System and method for transmitting data and ordering asynchronous data

Information

  • Patent Grant
  • 12301663
  • Patent Number
    12,301,663
  • Date Filed
    Monday, January 31, 2022
    3 years ago
  • Date Issued
    Tuesday, May 13, 2025
    2 days ago
Abstract
A computer-implemented system includes an electromechanical device configured to be manipulated by a patient while performing an exercise session, and a processor in communication with the electromechanical device. The processor is configured to receive data, generate a map packet, and transmit the map packet. The processor is configured to use the data to generate continuity packets, where each of the continuity packets includes a contiguous portion of the data, and transmit the continuity packets. The processor is configured to use the map packet and the continuity packets to cause an output file to be generated.
Description
TECHNICAL FIELD

This disclosure relates generally to systems and methods of transmitting and processing data.


BACKGROUND

Medical devices may include one or more sensors that detect events and generate data pertaining to the events. The data from the sensors may flow in a data stream from the device to a network and, optionally, back to the device. This process can generate exceedingly large amounts of data, requiring substantial memory to use and to store the data. The data may be input into an electronic medical record (EMR) system. EMRs can include information related to the health of a patient, and such information may be contained in or called an “electronic health record.” The EMR can use and store electronic health records of patients (e.g., a collection of patient and population health information in a digital format). The health information may be used by a variety of entities, such as health care providers (e.g., physicians, physical therapists, nurses, etc.); insurance companies; billing companies; hospitals; laboratory service providers; psychological service providers (e.g., psychiatrists, psychologists, counselors, social workers); or any other suitable entity. These entities may use the health information to enable the determination of optimal treatments for their patients, to provide or deliver those treatments; and to accurately bill for the associated healthcare services provided to the patients. However, the substantial amount of memory that may be required to use and to store the data generated by the medical devices may result in higher healthcare costs. Further, bulk transmission of data from the medical devices to remote servers may impact network performance by causing higher peak network loads. In addition, waiting for data collection to complete before processing data may prevent health care providers from acting on error information or detecting problems with medical devices as quickly as possible. The use of telemedicine may increase the number of medical devices used by patients in their homes. For example, healthcare professionals may lease the medical devices to patients to use for rehabilitating from an injury or a surgery. A reduction in memory needed for medical devices to properly function may reduce the cost of the medical device and the fees for leasing the medical devices, resulting in reduced healthcare expenses. Further, as bulk transmission of large data files from medical devices may result in higher peak network loads, it may be desirable to reduce the size of individual files being transmitted. Further, transmitting data closer to the time it is generated may enable easier access to error information and faster responses to medical devices on which problems have been detected.


SUMMARY

In general, the present disclosure provides systems and methods for transmitting data and ordering asynchronous data.


In one aspect, a computer-implemented system includes an electromechanical device configured to be manipulated by a patient while performing an exercise session, and a processor in communication with the electromechanical device. The processor is configured to receive data, generate a map packet, and transmit the map packet. The processor is configured to use the data to generate continuity packets, where each of the continuity packets includes a contiguous portion of the data, and transmit the continuity packets. The processor is configured to use the map packet and the continuity packets to cause an output file to be generated.


In one aspect, a system for transmitting data is disclosed. The system includes an information-generating device and a processor in communication with the information-generating device. The processor is configured to receive data; to generate a map packet; to transmit the map packet; using the data, to generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data; to transmit the continuity packets; and using the map packet and the continuity packets, to cause an output file to be generated.


In another aspect, a method for operating an information-generating device is disclosed. The method includes receiving data; generating a map packet; transmitting the map packet; using the data to generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data; transmitting the continuity packets; and using the map packet and the continuity packets to cause an output file to be generated.


In yet another aspect, a tangible, non-transitory computer-readable storage medium is disclosed. The tangible, non-transitory computer-readable storage medium stores instructions that, when executed, cause a processor to receive data from an information-generating device; to generate a map packet; to transmit the map packet; using the data, to generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data; to transmit the continuity packets; and using the map packet and the continuity packets, to cause an output file to be generated.


