et al. | Jun 2023 | B2 |
| 11678881 | Yates et al. | Jun 2023 | B2 |
| 11678901 | Scoggins et al. | Jun 2023 | B2 |
| 11678925 | Henderson et al. | Jun 2023 | B2 |
| 11678927 | Brady et al. | Jun 2023 | B2 |
| 11684400 | Jayme et al. | Jun 2023 | B2 |
| 11684401 | Oberkircher et al. | Jun 2023 | B2 |
| 11696760 | Shelton, IV et al. | Jul 2023 | B2 |
| 11696778 | Shelton, IV et al. | Jul 2023 | B2 |
| 11696789 | Petre et al. | Jul 2023 | B2 |
| 11696790 | Oberkircher et al. | Jul 2023 | B2 |
| 11696791 | Henderson et al. | Jul 2023 | B2 |
| 11701115 | Harris et al. | Jul 2023 | B2 |
| 11701139 | Nott et al. | Jul 2023 | B2 |
| 11701162 | Cuti et al. | Jul 2023 | B2 |
| 11701185 | Shelton, IV et al. | Jul 2023 | B2 |
| 11707293 | Denzinger et al. | Jul 2023 | B2 |
| 11712280 | Henderson et al. | Aug 2023 | B2 |
| 11712303 | Shelton, IV et al. | Aug 2023 | B2 |
| 11737668 | Shelton, IV et al. | Aug 2023 | B2 |
| 11743665 | Morgan et al. | Aug 2023 | B2 |
| 11744604 | Shelton, IV et al. | Sep 2023 | B2 |
| 11751872 | Zeiner et al. | Sep 2023 | B2 |
| 11751958 | Shelton, IV et al. | Sep 2023 | B2 |
| 11759224 | Shelton, IV et al. | Sep 2023 | B2 |
| 11771454 | Swensgard et al. | Oct 2023 | B2 |
| 11771487 | Shelton, IV et al. | Oct 2023 | B2 |
| 11775682 | Shelton, IV et al. | Oct 2023 | B2 |
| 11786245 | Shelton, IV | Oct 2023 | B2 |
| 11786251 | Shelton, IV et al. | Oct 2023 | B2 |
| 11793537 | Shelton, IV et al. | Oct 2023 | B2 |
| 11801098 | Stokes et al. | Oct 2023 | B2 |
| 11804679 | Henderson et al. | Oct 2023 | B2 |
| 11806062 | Henderson et al. | Nov 2023 | B2 |
| 11818052 | Shelton, IV et al. | Nov 2023 | B2 |
| 11819231 | Shelton, IV et al. | Nov 2023 | B2 |
| 11832899 | Shelton, IV et al. | Dec 2023 | B2 |
| 11839396 | Denzinger et al. | Dec 2023 | B2 |
| 11844545 | Scoggins et al. | Dec 2023 | B2 |
| 11844579 | Shelton, IV et al. | Dec 2023 | B2 |
| 20010056237 | Cane et al. | Dec 2001 | A1 |
| 20020049551 | Friedman et al. | Apr 2002 | A1 |
| 20020052616 | Wiener et al. | May 2002 | A1 |
| 20020072746 | Lingenfelder et al. | Jun 2002 | A1 |
| 20020138642 | Miyazawa et al. | Sep 2002 | A1 |
| 20020144147 | Basson et al. | Oct 2002 | A1 |
| 20020169584 | Fu et al. | Nov 2002 | A1 |
| 20020194023 | Turley et al. | Dec 2002 | A1 |
| 20030009111 | Cory et al. | Jan 2003 | A1 |
| 20030009154 | Whitman | Jan 2003 | A1 |
| 20030018329 | Hooven | Jan 2003 | A1 |
| 20030028183 | Sanchez et al. | Feb 2003 | A1 |
| 20030046109 | Uchikubo | Mar 2003 | A1 |
| 20030050654 | Whitman et al. | Mar 2003 | A1 |
| 20030069573 | Kadhiresan et al. | Apr 2003 | A1 |
| 20030093503 | Yamaki et al. | May 2003 | A1 |
| 20030114851 | Truckai et al. | Jun 2003 | A1 |
| 20030120284 | Palacios et al. | Jun 2003 | A1 |
| 20030130711 | Pearson et al. | Jul 2003 | A1 |
| 20030195662 | Wang et al. | Oct 2003 | A1 |
| 20030208465 | Yurko et al. | Nov 2003 | A1 |
| 20030210812 | Khamene et al. | Nov 2003 | A1 |
| 20030223877 | Anstine et al. | Dec 2003 | A1 |
| 20040015053 | Bieger et al. | Jan 2004 | A1 |
| 20040044546 | Moore | Mar 2004 | A1 |
| 20040078236 | Stoodley et al. | Apr 2004 | A1 |
| 20040082850 | Bonner et al. | Apr 2004 | A1 |
| 20040092992 | Adams et al. | May 2004 | A1 |
| 20040097913 | Refior et al. | May 2004 | A1 |
| 20040108825 | Lee et al. | Jun 2004 | A1 |
| 20040199180 | Knodel et al. | Oct 2004 | A1 |
| 20040199659 | Ishikawa et al. | Oct 2004 | A1 |
| 20040206365 | Knowlton | Oct 2004 | A1 |
| 20040215131 | Sakurai | Oct 2004 | A1 |
| 20040229496 | Robinson et al. | Nov 2004 | A1 |
| 20040243147 | Lipow | Dec 2004 | A1 |
| 20040243148 | Wasielewski | Dec 2004 | A1 |
| 20040243435 | Williams | Dec 2004 | A1 |
| 20050020909 | Moctezuma de la Barrera et al. | Jan 2005 | A1 |
| 20050020918 | Wilk et al. | Jan 2005 | A1 |
| 20050021027 | Shields et al. | Jan 2005 | A1 |
| 20050023324 | Doll et al. | Feb 2005 | A1 |
| 20050033108 | Sawyer | Feb 2005 | A1 |
| 20050063575 | Ma et al. | Mar 2005 | A1 |
| 20050065438 | Miller | Mar 2005 | A1 |
| 20050070800 | Takahashi | Mar 2005 | A1 |
| 20050100867 | Hilscher et al. | May 2005 | A1 |
| 20050131390 | Heinrich et al. | Jun 2005 | A1 |
| 20050139629 | Schwemberger et al. | Jun 2005 | A1 |
| 20050143759 | Kelly | Jun 2005 | A1 |
| 20050148854 | Ito et al. | Jul 2005 | A1 |
| 20050149001 | Uchikubo et al. | Jul 2005 | A1 |
| 20050149356 | Cyr et al. | Jul 2005 | A1 |
| 20050165390 | Mauti et al. | Jul 2005 | A1 |
| 20050182655 | Merzlak et al. | Aug 2005 | A1 |
| 20050192633 | Montpetit | Sep 2005 | A1 |
| 20050203380 | Sauer et al. | Sep 2005 | A1 |
| 20050203384 | Sati et al. | Sep 2005 | A1 |
| 20050203504 | Wham et al. | Sep 2005 | A1 |
| 20050213832 | Schofield et al. | Sep 2005 | A1 |
| 20050222631 | Dalal et al. | Oct 2005 | A1 |
| 20050228246 | Lee et al. | Oct 2005 | A1 |
| 20050228425 | Boukhny et al. | Oct 2005 | A1 |
| 20050236474 | Onuma et al. | Oct 2005 | A1 |
| 20050251233 | Kanzius | Nov 2005 | A1 |
| 20050277913 | McCary | Dec 2005 | A1 |
| 20050288425 | Lee et al. | Dec 2005 | A1 |
| 20060020272 | Gildenberg | Jan 2006 | A1 |
| 20060025816 | Shelton | Feb 2006 | A1 |
| 20060039105 | Smith et al. | Feb 2006 | A1 |
| 20060059018 | Shiobara | Mar 2006 | A1 |
| 20060069388 | Truckai et al. | Mar 2006 | A1 |
| 20060079872 | Eggleston | Apr 2006 | A1 |
| 20060079874 | Faller et al. | Apr 2006 | A1 |
| 20060116908 | Dew et al. | Jun 2006 | A1 |
| 20060122558 | Sherman et al. | Jun 2006 | A1 |
| 20060136622 | Rouvelin et al. | Jun 2006 | A1 |
| 20060142739 | DiSilestro et al. | Jun 2006 | A1 |
| 20060184160 | Ozaki et al. | Aug 2006 | A1 |
| 20060241399 | Fabian | Oct 2006 | A1 |
| 20060282009 | Oberg et al. | Dec 2006 | A1 |
| 20060287645 | Tashiro et al. | Dec 2006 | A1 |
| 20070005002 | Millman et al. | Jan 2007 | A1 |
| 20070010838 | Shelton et al. | Jan 2007 | A1 |
| 20070016235 | Tanaka et al. | Jan 2007 | A1 |
| 20070016979 | Damaj et al. | Jan 2007 | A1 |
| 20070027459 | Horvath et al. | Feb 2007 | A1 |
| 20070038080 | Salisbury et al. | Feb 2007 | A1 |
| 20070049947 | Menn et al. | Mar 2007 | A1 |
| 20070066970 | Ineson | Mar 2007 | A1 |
| 20070073389 | Bolduc et al. | Mar 2007 | A1 |
| 20070078678 | DiSilvestro et al. | Apr 2007 | A1 |
| 20070084896 | Doll et al. | Apr 2007 | A1 |
| 20070085528 | Govari et al. | Apr 2007 | A1 |
| 20070156019 | Larkin et al. | Jul 2007 | A1 |
| 20070156139 | Schechter et al. | Jul 2007 | A1 |
| 20070161979 | McPherson | Jul 2007 | A1 |
| 20070167702 | Hasser et al. | Jul 2007 | A1 |
| 20070168461 | Moore | Jul 2007 | A1 |
| 20070173803 | Wham et al. | Jul 2007 | A1 |
| 20070173811 | Couture et al. | Jul 2007 | A1 |
| 20070175951 | Shelton et al. | Aug 2007 | A1 |
| 20070175955 | Shelton et al. | Aug 2007 | A1 |
| 20070179482 | Anderson | Aug 2007 | A1 |
| 20070179508 | Arndt | Aug 2007 | A1 |
| 20070191713 | Eichmann et al. | Aug 2007 | A1 |
| 20070192139 | Cookson et al. | Aug 2007 | A1 |
| 20070203744 | Scholl | Aug 2007 | A1 |
| 20070225556 | Ortiz et al. | Sep 2007 | A1 |
| 20070225690 | Sekiguchi et al. | Sep 2007 | A1 |
| 20070239028 | Houser et al. | Oct 2007 | A1 |
| 20070244478 | Bahney | Oct 2007 | A1 |
| 20070249990 | Cosmescu | Oct 2007 | A1 |
| 20070270660 | Caylor et al. | Nov 2007 | A1 |
| 20070270688 | Gelbart et al. | Nov 2007 | A1 |
| 20070282195 | Masini et al. | Dec 2007 | A1 |
| 20070282321 | Shah et al. | Dec 2007 | A1 |
| 20070282333 | Fortson et al. | Dec 2007 | A1 |
| 20070293218 | Meylan et al. | Dec 2007 | A1 |
| 20080013460 | Allen et al. | Jan 2008 | A1 |
| 20080015664 | Podhajsky | Jan 2008 | A1 |
| 20080015912 | Rosenthal et al. | Jan 2008 | A1 |
| 20080019393 | Yamaki | Jan 2008 | A1 |
| 20080033404 | Romoda et al. | Feb 2008 | A1 |
| 20080039742 | Hashimshony et al. | Feb 2008 | A1 |
| 20080040151 | Moore | Feb 2008 | A1 |
| 20080058593 | Gu et al. | Mar 2008 | A1 |
| 20080059658 | Williams | Mar 2008 | A1 |
| 20080077158 | Haider et al. | Mar 2008 | A1 |
| 20080083414 | Messerges | Apr 2008 | A1 |
| 20080091071 | Kumar et al. | Apr 2008 | A1 |
| 20080114212 | Messerges | May 2008 | A1 |
| 20080114350 | Park et al. | May 2008 | A1 |
| 20080129465 | Rao | Jun 2008 | A1 |
| 20080140090 | Aranyi et al. | Jun 2008 | A1 |
| 20080147529 | Kreiner | Jun 2008 | A1 |
| 20080164296 | Shelton et al. | Jul 2008 | A1 |
| 20080167644 | Shelton et al. | Jul 2008 | A1 |
| 20080177258 | Govari et al. | Jul 2008 | A1 |
| 20080177362 | Phillips et al. | Jul 2008 | A1 |
| 20080200940 | Eichmann et al. | Aug 2008 | A1 |
| 20080223904 | Marczyk | Sep 2008 | A1 |
| 20080234708 | Houser et al. | Sep 2008 | A1 |
| 20080235052 | Node-Langlois et al. | Sep 2008 | A1 |
| 20080245841 | Smith et al. | Oct 2008 | A1 |
| 20080255413 | Zemlok et al. | Oct 2008 | A1 |
| 20080262654 | Omori et al. | Oct 2008 | A1 |
| 20080272172 | Zemlok et al. | Nov 2008 | A1 |
| 20080281301 | DeBoer et al. | Nov 2008 | A1 |
| 20080281678 | Keuls et al. | Nov 2008 | A1 |
| 20080296346 | Shelton, IV et al. | Dec 2008 | A1 |
| 20080306759 | Ilkin et al. | Dec 2008 | A1 |
| 20080312953 | Claus | Dec 2008 | A1 |
| 20090017910 | Rofougaran et al. | Jan 2009 | A1 |
| 20090030437 | Houser et al. | Jan 2009 | A1 |
| 20090036750 | Weinstein et al. | Feb 2009 | A1 |
| 20090036794 | Stubhaug et al. | Feb 2009 | A1 |
| 20090043253 | Podaima | Feb 2009 | A1 |
| 20090046146 | Hoyt | Feb 2009 | A1 |
| 20090048589 | Takashino et al. | Feb 2009 | A1 |
| 20090048595 | Mihori et al. | Feb 2009 | A1 |
| 20090048611 | Funda et al. | Feb 2009 | A1 |
| 20090076409 | Wu et al. | Mar 2009 | A1 |
| 20090090763 | Zemlok et al. | Apr 2009 | A1 |
| 20090093702 | Vollmer et al. | Apr 2009 | A1 |
| 20090099866 | Newman | Apr 2009 | A1 |
| 20090114699 | Viola | May 2009 | A1 |
| 20090128084 | Johnson et al. | May 2009 | A1 |
| 20090138095 | Giordano | May 2009 | A1 |
| 20090157072 | Wham et al. | Jun 2009 | A1 |
| 20090157695 | Roberts | Jun 2009 | A1 |
| 20090182577 | Squilla et al. | Jul 2009 | A1 |
| 20090188094 | Cunningham et al. | Jul 2009 | A1 |
| 20090192591 | Ryan et al. | Jul 2009 | A1 |
| 20090206131 | Weisenburgh, II et al. | Aug 2009 | A1 |
| 20090217932 | Voegele | Sep 2009 | A1 |
| 20090234352 | Behnke et al. | Sep 2009 | A1 |
| 20090259149 | Tahara et al. | Oct 2009 | A1 |
| 20090259221 | Tahara et al. | Oct 2009 | A1 |
| 20090259489 | Kimura et al. | Oct 2009 | A1 |
| 20090270678 | Scott et al. | Oct 2009 | A1 |
| 20090281541 | Ibrahim et al. | Nov 2009 | A1 |
| 20090299214 | Wu et al. | Dec 2009 | A1 |
| 20090306581 | Claus | Dec 2009 | A1 |
| 20090307681 | Armado et al. | Dec 2009 | A1 |
| 20090326321 | Jacobsen et al. | Dec 2009 | A1 |
| 20090326336 | Lemke et al. | Dec 2009 | A1 |
| 20100036192 | Yao et al. | Feb 2010 | A1 |
| 20100036374 | Ward | Feb 2010 | A1 |
| 20100036405 | Giordano et al. | Feb 2010 | A1 |
| 20100038403 | D'Arcangelo | Feb 2010 | A1 |
| 20100057106 | Sorrentino et al. | Mar 2010 | A1 |
| 20100065604 | Weng | Mar 2010 | A1 |
| 20100069939 | Konishi | Mar 2010 | A1 |
| 20100069942 | Shelton, IV | Mar 2010 | A1 |
| 20100070417 | Flynn et al. | Mar 2010 | A1 |
| 20100120266 | Rimborg | May 2010 | A1 |
| 20100132334 | Duclos et al. | Jun 2010 | A1 |
| 20100137845 | Ramstein et al. | Jun 2010 | A1 |
| 20100137886 | Zergiebel et al. | Jun 2010 | A1 |
| 20100168561 | Anderson | Jul 2010 | A1 |
| 20100179831 | Brown et al. | Jul 2010 | A1 |
| 20100191100 | Anderson et al. | Jul 2010 | A1 |
| 20100194574 | Monk et al. | Aug 2010 | A1 |
| 20100198200 | Horvath | Aug 2010 | A1 |
| 20100198220 | Boudreaux et al. | Aug 2010 | A1 |
| 20100198248 | Vakharia | Aug 2010 | A1 |
| 20100204717 | Knodel | Aug 2010 | A1 |
| 20100217991 | Choi | Aug 2010 | A1 |
| 20100234996 | Schreiber et al. | Sep 2010 | A1 |
| 20100235689 | Tian et al. | Sep 2010 | A1 |
| 20100250571 | Pierce et al. | Sep 2010 | A1 |
| 20100258327 | Esenwein et al. | Oct 2010 | A1 |
| 20100280247 | Mutti et al. | Nov 2010 | A1 |
| 20100292535 | Paskar | Nov 2010 | A1 |
| 20100292684 | Cybulski et al. | Nov 2010 | A1 |
| 20100301095 | Shelton, IV et al. | Dec 2010 | A1 |
| 20110006876 | Moberg et al. | Jan 2011 | A1 |
| 20110015649 | Anvari et al. | Jan 2011 | A1 |
| 20110022032 | Zemlok et al. | Jan 2011 | A1 |
| 20110036890 | Ma | Feb 2011 | A1 |
| 20110043612 | Keller et al. | Feb 2011 | A1 |
| 20110046618 | Minar et al. | Feb 2011 | A1 |
| 20110071530 | Carson | Mar 2011 | A1 |
| 20110077512 | Boswell | Mar 2011 | A1 |
| 20110087238 | Wang et al. | Apr 2011 | A1 |
| 20110087502 | Yelton et al. | Apr 2011 | A1 |
| 20110105277 | Shauli | May 2011 | A1 |
| 20110105895 | Kornblau et al. | May 2011 | A1 |
| 20110112569 | Friedman et al. | May 2011 | A1 |
| 20110118708 | Burbank et al. | May 2011 | A1 |
| 20110119075 | Dhoble | May 2011 | A1 |
| 20110125149 | El-Galley et al. | May 2011 | A1 |
| 20110152712 | Cao et al. | Jun 2011 | A1 |
| 20110163147 | Laurent et al. | Jul 2011 | A1 |
| 20110166883 | Palmer et al. | Jul 2011 | A1 |
| 20110196398 | Robertson et al. | Aug 2011 | A1 |
| 20110209128 | Nikara et al. | Aug 2011 | A1 |
| 20110218526 | Mathur | Sep 2011 | A1 |
| 20110222746 | Kotula et al. | Sep 2011 | A1 |
| 20110237883 | Chun | Sep 2011 | A1 |
| 20110238079 | Hannaford et al. | Sep 2011 | A1 |
| 20110251612 | Faller et al. | Oct 2011 | A1 |
| 20110264000 | Paul et al. | Oct 2011 | A1 |
| 20110264078 | Lipow et al. | Oct 2011 | A1 |
| 20110264086 | Ingle | Oct 2011 | A1 |
| 20110265311 | Kondo et al. | Nov 2011 | A1 |
| 20110273465 | Konishi et al. | Nov 2011 | A1 |
| 20110278343 | Knodel et al. | Nov 2011 | A1 |
| 20110290024 | Lefler | Dec 2011 | A1 |
| 20110295270 | Giordano et al. | Dec 2011 | A1 |
| 20110306840 | Allen et al. | Dec 2011 | A1 |
| 20110307284 | Thompson et al. | Dec 2011 | A1 |
| 20120012638 | Huang et al. | Jan 2012 | A1 |
| 20120021684 | Schultz et al. | Jan 2012 | A1 |
| 20120022519 | Huang et al. | Jan 2012 | A1 |
| 20120029354 | Mark et al. | Feb 2012 | A1 |
| 20120046662 | Gilbert | Feb 2012 | A1 |
| 20120059684 | Hampapur | Mar 2012 | A1 |
| 20120078247 | Worrell et al. | Mar 2012 | A1 |
| 20120080336 | Shelton, IV et al. | Apr 2012 | A1 |
| 20120080498 | Shelton, IV et al. | Apr 2012 | A1 |
| 20120083786 | Artale et al. | Apr 2012 | A1 |
| 20120100517 | Bowditch et al. | Apr 2012 | A1 |
| 20120101488 | Aldridge et al. | Apr 2012 | A1 |
| 20120116265 | Houser et al. | May 2012 | A1 |
| 20120116381 | Houser et al. | May 2012 | A1 |
| 20120116394 | Timm et al. | May 2012 | A1 |
| 20120130217 | Kauphusman et al. | May 2012 | A1 |
| 20120145714 | Farascioni et al. | Jun 2012 | A1 |
| 20120172696 | Kallback et al. | Jul 2012 | A1 |
| 20120190981 | Harris et al. | Jul 2012 | A1 |
| 20120191091 | Allen | Jul 2012 | A1 |
| 20120191162 | Villa | Jul 2012 | A1 |
| 20120197619 | Namer Yelin et al. | Aug 2012 | A1 |
| 20120203067 | Higgins et al. | Aug 2012 | A1 |
| 20120203143 | Sanai et al. | Aug 2012 | A1 |
| 20120203785 | Awada | Aug 2012 | A1 |
| 20120211542 | Racenet | Aug 2012 | A1 |
| 20120226150 | Balicki et al. | Sep 2012 | A1 |
| 20120232549 | Willyard et al. | Sep 2012 | A1 |
| 20120245958 | Lawrence et al. | Sep 2012 | A1 |
| 20120253329 | Zemlok et al. | Oct 2012 | A1 |
| 20120253847 | Dell'Anno et al. | Oct 2012 | A1 |
| 20120265555 | Cappuzzo et al. | Oct 2012 | A1 |
| 20120292367 | Morgan et al. | Nov 2012 | A1 |
| 20120319859 | Taub et al. | Dec 2012 | A1 |
| 20130001121 | Metzger | Jan 2013 | A1 |
| 20130006241 | Takashino | Jan 2013 | A1 |
| 20130008677 | Huifu | Jan 2013 | A1 |
| 20130024213 | Poon | Jan 2013 | A1 |
| 20130046182 | Hegg et al. | Feb 2013 | A1 |
| 20130046279 | Niklewski et al. | Feb 2013 | A1 |
| 20130046295 | Kerr et al. | Feb 2013 | A1 |
| 20130066647 | Andrie et al. | Mar 2013 | A1 |
| 20130085413 | Tsamir et al. | Apr 2013 | A1 |
| 20130090526 | Suzuki et al. | Apr 2013 | A1 |
| 20130090755 | Kiryu et al. | Apr 2013 | A1 |
| 20130093829 | Rosenblatt et al. | Apr 2013 | A1 |
| 20130096597 | Anand et al. | Apr 2013 | A1 |
| 20130116218 | Kaplan et al. | May 2013 | A1 |
| 20130131845 | Guilleminot | May 2013 | A1 |
| 20130144284 | Behnke, II et al. | Jun 2013 | A1 |
| 20130153635 | Hodgkinson | Jun 2013 | A1 |
| 20130165776 | Blomqvist | Jun 2013 | A1 |