In yet another aspect, a system for ordering of asynchronously transmitted data is disclosed. The system includes a processor configured to receive, from an information-generating device, a map packet and continuity packets in an initial order. Responsive to receiving the map packet and at least two of the continuity packets, the processor is configured to use the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


In yet another aspect, a method for operating a computing device is disclosed. The method includes receiving, from an information-generating device, a map packet and continuity packets in an initial order, and, responsive to receiving the map packet and at least two of the continuity packets, using the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


In yet another aspect, a tangible, non-transitory computer-readable storage medium is disclosed. The tangible, non-transitory computer-readable storage medium stores instructions that, when executed, cause a processor to receive, from an information-generating device, a map packet and continuity packets in an initial order. Responsive to receiving the map packet and at least two of the continuity packets, the instructions cause the processor to use the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


In yet another aspect, a system for transmission and ordering of asynchronous data is disclosed. The system comprises an information-generating device comprising a device-side processor. The device-side processor is configured to receive data; generate a map packet; transmit the map packet; use the data to generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data; and transmit the continuity packets. The system further comprises a remote computing device comprising a remote processor. The remote processor is configured to receive, from the information-generating device, the map packet; to receive, from the information-generating device, the continuity packets in an initial order; and responsive to receiving at least two of the continuity packets and the map packet, to use the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


Other technical features may be readily apparent to one skilled in the art from the following figures, descriptions, and claims.


Before undertaking the DETAILED DESCRIPTION below, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document. The term “couple” and its derivatives refer to any direct or indirect communication between two or more elements, independent of whether those elements are in physical contact with one another. The terms “transmit,” “receive,” and “communicate,” as well as derivatives thereof, encompass both direct and indirect communication. The terms “transmit,” “receive,” and “communicate,” as well as derivatives thereof, encompass both communication with remote systems and communication within a system, including reading and writing to different portions of a memory device. The terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation. The term “or” is inclusive, meaning and/or. The phrase “associated with,” as well as derivatives thereof, means to include, be included within, interconnect with, contain, be contained within, connect to or with, couple to or with, be communicable with, cooperate with, interleave, juxtapose, be proximate to, be bound to or with, have, have a property of, have a relationship to or with, or the like. The term “controller” means any device, system or part thereof that controls at least one operation. Such a controller may be implemented in hardware or a combination of hardware and software and/or firmware. The functionality associated with any particular controller may be centralized or distributed, whether locally or remotely. The phrase “at least one of,” when used with a list of items, means that different combinations of one or more of the listed items may be used, and only one item in the list may be needed. For example, “at least one of: A, B, and C” includes any of the following combinations: A, B, C, A and B, A and C, B and C, and A and B and C.


Moreover, various functions described below can be implemented or supported by one or more computer programs, each of which is formed from computer readable program code and embodied in a computer readable storage medium. The terms “application” and “program” refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in a suitable computer readable program code. The phrase “computer readable program code” includes any type of computer code, including source code, object code, and executable code. The phrase “computer readable storage medium” includes any type of medium capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a flash drive, a compact disc (CD), a digital video disc (DVD), solid state drive (SSD), or any other type of memory. A “non-transitory” computer readable storage medium excludes wired, wireless, optical, or other communication links that transport transitory electrical or other signals. A non-transitory computer-readable storage medium includes media where data can be permanently stored and media where data can be stored and later overwritten, such as a rewritable optical disc or an erasable memory device.


Definitions for other certain words and phrases are provided throughout this patent document. Those of ordinary skill in the art should understand that in many if not most instances, such definitions apply to prior as well as future uses of such defined words and phrases.





BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of this disclosure and its advantages, reference is now made to the following description, taken in conjunction with the accompanying drawings. It is emphasized that, according to common practice, the various features of the drawings are not to-scale. On the contrary, the dimensions of the various features are arbitrarily expanded or reduced for clarity.



FIG. 1 illustrates a component diagram of an illustrative system for transmitting and ordering asynchronous data according to certain aspects of this disclosure.



FIG. 2 illustrates an example information-generating device according to certain aspects of this disclosure.



FIGS. 3A and 3B illustrate a method for transmitting data and ordering asynchronous data according to certain aspects of this disclosure.



FIG. 4 illustrate a method for transmitting data according to certain aspects of this disclosure.



FIGS. 5A and 5B illustrate a method for ordering asynchronous data according to certain aspects of this disclosure.





DETAILED DESCRIPTION


FIGS. 1-5, discussed below, and the various embodiments used to describe the principles of this disclosure are by way of illustration only and should not be construed in any way to limit the scope of the disclosure.