| 20130168435 | Huang et al. | Jul 2013 | A1 |
| 20130178853 | Hyink et al. | Jul 2013 | A1 |
| 20130190755 | Deborski et al. | Jul 2013 | A1 |
| 20130191154 | William R. et al. | Jul 2013 | A1 |
| 20130191647 | Ferrara, Jr. et al. | Jul 2013 | A1 |
| 20130193188 | Shelton, IV et al. | Aug 2013 | A1 |
| 20130196703 | Masoud et al. | Aug 2013 | A1 |
| 20130197531 | Boukhny et al. | Aug 2013 | A1 |
| 20130201356 | Kennedy et al. | Aug 2013 | A1 |
| 20130206813 | Nalagatla | Aug 2013 | A1 |
| 20130214025 | Zemlok et al. | Aug 2013 | A1 |
| 20130253480 | Kimball | Sep 2013 | A1 |
| 20130256373 | Schmid et al. | Oct 2013 | A1 |
| 20130261503 | Sherman et al. | Oct 2013 | A1 |
| 20130267874 | Marcotte et al. | Oct 2013 | A1 |
| 20130268283 | Vann et al. | Oct 2013 | A1 |
| 20130277410 | Fernandez et al. | Oct 2013 | A1 |
| 20130317837 | Ballantyne et al. | Nov 2013 | A1 |
| 20130321425 | Greene et al. | Dec 2013 | A1 |
| 20130325809 | Kim et al. | Dec 2013 | A1 |
| 20130331873 | Ross et al. | Dec 2013 | A1 |
| 20130331875 | Ross et al. | Dec 2013 | A1 |
| 20140001231 | Shelton, IV et al. | Jan 2014 | A1 |
| 20140001234 | Shelton, IV et al. | Jan 2014 | A1 |
| 20140005640 | Shelton, IV et al. | Jan 2014 | A1 |
| 20140006132 | Barker | Jan 2014 | A1 |
| 20140009894 | Yu | Jan 2014 | A1 |
| 20140013565 | MacDonald et al. | Jan 2014 | A1 |
| 20140018788 | Engelman et al. | Jan 2014 | A1 |
| 20140029411 | Nayak et al. | Jan 2014 | A1 |
| 20140033926 | Fassel et al. | Feb 2014 | A1 |
| 20140035762 | Shelton, IV et al. | Feb 2014 | A1 |
| 20140039491 | Bakos et al. | Feb 2014 | A1 |
| 20140058407 | Tsekos et al. | Feb 2014 | A1 |
| 20140066700 | Wilson et al. | Mar 2014 | A1 |
| 20140073893 | Bencini | Mar 2014 | A1 |
| 20140074076 | Gertner | Mar 2014 | A1 |
| 20140081255 | Johnson et al. | Mar 2014 | A1 |
| 20140081659 | Nawana et al. | Mar 2014 | A1 |
| 20140084949 | Smith et al. | Mar 2014 | A1 |
| 20140087999 | Kaplan et al. | Mar 2014 | A1 |
| 20140092089 | Kasuya et al. | Apr 2014 | A1 |
| 20140107697 | Patani et al. | Apr 2014 | A1 |
| 20140108035 | Akbay et al. | Apr 2014 | A1 |
| 20140108983 | William R. et al. | Apr 2014 | A1 |
| 20140117256 | Mueller et al. | May 2014 | A1 |
| 20140121669 | Claus | May 2014 | A1 |
| 20140142963 | Hill et al. | May 2014 | A1 |
| 20140148729 | Schmitz et al. | May 2014 | A1 |
| 20140148803 | Taylor | May 2014 | A1 |
| 20140163359 | Sholev et al. | Jun 2014 | A1 |
| 20140166724 | Schellin et al. | Jun 2014 | A1 |
| 20140171778 | Tsusaka et al. | Jun 2014 | A1 |
| 20140171787 | Garbey et al. | Jun 2014 | A1 |
| 20140176576 | Spencer | Jun 2014 | A1 |
| 20140187856 | Holoien et al. | Jul 2014 | A1 |
| 20140188440 | Donhowe et al. | Jul 2014 | A1 |
| 20140194864 | Martin et al. | Jul 2014 | A1 |
| 20140195052 | Tsusaka et al. | Jul 2014 | A1 |
| 20140204190 | Rosenblatt, III et al. | Jul 2014 | A1 |
| 20140207124 | Aldridge et al. | Jul 2014 | A1 |
| 20140226572 | Thota et al. | Aug 2014 | A1 |
| 20140243799 | Parihar | Aug 2014 | A1 |
| 20140243809 | Gelfand et al. | Aug 2014 | A1 |
| 20140243811 | Reschke et al. | Aug 2014 | A1 |
| 20140246475 | Hall et al. | Sep 2014 | A1 |
| 20140249557 | Koch, Jr. et al. | Sep 2014 | A1 |
| 20140252064 | Mozdzierz et al. | Sep 2014 | A1 |
| 20140263541 | Leimbach et al. | Sep 2014 | A1 |
| 20140263552 | Hall et al. | Sep 2014 | A1 |
| 20140275760 | Lee et al. | Sep 2014 | A1 |
| 20140276748 | Ku et al. | Sep 2014 | A1 |
| 20140276749 | Johnson | Sep 2014 | A1 |
| 20140278219 | Canavan et al. | Sep 2014 | A1 |
| 20140287393 | Kumar et al. | Sep 2014 | A1 |
| 20140296694 | Jaworski | Oct 2014 | A1 |
| 20140303660 | Boyden et al. | Oct 2014 | A1 |
| 20140303990 | Schoenefeld et al. | Oct 2014 | A1 |
| 20140336943 | Pellini et al. | Nov 2014 | A1 |
| 20140337052 | Pellini et al. | Nov 2014 | A1 |
| 20140364691 | Krivopisk et al. | Dec 2014 | A1 |
| 20150006201 | Pait et al. | Jan 2015 | A1 |
| 20150012010 | Adler et al. | Jan 2015 | A1 |
| 20150025549 | Kilroy et al. | Jan 2015 | A1 |
| 20150032150 | Ishida et al. | Jan 2015 | A1 |
| 20150033128 | Curd et al. | Jan 2015 | A1 |
| 20150051452 | Ciaccio | Feb 2015 | A1 |
| 20150051598 | Orszulak et al. | Feb 2015 | A1 |
| 20150051617 | Takemura et al. | Feb 2015 | A1 |
| 20150053737 | Leimbach et al. | Feb 2015 | A1 |
| 20150053743 | Yates et al. | Feb 2015 | A1 |
| 20150053746 | Shelton, IV et al. | Feb 2015 | A1 |
| 20150053749 | Shelton, IV et al. | Feb 2015 | A1 |
| 20150057675 | Akeel et al. | Feb 2015 | A1 |
| 20150062316 | Haraguchi et al. | Mar 2015 | A1 |
| 20150066000 | An et al. | Mar 2015 | A1 |
| 20150070187 | Wiesner et al. | Mar 2015 | A1 |
| 20150073400 | Sverdlik et al. | Mar 2015 | A1 |
| 20150077528 | Awdeh | Mar 2015 | A1 |
| 20150083774 | Measamer et al. | Mar 2015 | A1 |
| 20150099458 | Weisner et al. | Apr 2015 | A1 |
| 20150108198 | Estrella | Apr 2015 | A1 |
| 20150133945 | Dushyant et al. | May 2015 | A1 |
| 20150136833 | Shelton, IV et al. | May 2015 | A1 |
| 20150140982 | Postrel | May 2015 | A1 |
| 20150141980 | Jadhav et al. | May 2015 | A1 |
| 20150142016 | Bolduc et al. | May 2015 | A1 |
| 20150145682 | Harris | May 2015 | A1 |
| 20150148830 | Stulen et al. | May 2015 | A1 |
| 20150157354 | Bales, Jr. et al. | Jun 2015 | A1 |
| 20150168126 | Nevet et al. | Jun 2015 | A1 |
| 20150173673 | Toth et al. | Jun 2015 | A1 |
| 20150173756 | Baxter, III et al. | Jun 2015 | A1 |
| 20150182220 | Yates et al. | Jul 2015 | A1 |
| 20150196295 | Shelton, IV et al. | Jul 2015 | A1 |
| 20150199109 | Lee | Jul 2015 | A1 |
| 20150201918 | Kumar et al. | Jul 2015 | A1 |
| 20150202014 | Kim et al. | Jul 2015 | A1 |
| 20150208934 | Sztrubel et al. | Jul 2015 | A1 |
| 20150223725 | Engel et al. | Aug 2015 | A1 |
| 20150223868 | Brandt et al. | Aug 2015 | A1 |
| 20150237502 | Schmidt et al. | Aug 2015 | A1 |
| 20150238118 | Legassey et al. | Aug 2015 | A1 |
| 20150257783 | Levine et al. | Sep 2015 | A1 |
| 20150272557 | Overmyer et al. | Oct 2015 | A1 |
| 20150272571 | Leimbach et al. | Oct 2015 | A1 |
| 20150272580 | Leimbach et al. | Oct 2015 | A1 |
| 20150272582 | Leimbach et al. | Oct 2015 | A1 |
| 20150272694 | Charles | Oct 2015 | A1 |
| 20150282733 | Fielden et al. | Oct 2015 | A1 |
| 20150282796 | Nawana et al. | Oct 2015 | A1 |
| 20150282821 | Look et al. | Oct 2015 | A1 |
| 20150286787 | Chen et al. | Oct 2015 | A1 |
| 20150289820 | Miller et al. | Oct 2015 | A1 |
| 20150289925 | Voegele et al. | Oct 2015 | A1 |
| 20150296042 | Aoyama | Oct 2015 | A1 |
| 20150297200 | Fitzsimmons et al. | Oct 2015 | A1 |
| 20150297222 | Huitema et al. | Oct 2015 | A1 |
| 20150297311 | Tesar | Oct 2015 | A1 |
| 20150302157 | Collar et al. | Oct 2015 | A1 |
| 20150305828 | Park et al. | Oct 2015 | A1 |
| 20150310174 | Coudert et al. | Oct 2015 | A1 |
| 20150313538 | Bechtel et al. | Nov 2015 | A1 |
| 20150317899 | Dumbauld et al. | Nov 2015 | A1 |
| 20150320423 | Aranyi | Nov 2015 | A1 |
| 20150324114 | Hurley et al. | Nov 2015 | A1 |
| 20150328474 | Flyash et al. | Nov 2015 | A1 |
| 20150331995 | Zhao et al. | Nov 2015 | A1 |
| 20150332003 | Stamm et al. | Nov 2015 | A1 |
| 20150332196 | Stiller et al. | Nov 2015 | A1 |
| 20150335344 | Aljuri et al. | Nov 2015 | A1 |
| 20150374259 | Garbey et al. | Dec 2015 | A1 |
| 20160000437 | Giordano et al. | Jan 2016 | A1 |
| 20160001411 | Alberti | Jan 2016 | A1 |
| 20160005169 | Sela et al. | Jan 2016 | A1 |
| 20160015471 | Piron et al. | Jan 2016 | A1 |
| 20160019346 | Boston et al. | Jan 2016 | A1 |
| 20160022374 | Haider et al. | Jan 2016 | A1 |
| 20160034648 | Mohlenbrock et al. | Feb 2016 | A1 |
| 20160038224 | Couture et al. | Feb 2016 | A1 |
| 20160038253 | Piron et al. | Feb 2016 | A1 |
| 20160048780 | Sethumadhavan et al. | Feb 2016 | A1 |
| 20160051315 | Boudreaux | Feb 2016 | A1 |
| 20160058439 | Shelton, IV et al. | Mar 2016 | A1 |
| 20160066913 | Swayze et al. | Mar 2016 | A1 |
| 20160100837 | Huang et al. | Apr 2016 | A1 |
| 20160103810 | Hanning | Apr 2016 | A1 |
| 20160106516 | Mesallum | Apr 2016 | A1 |
| 20160106934 | Hiraga et al. | Apr 2016 | A1 |
| 20160121143 | Mumaw et al. | May 2016 | A1 |
| 20160143659 | Glutz et al. | May 2016 | A1 |
| 20160143693 | Yilmaz et al. | May 2016 | A1 |
| 20160157717 | Gaster | Jun 2016 | A1 |
| 20160158468 | Tang et al. | Jun 2016 | A1 |
| 20160166336 | Razzaque et al. | Jun 2016 | A1 |
| 20160174998 | Lal et al. | Jun 2016 | A1 |
| 20160175025 | Strobl | Jun 2016 | A1 |
| 20160180045 | Syed | Jun 2016 | A1 |
| 20160182637 | Adriaens et al. | Jun 2016 | A1 |
| 20160184054 | Lowe | Jun 2016 | A1 |
| 20160184469 | Welch et al. | Jun 2016 | A1 |
| 20160192960 | Bueno et al. | Jul 2016 | A1 |
| 20160192999 | Stulen et al. | Jul 2016 | A1 |
| 20160203599 | Gillies et al. | Jul 2016 | A1 |
| 20160206202 | Frangioni | Jul 2016 | A1 |
| 20160206362 | Mehta et al. | Jul 2016 | A1 |
| 20160224760 | Petak et al. | Aug 2016 | A1 |
| 20160225551 | Shedletsky | Aug 2016 | A1 |
| 20160228061 | Kallback et al. | Aug 2016 | A1 |
| 20160228204 | Quaid et al. | Aug 2016 | A1 |
| 20160235303 | Fleming et al. | Aug 2016 | A1 |
| 20160242836 | Eggers et al. | Aug 2016 | A1 |
| 20160249910 | Shelton, IV et al. | Sep 2016 | A1 |
| 20160249920 | Gupta et al. | Sep 2016 | A1 |
| 20160270732 | Källbäck et al. | Sep 2016 | A1 |
| 20160270842 | Strobl et al. | Sep 2016 | A1 |
| 20160270861 | Guru et al. | Sep 2016 | A1 |
| 20160275259 | Nolan et al. | Sep 2016 | A1 |
| 20160278841 | Panescu et al. | Sep 2016 | A1 |
| 20160287312 | Tegg et al. | Oct 2016 | A1 |
| 20160287316 | Worrell et al. | Oct 2016 | A1 |
| 20160287337 | Aram et al. | Oct 2016 | A1 |
| 20160287912 | Warnking | Oct 2016 | A1 |
| 20160292456 | Dubey et al. | Oct 2016 | A1 |
| 20160296246 | Schaller | Oct 2016 | A1 |
| 20160302210 | Thornton et al. | Oct 2016 | A1 |
| 20160310055 | Zand et al. | Oct 2016 | A1 |
| 20160310204 | McHenry et al. | Oct 2016 | A1 |
| 20160314716 | Grubbs | Oct 2016 | A1 |
| 20160314717 | Grubbs | Oct 2016 | A1 |
| 20160317172 | Kumada et al. | Nov 2016 | A1 |
| 20160321400 | Durrant et al. | Nov 2016 | A1 |
| 20160323283 | Kang et al. | Nov 2016 | A1 |
| 20160331460 | Cheatham, III et al. | Nov 2016 | A1 |
| 20160331473 | Yamamura | Nov 2016 | A1 |
| 20160338685 | Nawana et al. | Nov 2016 | A1 |
| 20160342753 | Feazell | Nov 2016 | A1 |
| 20160342916 | Arceneaux et al. | Nov 2016 | A1 |
| 20160345857 | Jensrud et al. | Dec 2016 | A1 |
| 20160350490 | Martinez et al. | Dec 2016 | A1 |
| 20160354155 | Hodges et al. | Dec 2016 | A1 |
| 20160354160 | Crowley et al. | Dec 2016 | A1 |
| 20160354162 | Yen et al. | Dec 2016 | A1 |
| 20160356852 | Lee | Dec 2016 | A1 |
| 20160361070 | Ardel et al. | Dec 2016 | A1 |
| 20160367305 | Hareland | Dec 2016 | A1 |
| 20160367401 | Claus | Dec 2016 | A1 |
| 20160374710 | Sinelnikov et al. | Dec 2016 | A1 |
| 20160374723 | Frankhouser et al. | Dec 2016 | A1 |
| 20160374762 | Case et al. | Dec 2016 | A1 |
| 20160379504 | Bailey et al. | Dec 2016 | A1 |
| 20170005911 | Kasargod et al. | Jan 2017 | A1 |
| 20170007247 | Shelton, IV et al. | Jan 2017 | A1 |
| 20170027603 | Pandey | Feb 2017 | A1 |
| 20170042604 | McFarland et al. | Feb 2017 | A1 |
| 20170049522 | Kapadia | Feb 2017 | A1 |
| 20170056038 | Hess et al. | Mar 2017 | A1 |
| 20170068792 | Reiner | Mar 2017 | A1 |
| 20170079530 | DiMaio et al. | Mar 2017 | A1 |
| 20170079730 | Azizian et al. | Mar 2017 | A1 |
| 20170086829 | Vendely et al. | Mar 2017 | A1 |
| 20170086906 | Tsuruta | Mar 2017 | A1 |
| 20170086930 | Thompson et al. | Mar 2017 | A1 |
| 20170105754 | Boudreaux et al. | Apr 2017 | A1 |
| 20170105787 | Witt et al. | Apr 2017 | A1 |
| 20170116873 | Lendvay et al. | Apr 2017 | A1 |
| 20170119477 | Amiot et al. | May 2017 | A1 |
| 20170127499 | Unoson et al. | May 2017 | A1 |
| 20170132374 | Lee et al. | May 2017 | A1 |
| 20170132385 | Hunter et al. | May 2017 | A1 |
| 20170132785 | Wshah et al. | May 2017 | A1 |
| 20170143284 | Sehnert et al. | May 2017 | A1 |
| 20170143366 | Groene et al. | May 2017 | A1 |
| 20170147759 | Iyer et al. | May 2017 | A1 |
| 20170154156 | Sevenster et al. | Jun 2017 | A1 |
| 20170161443 | Bassham et al. | Jun 2017 | A1 |
| 20170164996 | Honda et al. | Jun 2017 | A1 |
| 20170164997 | Johnson et al. | Jun 2017 | A1 |
| 20170165008 | Finley | Jun 2017 | A1 |
| 20170165012 | Chaplin et al. | Jun 2017 | A1 |
| 20170172550 | Mukherjee et al. | Jun 2017 | A1 |
| 20170172565 | Heneveld | Jun 2017 | A1 |
| 20170172614 | Scheib et al. | Jun 2017 | A1 |
| 20170172674 | Hanuschik et al. | Jun 2017 | A1 |
| 20170172676 | Itkowitz et al. | Jun 2017 | A1 |
| 20170173262 | Veltz | Jun 2017 | A1 |
| 20170177807 | Fabian | Jun 2017 | A1 |
| 20170178069 | Paterra et al. | Jun 2017 | A1 |
| 20170185732 | Niklewski et al. | Jun 2017 | A1 |
| 20170196583 | Sugiyama | Jul 2017 | A1 |
| 20170202305 | Huard et al. | Jul 2017 | A1 |
| 20170202595 | Shelton, IV | Jul 2017 | A1 |
| 20170202608 | Shelton, IV et al. | Jul 2017 | A1 |
| 20170209145 | Swayze et al. | Jul 2017 | A1 |
| 20170215944 | Keffeler | Aug 2017 | A1 |
| 20170224332 | Hunter et al. | Aug 2017 | A1 |
| 20170224428 | Kopp | Aug 2017 | A1 |
| 20170231553 | Igarashi et al. | Aug 2017 | A1 |
| 20170231628 | Shelton, IV et al. | Aug 2017 | A1 |
| 20170235897 | Henderson et al. | Aug 2017 | A1 |
| 20170245809 | Ma et al. | Aug 2017 | A1 |
| 20170249431 | Shelton, IV et al. | Aug 2017 | A1 |
| 20170249432 | Grantcharov | Aug 2017 | A1 |
| 20170254013 | Pratt et al. | Sep 2017 | A1 |
| 20170262604 | Francois | Sep 2017 | A1 |
| 20170265864 | Hessler et al. | Sep 2017 | A1 |
| 20170265943 | Sela et al. | Sep 2017 | A1 |
| 20170270323 | Butler et al. | Sep 2017 | A1 |
| 20170273715 | Piron et al. | Sep 2017 | A1 |
| 20170281186 | Shelton, IV et al. | Oct 2017 | A1 |
| 20170289617 | Song et al. | Oct 2017 | A1 |
| 20170296173 | Shelton, IV et al. | Oct 2017 | A1 |
| 20170296301 | Dor et al. | Oct 2017 | A1 |
| 20170303984 | Malackowski | Oct 2017 | A1 |
| 20170304007 | Piron et al. | Oct 2017 | A1 |
| 20170304020 | Ng et al. | Oct 2017 | A1 |
| 20170311777 | Hirayama et al. | Nov 2017 | A1 |
| 20170312456 | Phillips | Nov 2017 | A1 |
| 20170319268 | Akagane | Nov 2017 | A1 |
| 20170325876 | Nakadate et al. | Nov 2017 | A1 |
| 20170325878 | Messerly et al. | Nov 2017 | A1 |
| 20170333147 | Bernstein | Nov 2017 | A1 |
| 20170333152 | Wade | Nov 2017 | A1 |
| 20170337043 | Brincat et al. | Nov 2017 | A1 |
| 20170337493 | Paramasivan et al. | Nov 2017 | A1 |
| 20170348047 | Reiter et al. | Dec 2017 | A1 |
| 20170360358 | Amiot et al. | Dec 2017 | A1 |
| 20170360499 | Greep et al. | Dec 2017 | A1 |
| 20170367583 | Black et al. | Dec 2017 | A1 |
| 20170367754 | Narisawa | Dec 2017 | A1 |
| 20170367771 | Tako et al. | Dec 2017 | A1 |
| 20170367772 | Gunn et al. | Dec 2017 | A1 |
| 20170370710 | Chen et al. | Dec 2017 | A1 |
| 20180008359 | Randle | Jan 2018 | A1 |
| 20180011983 | Zuhars et al. | Jan 2018 | A1 |
| 20180014764 | Bechtel et al. | Jan 2018 | A1 |
| 20180021058 | Meglan | Jan 2018 | A1 |
| 20180028088 | Garbey et al. | Feb 2018 | A1 |
| 20180042659 | Rupp et al. | Feb 2018 | A1 |
| 20180050196 | Pawsey et al. | Feb 2018 | A1 |
| 20180052971 | Hanina et al. | Feb 2018 | A1 |
| 20180056496 | Rubens et al. | Mar 2018 | A1 |
| 20180065248 | Barral et al. | Mar 2018 | A1 |
| 20180078170 | Panescu et al. | Mar 2018 | A1 |
| 20180082480 | White et al. | Mar 2018 | A1 |
| 20180085102 | Kikuchi | Mar 2018 | A1 |
| 20180098049 | Sugano et al. | Apr 2018 | A1 |
| 20180098816 | Govari et al. | Apr 2018 | A1 |
| 20180108438 | Ryan et al. | Apr 2018 | A1 |
| 20180110398 | Schwartz et al. | Apr 2018 | A1 |
| 20180116735 | Tierney et al. | May 2018 | A1 |
| 20180122506 | Grantcharov et al. | May 2018 | A1 |
| 20180132895 | Silver | May 2018 | A1 |
| 20180144243 | Hsieh et al. | May 2018 | A1 |
| 20180144314 | Miller | May 2018 | A1 |
| 20180153436 | Olson | Jun 2018 | A1 |
| 20180153574 | Faller et al. | Jun 2018 | A1 |
| 20180153632 | Tokarchuk et al. | Jun 2018 | A1 |
| 20180154297 | Maletich et al. | Jun 2018 | A1 |
| 20180161062 | Kaga et al. | Jun 2018 | A1 |
| 20180161716 | Li et al. | Jun 2018 | A1 |
| 20180165780 | Romeo | Jun 2018 | A1 |
| 20180168574 | Robinson et al. | Jun 2018 | A1 |
| 20180168575 | Simms et al. | Jun 2018 | A1 |
| 20180168577 | Aronhalt et al. | Jun 2018 | A1 |
| 20180168579 | Aronhalt et al. | Jun 2018 | A1 |
| 20180168598 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168608 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168609 | Fanelli et al. | Jun 2018 | A1 |
| 20180168615 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168618 | Scott et al. | Jun 2018 | A1 |
| 20180168619 | Scott et al. | Jun 2018 | A1 |
| 20180168623 | Simms et al. | Jun 2018 | A1 |
| 20180168625 | Posada et al. | Jun 2018 | A1 |
| 20180168633 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168647 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168648 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168650 | Shelton, IV et al. | Jun 2018 | A1 |
| 20180168739 | Alikhani et al. | Jun 2018 | A1 |
| 20180172420 | Hein et al. | Jun 2018 | A1 |
| 20180177383 | Noonan et al. | Jun 2018 | A1 |
| 20180182475 | Cossler et al. | Jun 2018 | A1 |
| 20180183684 | Jacobson et al. | Jun 2018 | A1 |
| 20180193579 | Hanrahan et al. | Jul 2018 | A1 |
| 20180206884 | Beaupre | Jul 2018 | A1 |
| 20180206905 | Batchelor et al. | Jul 2018 | A1 |
| 20180211726 | Courtemanche et al. | Jul 2018 | A1 |
| 20180214025 | Homyk et al. | Aug 2018 | A1 |
| 20180221005 | Hamel et al. | Aug 2018 | A1 |
| 20180221598 | Silver | Aug 2018 | A1 |
| 20180228557 | Darisse et al. | Aug 2018 | A1 |
| 20180233222 | Daley et al. | Aug 2018 | A1 |
| 20180233235 | Angelides | Aug 2018 | A1 |
| 20180235719 | Jarc | Aug 2018 | A1 |
| 20180235722 | Baghdadi et al. | Aug 2018 | A1 |
| 20180242967 | Meade | Aug 2018 | A1 |
| 20180247128 | Alvi et al. | Aug 2018 | A1 |
| 20180247711 | Terry | Aug 2018 | A1 |
| 20180250086 | Grubbs | Sep 2018 | A1 |
| 20180250825 | Hashimoto et al. | Sep 2018 | A1 |
| 20180263699 | Murphy et al. | Sep 2018 | A1 |
| 20180263710 | Sakaguchi et al. | Sep 2018 | A1 |
| 20180268320 | Shekhar | Sep 2018 | A1 |
| 20180271603 | Nir et al. | Sep 2018 | A1 |
| 20180289427 | Griffiths et al. | Oct 2018 | A1 |
| 20180294060 | Kassab | Oct 2018 | A1 |
| 20180296286 | Peine et al. | Oct 2018 | A1 |
| 20180296289 | Rodriguez-Navarro et al. | Oct 2018 | A1 |
| 20180300506 | Kawakami et al. | Oct 2018 | A1 |
| 20180303552 | Ryan et al. | Oct 2018 | A1 |
| 20180304471 | Tokuchi | Oct 2018 | A1 |
| 20180310986 | Batchelor et al. | Nov 2018 | A1 |
| 20180315492 | Bishop et al. | Nov 2018 | A1 |
| 20180317916 | Wixey | Nov 2018 | A1 |
| 20180325619 | Rauniyar et al. | Nov 2018 | A1 |
| 20180333188 | Nott et al. | Nov 2018 | A1 |
| 20180333207 | Moctezuma De la Barrera | Nov 2018 | A1 |
| 20180333209 | Frushour et al. | Nov 2018 | A1 |
| 20180345501 | Jumis et al. | Dec 2018 | A1 |
| 20180349721 | Agrawal et al. | Dec 2018 | A1 |
| 20180353186 | Mozdzierz et al. | Dec 2018 | A1 |
| 20180357383 | Allen et al. | Dec 2018 | A1 |
| 20180360456 | Shelton, IV et al. | Dec 2018 | A1 |
| 20180366213 | Fidone et al. | Dec 2018 | A1 |
| 20180368930 | Esterberg et al. | Dec 2018 | A1 |
| 20190000569 | Crawford et al. | Jan 2019 | A1 |
| 20190001079 | Zergiebel et al. | Jan 2019 | A1 |
| 20190005641 | Yamamoto | Jan 2019 | A1 |
| 20190006047 | Gorek et al. | Jan 2019 | A1 |
| 20190025040 | Andreason et al. | Jan 2019 | A1 |
| 20190036688 | Wasily et al. | Jan 2019 | A1 |
| 20190038335 | Mohr et al. | Feb 2019 | A1 |
| 20190038364 | Enoki | Feb 2019 | A1 |
| 20190045515 | Kwasnick et al. | Feb 2019 | A1 |
| 20190046198 | Stokes et al. | Feb 2019 | A1 |
| 20190053801 | Wixey et al. | Feb 2019 | A1 |
| 20190053866 | Seow et al. | Feb 2019 | A1 |
| 20190059986 | Shelton, IV et al. | Feb 2019 | A1 |
| 20190059997 | Frushour | Feb 2019 | A1 |
| 20190069949 | Vrba et al. | Mar 2019 | A1 |
| 20190069964 | Hagn | Mar 2019 | A1 |
| 20190069966 | Petersen et al. | Mar 2019 | A1 |
| 20190070550 | Lalomia et al. | Mar 2019 | A1 |
| 20190070731 | Bowling et al. | Mar 2019 | A1 |
| 20190083190 | Graves et al. | Mar 2019 | A1 |
| 20190083809 | Zhang | Mar 2019 | A1 |
| 20190087544 | Peterson | Mar 2019 | A1 |
| 20190099221 | Schmidt et al. | Apr 2019 | A1 |
| 20190099226 | Hallen | Apr 2019 | A1 |
| 20190104919 | Shelton, IV et al. | Apr 2019 | A1 |
| 20190105468 | Kato et al. | Apr 2019 | A1 |
| 20190110828 | Despatie | Apr 2019 | A1 |
| 20190110855 | Barral et al. | Apr 2019 | A1 |
| 20190110856 | Barral et al. | Apr 2019 | A1 |
| 20190115108 | Hegedus et al. | Apr 2019 | A1 |
| 20190122330 | Saget et al. | Apr 2019 | A1 |
| 20190125320 | Shelton, IV et al. | May 2019 | A1 |
| 20190125336 | Deck et al. | May 2019 | A1 |
| 20190125361 | Shelton, IV et al. | May 2019 | A1 |
| 20190125432 | Shelton, IV et al. | May 2019 | A1 |
| 20190125476 | Shelton, IV et al. | May 2019 | A1 |
| 20190133703 | Seow et al. | May 2019 | A1 |
| 20190142535 | Seow et al. | May 2019 | A1 |
| 20190145942 | Dutriez et al. | May 2019 | A1 |
| 20190150975 | Kawasaki et al. | May 2019 | A1 |
| 20190163875 | Allen et al. | May 2019 | A1 |
| 20190167296 | Tsubuku et al. | Jun 2019 | A1 |
| 20190192044 | Ravi et al. | Jun 2019 | A1 |
| 20190200844 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200905 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200906 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200977 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200980 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200981 | Harris et al. | Jul 2019 | A1 |
| 20190200987 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190200997 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201021 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201024 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201027 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201029 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201030 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201034 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201039 | Widenhouse et al. | Jul 2019 | A1 |
| 20190201042 | Nott et al. | Jul 2019 | A1 |
| 20190201045 | Yates et al. | Jul 2019 | A1 |
| 20190201076 | Honda et al. | Jul 2019 | A1 |
| 20190201087 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201090 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201102 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201104 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201112 | Wiener et al. | Jul 2019 | A1 |
| 20190201113 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201115 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201118 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201128 | Yates et al. | Jul 2019 | A1 |
| 20190201130 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201139 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201140 | Yates et al. | Jul 2019 | A1 |
| 20190201142 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201146 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201158 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190201594 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190205567 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206555 | Morgan et al. | Jul 2019 | A1 |
| 20190206561 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206564 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190206569 | Shelton, IV et al. | Jul 2019 | A1 |
| 20190216452 | Nawana et al. | Jul 2019 | A1 |
| 20190224434 | Silver et al. | Jul 2019 | A1 |
| 20190254759 | Azizian | Aug 2019 | A1 |
| 20190261984 | Nelson et al. | Aug 2019 | A1 |
| 20190269476 | Bowling et al. | Sep 2019 | A1 |
| 20190272917 | Couture et al. | Sep 2019 | A1 |
| 20190274662 | Rockman et al. | Sep 2019 | A1 |
| 20190278262 | Taylor et al. | Sep 2019 | A1 |
| 20190282311 | Nowlin et al. | Sep 2019 | A1 |
| 20190290389 | Kopp | Sep 2019 | A1 |
| 20190298353 | Shelton, IV et al. | Oct 2019 | A1 |
| 20190298464 | Abbott | Oct 2019 | A1 |
| 20190307520 | Peine et al. | Oct 2019 | A1 |
| 20190311802 | Kokubo et al. | Oct 2019 | A1 |
| 20190314081 | Brogna | Oct 2019 | A1 |
| 20190320929 | Spencer et al. | Oct 2019 | A1 |
| 20190321117 | Itkowitz et al. | Oct 2019 | A1 |
| 20190325386 | Laster et al. | Oct 2019 | A1 |
| 20190333626 | Mansi et al. | Oct 2019 | A1 |
| 20190343594 | Garcia Kilroy et al. | Nov 2019 | A1 |
| 20190365569 | Skovgaard et al. | Dec 2019 | A1 |
| 20190374140 | Tucker et al. | Dec 2019 | A1 |
| 20190374292 | Barral et al. | Dec 2019 | A1 |
| 20190378610 | Barral et al. | Dec 2019 | A1 |
| 20200000470 | Du et al. | Jan 2020 | A1 |
| 20200000509 | Hayashida et al. | Jan 2020 | A1 |
| 20200022687 | Takemoto et al. | Jan 2020 | A1 |
| 20200038120 | Ziraknejad et al. | Feb 2020 | A1 |
| 20200046353 | Deck et al. | Feb 2020 | A1 |
| 20200054317 | Pisarnwongs et al. | Feb 2020 | A1 |
| 20200054321 | Harris et al. | Feb 2020 | A1 |
| 20200078071 | Asher | Mar 2020 | A1 |
| 20200078080 | Henderson et al. | Mar 2020 | A1 |
| 20200078089 | Henderson et al. | Mar 2020 | A1 |
| 20200078096 | Barbagli et al. | Mar 2020 | A1 |
| 20200078113 | Sawhney et al. | Mar 2020 | A1 |
| 20200078114 | Asher et al. | Mar 2020 | A1 |
| 20200078115 | Asher et al. | Mar 2020 | A1 |
| 20200078117 | Henderson et al. | Mar 2020 | A1 |
| 20200078118 | Henderson et al. | Mar 2020 | A1 |
| 20200078119 | Henderson et al. | Mar 2020 | A1 |
| 20200078120 | Aldridge et al. | Mar 2020 | A1 |
| 20200090808 | Carroll et al. | Mar 2020 | A1 |
| 20200100825 | Henderson et al. | Apr 2020 | A1 |
| 20200162896 | Su et al. | May 2020 | A1 |
| 20200168323 | Bullington et al. | May 2020 | A1 |
| 20200178760 | Kashima et al. | Jun 2020 | A1 |
| 20200193600 | Shameli et al. | Jun 2020 | A1 |
| 20200197027 | Hershberger et al. | Jun 2020 | A1 |
| 20200203004 | Shanbhag et al. | Jun 2020 | A1 |
| 20200214699 | Shelton, IV et al. | Jul 2020 | A1 |
| 20200222079 | Swaney et al. | Jul 2020 | A1 |
| 20200222149 | Valentine et al. | Jul 2020 | A1 |
| 20200226751 | Jin et al. | Jul 2020 | A1 |
| 20200230803 | Yamashita et al. | Jul 2020 | A1 |
| 20200237372 | Park | Jul 2020 | A1 |
| 20200237452 | Wolf et al. | Jul 2020 | A1 |
| 20200273581 | Wolf et al. | Aug 2020 | A1 |
| 20200281665 | Kopp | Sep 2020 | A1 |
| 20200305924 | Carroll | Oct 2020 | A1 |
| 20200348662 | Cella et al. | Nov 2020 | A1 |
| 20200352664 | King et al. | Nov 2020 | A1 |
| 20200388385 | De Los Reyes et al. | Dec 2020 | A1 |
| 20200405304 | Mozdzierz et al. | Dec 2020 | A1 |
| 20210007760 | Reisin | Jan 2021 | A1 |
| 20210015568 | Liao et al. | Jan 2021 | A1 |
| 20210022731 | Eisinger | Jan 2021 | A1 |
| 20210022738 | Weir et al. | Jan 2021 | A1 |
| 20210022809 | Crawford et al. | Jan 2021 | A1 |
| 20210059674 | Shelton, IV et al. | Mar 2021 | A1 |
| 20210076966 | Grantcharov et al. | Mar 2021 | A1 |
| 20210128149 | Whitfield et al. | May 2021 | A1 |
| 20210153889 | Nott et al. | May 2021 | A1 |
| 20210169516 | Houser et al. | Jun 2021 | A1 |
| 20210177452 | Nott et al. | Jun 2021 | A1 |
| 20210177489 | Yates et al. | Jun 2021 | A1 |
| 20210186454 | Behzadi et al. | Jun 2021 | A1 |
| 20210192914 | Shelton, IV et al. | Jun 2021 | A1 |
| 20210201646 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205020 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205021 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205028 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205029 | Wiener et al. | Jul 2021 | A1 |
| 20210205030 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210205031 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212602 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212694 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212717 | Yates et al. | Jul 2021 | A1 |
| 20210212719 | Houser et al. | Jul 2021 | A1 |
| 20210212770 | Messerly et al. | Jul 2021 | A1 |
| 20210212771 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210212775 | Shelton, IV et al. | Jul 2021 | A1 |
| 20210220058 | Messerly et al. | Jul 2021 | A1 |
| 20210241898 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210249125 | Morgan et al. | Aug 2021 | A1 |
| 20210259687 | Gonzalez et al. | Aug 2021 | A1 |
| 20210259697 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210259698 | Shelton, IV et al. | Aug 2021 | A1 |
| 20210282780 | Shelton, IV et al. | Sep 2021 | A1 |
| 20210282781 | Shelton, IV et al. | Sep 2021 | A1 |
| 20210306176 | Park et al. | Sep 2021 | A1 |
| 20210315579 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210315580 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210315581 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210315582 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322014 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322015 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322017 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322018 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322019 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210322020 | Shelton, IV et al. | Oct 2021 | A1 |
| 20210336939 | Wiener et al. | Oct 2021 | A1 |
| 20210353287 | Shelton, IV et al. | Nov 2021 | A1 |
| 20210353288 | Shelton, IV et al. | Nov 2021 | A1 |
| 20210358599 | Alvi et al. | Nov 2021 | A1 |
| 20210361284 | Shelton, IV et al. | Nov 2021 | A1 |
| 20220000484 | Shelton, IV et al. | Jan 2022 | A1 |
| 20220054158 | Shelton, IV et al. | Feb 2022 | A1 |
| 20220061836 | Parihar et al. | Mar 2022 | A1 |
| 20220079591 | Bakos et al. | Mar 2022 | A1 |
| 20220104880 | Frushour | Apr 2022 | A1 |
| 20220157306 | Albrecht et al. | May 2022 | A1 |
| 20220175374 | Shelton, IV et al. | Jun 2022 | A1 |
| 20220241027 | Shelton, IV et al. | Aug 2022 | A1 |
| 20220323092 | Shelton, IV et al. | Oct 2022 | A1 |
| 20220323150 | Yates et al. | Oct 2022 | A1 |
| 20220331011 | Shelton, IV et al. | Oct 2022 | A1 |
| 20220331018 | Parihar et al. | Oct 2022 | A1 |
| 20220346792 | Shelton, IV et al. | Nov 2022 | A1 |
| 20220370117 | Messerly et al. | Nov 2022 | A1 |
| 20220370126 | Shelton, IV et al. | Nov 2022 | A1 |
| 20220374414 | Shelton, IV et al. | Nov 2022 | A1 |
| 20220395276 | Yates et al. | Dec 2022 | A1 |
| 20220401099 | Shelton, IV et al. | Dec 2022 | A1 |
| 20220406452 | Shelton, IV | Dec 2022 | A1 |
| 20220409302 | Shelton, IV et al. | Dec 2022 | A1 |
| 20230000518 | Nott et al. | Jan 2023 | A1 |
| 20230037577 | Kimball et al. | Feb 2023 | A1 |
| 20230064821 | Shelton, IV | Mar 2023 | A1 |
| 20230092371 | Yates et al. | Mar 2023 | A1 |
| 20230098870 | Harris et al. | Mar 2023 | A1 |
| 20230116571 | Shelton, IV et al. | Apr 2023 | A1 |
| 20230146947 | Shelton, IV et al. | May 2023 | A1 |
| 20230165642 | Shelton, IV et al. | Jun 2023 | A1 |
| 20230171266 | Brunner et al. | Jun 2023 | A1 |
| 20230171304 | Shelton, IV et al. | Jun 2023 | A1 |
| 20230187060 | Morgan et al. | Jun 2023 | A1 |
| 20230190390 | Shelton, IV et al. | Jun 2023 | A1 |
| 20230200889 | Shelton, IV et al. | Jun 2023 | A1 |
| 20230210611 | Shelton, IV et al. | Jul 2023 | A1 |
| 20230233245 | Nott et al. | Jul 2023 | A1 |
| 20230263548 | Shelton, IV et al. | Aug 2023 | A1 |
| 20230320792 | Shelton, IV et al. | Oct 2023 | A1 |
| 20230355265 | Nott et al. | Nov 2023 | A1 |
| Number | Date | Country |
|---|---|---|
| 2015201140 | Mar 2015 | AU |
| 2709634 | Jul 2009 | CA |
| 2795323 | May 2014 | CA |
| 101617950 | Jan 2010 | CN |
| 106027664 | Oct 2016 | CN |
| 106413578 | Feb 2017 | CN |
| 106456169 | Feb 2017 | CN |
| 104490448 | Mar 2017 | CN |
| 206097107 | Apr 2017 | CN |
| 106777916 | May 2017 | CN |
| 107811710 | Mar 2018 | CN |
| 108652695 | Oct 2018 | CN |
| 3016131 | Oct 1981 | DE |
| 3824913 | Feb 1990 | DE |
| 4002843 | Apr 1991 | DE |
| 102005051367 | Apr 2007 | DE |
| 102016207666 | Nov 2017 | DE |
| 0000756 | Oct 1981 | EP |
| 0408160 | Jan 1991 | EP |
| 0473987 | Mar 1992 | EP |
| 0929263 | Jul 1999 | EP |
| 1214913 | Jun 2002 | EP |
| 2730209 | May 2014 | EP |
| 2732772 | May 2014 | EP |
| 2942023 | Nov 2015 | EP |
| 3047806 | Jul 2016 | EP |
| 3056923 | Aug 2016 | EP |
| 3095399 | Nov 2016 | EP |
| 3120781 | Jan 2017 | EP |
| 3135225 | Mar 2017 | EP |
| 3141181 | Mar 2017 | EP |
| 2838234 | Oct 2003 | FR |
| 2037167 | Jul 1980 | GB |
| 2509523 | Jul 2014 | GB |
| S5191993 | Jul 1976 | JP |
| S5373315 | Jun 1978 | JP |
| S57185848 | Nov 1982 | JP |
| S58207752 | Dec 1983 | JP |
| S63315049 | Dec 1988 | JP |
| H06142113 | May 1994 | JP |
| H06178780 | Jun 1994 | JP |
| H06209902 | Aug 1994 | JP |
| H07132122 | May 1995 | JP |
| H08071072 | Mar 1996 | JP |
| H08332169 | Dec 1996 | JP |
| H0928663 | Feb 1997 | JP |
| H09154850 | Jun 1997 | JP |
| H11151247 | Jun 1999 | JP |
| H11197159 | Jul 1999 | JP |
| H11309156 | Nov 1999 | JP |
| 2000058355 | Feb 2000 | JP |
| 2001029353 | Feb 2001 | JP |
| 2001195686 | Jul 2001 | JP |
| 2001314411 | Nov 2001 | JP |
| 2001340350 | Dec 2001 | JP |
| 2002272758 | Sep 2002 | JP |
| 2003061975 | Mar 2003 | JP |
| 2003070921 | Mar 2003 | JP |
| 2003153918 | May 2003 | JP |
| 2004118664 | Apr 2004 | JP |
| 2005111080 | Apr 2005 | JP |
| 2005309702 | Nov 2005 | JP |
| 2005348797 | Dec 2005 | JP |
| 2006077626 | Mar 2006 | JP |
| 2006117143 | May 2006 | JP |
| 2006164251 | Jun 2006 | JP |
| 2006280804 | Oct 2006 | JP |
| 2006288431 | Oct 2006 | JP |
| 2007123394 | May 2007 | JP |
| 2007139822 | Jun 2007 | JP |
| 2007300312 | Nov 2007 | JP |
| 2009039515 | Feb 2009 | JP |
| 2010057642 | Mar 2010 | JP |
| 2010131265 | Jun 2010 | JP |
| 2010269067 | Dec 2010 | JP |
| 2012065698 | Apr 2012 | JP |
| 2012239669 | Dec 2012 | JP |
| 2012240158 | Dec 2012 | JP |
| 2012533346 | Dec 2012 | JP |
| 2013044303 | Mar 2013 | JP |
| 2013081282 | May 2013 | JP |
| 2013135738 | Jul 2013 | JP |
| 2013144057 | Jul 2013 | JP |
| 2014155207 | Aug 2014 | JP |
| 2015085454 | May 2015 | JP |
| 2016514017 | May 2016 | JP |
| 2016528010 | Sep 2016 | JP |
| 2016174836 | Oct 2016 | JP |
| 2016214553 | Dec 2016 | JP |
| 2017047022 | Mar 2017 | JP |
| 2017096359 | Jun 2017 | JP |
| 2017513561 | Jun 2017 | JP |
| 2017526510 | Sep 2017 | JP |
| 2017532168 | Nov 2017 | JP |
| 20140104587 | Aug 2014 | KR |
| 101587721 | Jan 2016 | KR |
| 2020860 | Oct 1994 | RU |
| WO-9734533 | Sep 1997 | WO |
| WO-9808449 | Mar 1998 | WO |
| WO-0024322 | May 2000 | WO |
| WO-0108578 | Feb 2001 | WO |
| WO-0112089 | Feb 2001 | WO |
| WO-0120892 | Mar 2001 | WO |
| WO-03079909 | Oct 2003 | WO |
| WO-2006001264 | Jan 2006 | WO |
| WO-2007137304 | Nov 2007 | WO |
| WO-2008053485 | May 2008 | WO |
| WO-2008056618 | May 2008 | WO |
| WO-2008069816 | Jun 2008 | WO |
| WO-2008076079 | Jun 2008 | WO |
| WO-2008147555 | Dec 2008 | WO |
| WO-2011112931 | Sep 2011 | WO |
| WO-2013143573 | Oct 2013 | WO |
| WO-2014031800 | Feb 2014 | WO |
| WO-2014071184 | May 2014 | WO |
| WO-2014116961 | Jul 2014 | WO |
| WO-2014134196 | Sep 2014 | WO |
| WO-2015030157 | Mar 2015 | WO |
| WO-2015054665 | Apr 2015 | WO |
| WO-2015129395 | Sep 2015 | WO |
| WO-2016093049 | Jun 2016 | WO |
| WO-2016100719 | Jun 2016 | WO |
| WO-2016118752 | Jul 2016 | WO |
| WO-2016206015 | Dec 2016 | WO |
| WO-2017011382 | Jan 2017 | WO |
| WO-2017011646 | Jan 2017 | WO |
| WO-2017058617 | Apr 2017 | WO |
| WO-2017058695 | Apr 2017 | WO |
| WO-2017151996 | Sep 2017 | WO |
| WO-2017183353 | Oct 2017 | WO |
| WO-2017189317 | Nov 2017 | WO |
| WO-2017205308 | Nov 2017 | WO |
| WO-2017210499 | Dec 2017 | WO |
| WO-2017210501 | Dec 2017 | WO |
| WO-2018116247 | Jun 2018 | WO |
| WO-2018152141 | Aug 2018 | WO |
| WO-2018176414 | Oct 2018 | WO |
| Entry |
|---|
| US 10,504,709 B2, 12/2019, Karancsi et al. (withdrawn) |
| Surgical instrumentation: the true cost of instrument trays and a potential strategy for optimization; Mhiala et al.; Sep. 23, 2015 (Year: 2015). |
| “ATM-MPLS Network Interworking Version 2.0, af-aic-0178.001” ATM Standard, The ATM Forum Technical Committee, published Aug. 2003. |
| “Surgical instrumentation: the true cost of instrument trays and a potential strategy for optimization”; Mhlaba et al.; Sep. 23, 2015 (Year: 2015). |
| Allan et al., “3-D Pose Estimation of Articulated Instruments in Robotic Minimally Invasive Surgery,” IEEE Transactions on Medical Imaging, vol. 37, No. 5, May 1, 2018, pp. 1204-1213. |
| Altenberg et al., “Genes of Glycolysis are Ubiquitously Overexpressed in 24 Cancer Classes,” Genomics, vol. 84, pp. 1014-1020 (2004). |
| Anonymous, “Internet of Things Powers Connected Surgical Device Infrastructure Case Study”, Dec. 31, 2016 (Dec. 31, 2016), Retrieved from the Internet: URL:https://www.cognizant.com/services-resources/150110_IoT_connected_surgical_devices.pdf. |
| Anonymous: “Screwdriver—Wikipedia”, en.wikipedia. org, Jun. 23, 2019, XP055725151, Retrieved from the Internet: URL:https://en.wikipedia.org/w/index.php?title=Screwdriver&oldid=903111203 [retrieved on Mar. 20, 2021]. |
| Anonymous: “Cloud computing—Wikipedia”, Dec. 19, 2017, Retrieved from the Internet: URL:https://en.wikipedia.org/w/index.php?title=Cloud_computing&oldid=816206558 [retrieved Feb. 14, 2023], pp. 1-21. |
| Anonymous: “Differentiated services—Wikipedia”, Dec. 14, 2017, Retrieved from the Internet: URL:https://en.wikipedia.org/w/index.php?title=Differentiated_services&oldid=815415620 [retrieved on Feb. 14, 2023], pp. 1-7. |
| Anonymous: “Quality of service—Wikipedia”, Dec. 7, 2017, Retrieved from the Internet: URL:https://en.wikipedia.org/w/index.php?title=Quality_of_service&oldid=814298744#Applications [retrieved on Feb. 14, 2023], pp. 1-12. |
| Anonymous: “Titanium Key Chain Tool 1.1, Ultralight Multipurpose Key Chain Tool, Forward Cutting Can Opener—Vargo Titanium,” vargooutdoors.com, Jul. 5, 2014 (Jul. 5, 2014), retrieved from the internet: https://vargooutdoors.com/titanium-key-chain-tool-1-1.html. |
| Benkmann et al., “Concept of iterative optimization of minimally invasive surgery,” 2017 22nd International Conference on Methods and Models in Automation and Robotics (MMAR), IEEE pp. 443-446, Aug. 28, 2017. |
| Bonaci et al., “To Make a Robot Secure: An Experimental Analysis of Cyber Security Threats Against Teleoperated Surgical Robots,” May 13, 2015. Retrieved from the Internet: URL:https://arxiv.org/pdf/1504.04339v2.pdf [retrieved on Aug. 24, 2019]. |
| Cengiz, et al., “A Tale of Two Compartments: Interstitial Versus Blood Glucose Monitoring,” Article, Jun. 2009, pp. S11-S16, vol. 11, Supplement 1, Diabetes Technology & Therapeutics. |
| Choi et al., A haptic augmented reality surgeon console for a laparoscopic surgery robot system, 2013, IEEE, p. 355-357 (Year: 2013). |
| CRC Press, “The Measurement, Instrumentation and Sensors Handbook,” 1999, Section VII, Chapter 41, Peter O'Shea, “Phase Measurement,” pp. 1303-1321, ISBN 0-8493-2145-X. |
| Dottorato, “Analysis and Design of the Rectangular Microstrip Patch Antennas for TM0n0 operating mode, ”Article, Oct. 8, 2010, pp. 1-9, Microwave Journal. |
| Draijer, Matthijs et al., “Review of laser speckle contrast techniques for visualizing tissue perfusion,” Lasers in Medical Science, Springer-Verlag, LO, vol. 24, No. 4, Dec. 3, 2008, pp. 639-651. |
| Engel et al. “A safe robot system for craniofacial surgery”, 2013 IEEE International Conference on Robotics and Automation (ICRA); May 6-10, 2013; Karlsruhe, Germany, vol. 2, Jan. 1, 2001, pp. 2020-2024. |
| Flores et al., “Large-scale Offloading in the Internet of Things,” 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), IEEE, pp. 479-484, Mar. 13, 2017. |
| Giannios, et al., “Visible to near-infrared refractive properties of freshly-excised human-liver tissues: marking hepatic malignancies,” Article, Jun. 14, 2016, pp. 1-10, Scientific Reports 6, Article No. 27910, Nature. |
| Harold I. Brandon and V. Leroy Young, Mar. 1997, Surgical Services Management vol. 3 No. 3. retrieved from the internet <https://www.surgimedics.com/Research%20Articles/Electrosurgical%20Plume/Characterization%20And%20Removal%20Of%20Electrosurgical%20Smoke.pdf> (Year: 1997). |
| Hirayama et al., “Quantitative Metabolome Profiling of Colon and Stomach Cancer Microenvironment by Capillary Electrophoresis Time-of-Flight Mass Spectrometry,” Article, Jun. 2009, pp. 4918-4925, vol. 69, Issue 11, Cancer Research. |
| Homa Alemzadeh et al., “Targeted Attacks on Teleoperated Surgical Robots: Dynamic Model-Based Detection and Mitigation,” 2016 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), IEEE, Jun. 28, 2016, pp. 395-406. |
| Horn et al., “Effective data validation of high-frequency data: Time-point-time-interval-, and trend-based methods,” Computers in Biology and Medic, New York, NY, vol. 27, No. 5, pp. 389-409 (1997). |
| Hsiao-Wei Tang, “ARCM”, Video, Sep. 2012, YouTube, 5 screenshots, Retrieved from internet: <https://www.youtube.com/watch?v=UIdQaxb3fRw&feature=youtu.be>. |
| Hu, Jinwen, Stimulations of adaptive temperature control with self-focused hyperthermia system for tumor treatment, Jan. 9, 2012, Ultrasonics 53, pp. 171-177, (Year: 2012). |
| Hussain et al., “A survey on resource allocation in high performance distributed computing systems”, Parallel Computing, vol. 39, No. 11, pp. 709-736 (2013). |
| IEEE Std 802.3-2012 (Revision of IEEE Std 802.3-2008, published Dec. 28, 2012. |
| IEEE Std No. 177, “Standard Definitions and Methods of Measurement for Piezoelectric Vibrators,” published May 1966, The Institute of Electrical and Electronics Engineers, Inc., New York, N.Y. |
| Jiang, “Sound of Silence' : a secure indoor wireless ultrasonic communication system,” Article, 2014, pp. 46-50, Snapshots of Doctoral Research at University College Cork, School of Engineering—Electrical & Electronic Engineering, UCC, Cork, Ireland. |
| Kalantarian et al., “Computation Offloading for Real-Time Health-Monitoring Devices,” 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EBMC), IEEE, pp. 4971-4974, Aug. 16, 2016. |
| Kassahun et al., “Surgical Robotics Beyond Enhanced Dexterity Instrumentation: A Survey of the Machine Learning Techniques and their Role in Intelligent and Autonomous Surgical Actions.” International Journal of Computer Assisted Radiology and Surgery, vol. 11, No. 4, Oct. 8, 2015, pp. 553-568. |
| Khazaei et al., “Health Informatics for Neonatal Intensive Care Units: An Analytical Modeling Perspective,” IEEE Journal of Translational Engineering in Health and Medicine, vol. 3, pp. 1-9, Oct. 21, 2015. |
| Lalys, et al., “Automatic knowledge-based recognition of low-level tasks in ophthalmological procedures”, Int J CARS, vol. 8, No. 1, pp. 1-49, Apr. 19, 2012. |
| Li, et al., “Short-range ultrasonic communications in air using quadrature modulation,” Journal, Oct. 30, 2009, pp. 2060-2072, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 56, No. 10, IEEE. |
| Marshall Brain, How Microcontrollers Work, 2006, retrieved from the internet <https://web.archive.org/web/20060221235221/http://electronics.howstuffworks.com/microcontroller.htm/printable> (Year: 2006). |
| Miksch et al., “Utilizing temporal data abstraction for data validation and therapy planning for artificially ventilated newborn infants,” Artificial Intelligence in Medicine, vol. 8, No. 6, pp. 543-576 (1996). |
| Miller, et al., “Impact of Powered and Tissue-Specific Endoscopic Stapling Technology on Clinical and Economic Outcomes of Video-Assisted Thoracic Surgery Lobectomy Procedures: A Retrospective, Observational Study,” Article, Apr. 2018, pp. 707-723, vol. 35 (Issue 5), Advances in Therapy. |
| Misawa, et al. “Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience,” Article, Jun. 2018, pp. 2027-2029, vol. 154, Issue 8, American Gastroenterolgy Association. |
| Nabil Simaan et al, “Intelligent Surgical Robots with Situational Awareness: From Good to Great Surgeons”, DOI: 10.1115/1.2015-Sep-6 external link, Sep. 2015 (Sep. 2015), p. 3-6, Retrieved from the Internet: URL:http://memagazineselect.asmedigitalcollection.asme.org/data/journals/meena/936888/me-2015-sep6.pdf XP055530863,. |
| Nordlinger, Christopher, “The Internet of Things and the Operating Room of the Future,” May 4, 2015, https://medium.com/@chrisnordlinger/the-internet-of-things-and-the-operating-room-of-the-future-8999a143d7b1, retrieved from the internet on Apr. 27, 2021, 9 pages. |
| Phumzile Malindi, “5. QoS in Telemedicine,” “Telemedicine,” Jun. 20, 2011, IntechOpen, pp. 119-138. |
| Roy D Cullum, “Handbook of Engineering Design”, ISBN: 9780408005586, Jan. 1, 1988 (Jan. 1, 1988), XP055578597, ISBN: 9780408005586, 10-20, Chapter 6, p. 138, right-hand col. paragraph 3. |
| Salamon, “Al Detects Polyps Better Than Colonoscopists” Online Article, Jun. 3, 2018, Medscape Medical News, Digestive Disease Week (DDW) 2018: Presentation 133. |
| Screen captures from YouTube video clip entitled “Four ways to use the Lego Brick Separator Tool,” 2 pages, uploaded on May 29, 2014 by user “Sarah Lewis”. Retrieved from internet: https://www.youtube.com/watch?v=ucKiRD6U1LU (Year: 2014). |
| Shen, et al., “An iridium nanoparticles dispersed carbon based thick film electrochemical biosensor and its application for a single use, disposable glucose biosensor,” Article, Feb. 3, 2007, pp. 106-113, vol. 125, Issue 1, Sensors and Actuators B: Chemical, Science Direct. |
| Shi et al., An intuitive control console for robotic surgery system, 2014, IEEE, p. 404-407 (Year: 2014). |
| Slocinski et al., “Distance measure for impedance spectra for quantified evaluations,” Lecture Notes on Impedance Spectroscopy, vol. 3, Taylor and Francis Group (Jul. 2012)—Book Not Attached. |
| Sorrells, P., “Application Note AN680. Passive RFID Basics,” retrieved from http://ww1.microchip.com/downloads/en/AppNotes/00680b.pdf on Feb. 26, 2020, Dec. 31, 1998, pp. 1-7. |
| Stacey et al., “Temporal abstraction in intelligent clinical data analysis: A survey, ” Artificial Intelligence in Medicine, vol. 39, No. 1, pp. 1-24 (2006). |
| Staub et al., “Contour-based Surgical Instrument Tracking Supported by Kinematic Prediction,” Proceedings of the 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics, Sep. 1, 2010, pp. 746-752. |
| Sun et al., Innovative effector design for simulation training in robotic surgery, 2010, IEEE, p. 1755-1759 (Year: 2010). |
| Takahashi et al., “Automatic smoke evacuation in laparoscopic surgery: a simplified method for objective evaluation,” Surgical Endoscopy, vol. 27, No. 8, pp. 2980-2987, Feb. 23, 2013. |
| Trautman, Peter, “Breaking the Human-Robot Deadlock: Surpassing Shared Control Performance Limits with Sparse Human-Robot Interaction,” Robotics: Science and Systems XIIII, pp. 1-10, Jul. 12, 2017. |
| Vander Heiden, et al., “Understanding the Warburg effect: the metabolic requirements of cell proliferation,” Article, May 22, 2009, pp. 1-12, vol. 324, Issue 5930, Science. |
| Weede et al. “An Intelligent and Autonomous Endoscopic Guidance System for Minimally Invasive Surgery,” 2013 IEEE International Conference on Robotics ad Automation (ICRA), May 6-10, 2013. Karlsruhe, Germany, May 1, 2011, pp. 5762-5768. |
| Xie et al., Development of stereo vision and master-slave controller for a compact surgical robot system, 2015, IEEE, p. 403-407 (Year: 2015). |
| Yang et al., “A dynamic stategy for packet scheduling and bandwidth allocation based on channel quality in IEEE 802.16e OFDMA system,” Journal of Network and Computer Applications, vol. 39, pp. 52-60, May 2, 2013. |
| Yuyi Mao et al., “A Survey on Mobile Edge Computing: The Communication Perspective,” IEEE Communications Surveys & Tutorials, pp. 2322-2358, Jun. 13, 2017. |
| Zoccali, Bruno, “A Method for Approximating Component Temperatures at Altitude Conditions Based on CFD Analysis at Sea Level Conditions,” (white paper), www.tdmginc.com, Dec. 6, 2018 (9 pages). |
| Number | Date | Country | |
|---|---|---|---|
| 20220230738 A1 | Jul 2022 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62729191 | Sep 2018 | US | |
| 62692768 | Jun 2018 | US | |
| 62692747 | Jun 2018 | US | |
| 62692748 | Jun 2018 | US | |
| 62659900 | Apr 2018 | US | |
| 62650882 | Mar 2018 | US | |
| 62650877 | Mar 2018 | US | |
| 62650887 | Mar 2018 | US | |
| 62650898 | Mar 2018 | US | |
| 62640415 | Mar 2018 | US | |
| 62640417 | Mar 2018 | US | |
| 62611340 | Dec 2017 | US | |
| 62611339 | Dec 2017 | US | |
| 62611341 | Dec 2017 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 16182242 | Nov 2018 | US |
| Child | 17592080 | US |