FIG. 1 illustrates a component diagram of an illustrative system 100 for transmitting and ordering asynchronous data in accordance with aspects of this disclosure. The system 100 may include an information-generating device 102. The information-generating device 102 may be a medical device. The medical device may be a testing device, a diagnostic device, a therapeutic device, or any other suitable medical device. “Medical device” as used in this context may refer to hardware, software, or a mechanical or other device that may assist in a medical service, regardless of whether it is FDA (or other governmental regulatory body of any given country) approved, required to be FDA (or other governmental regulatory body of any given country) approved or available commercially or to consumers without such approval. Non-limiting examples of the medical devices include an insulin pump, a thermometer, an MRI machine, a CT-scan machine, a glucose meter, an apheresis machine, and a physical therapy machine (e.g., an orthopedic rehabilitation device, such as a physical therapy cycle). Non-limiting examples of places where the medical device may be located include a healthcare clinic, a physical rehabilitation center, and a user's home to allow for telemedicine treatment, rehabilitation, and/or testing. FIG. 2 illustrates an example of the information-generating device 102 in which the information-generating device 102 is a physical therapy cycle 200.


The information-generating device 102 may include an electromechanical device 104, such as pedals 202 of the physical therapy cycle 200, a goniometer configured to attach to a joint and measure joint angles, or any other suitable electromechanical device. The electromechanical device 104 may be configured to be manipulated by a patient while performing an exercise session. The electromechanical device 104 may be configured to transmit information, such as pedal position information. A non-limiting example of positioning information includes information relating to the location of the electromechanical device 104 (e.g., the pedals 202).


The information-generating device 102 may include a sensor 106. The sensor 106 can be used for obtaining information, such as fingerprint information, retina information, voice information, height information, weight information, vital sign information (e.g., blood pressure, heart rate, etc.), response information to physical stimuli (e.g., change in heart rate while running on a treadmill), performance information (rate of speed of rotation of the pedals 202 of the physical therapy cycle 200), or any other suitable information. The sensor 106 may be a temperature sensor (such as a thermometer or thermocouple), a strain gauge, a proximity sensor, an accelerometer, an inclinometer, an infrared sensor, a pressure sensor, a light sensor, a smoke sensor, a chemical sensor, any other suitable sensor, a fingerprint scanner, a sound sensor, a microphone, or any combination thereof. The sensor 106 may be located on an interior or exterior of the device. For example, the sensor 106 may be a pedal position sensor located on the pedals 202 of the physical therapy cycle 200.


The information-generating device 102 may include a camera 108, such as a still image camera, a video camera, an infrared camera, an X-ray camera, any other suitable camera, or any combination thereof. The information-generating device 102 may include an imaging device 110, such as an MRI imaging device, an X-ray imaging device, a thermal imaging device, any other suitable imaging device, or any combination thereof. The information-generating device 102 may include a device-side processor 112. The device-side processor 112 can include, for example, computers, intellectual property (IP) cores, application-specific integrated circuits (ASICs), programmable logic arrays, optical processors, programmable logic controllers, microcode, microcontrollers, servers, microprocessors, digital signal processors, any other suitable circuit, or any combination thereof. The device-side processor may be in communication with the electromechanical device 104, the sensor 106, the camera 108, the imaging device 110, any other suitable device, or any combination thereof.


The information-generating device 102 may include a device-side memory 114 in communication with the device-side processor 112. The device-side memory 114 can include any type of memory capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a flash drive, a compact disc (CD), a digital video disc (DVD), solid state drive (SSD), or any other suitable type of memory. The device-side memory 114 may store instructions that cause the device-side processor 112 to perform a series of actions or processes.


The information-generating device 102 may include a device-side input 116 in communication with the device-side processor 112. Examples of the device-side input 116 include a keyboard, a keypad, a mouse, a microphone supported by speech-to-text software, or any other suitable input device. The device-side input 116 may be used by a medical system operator to input information, such as user-identifying information, observational notes, or any other suitable information. An operator is to be understood throughout this disclosure to include people, bots, robots, hardware, and/or computer software, such as programs or artificial intelligence, and any combination thereof.


The information-generating device 102 may include a device-side output 118 in communication with the device-side processor 112. The device-side output 118 may be used to provide information to the operator or a user (or patient) of the information-generating device 102. For the purposes of this disclosure, user and patient are used interchangeably. Examples of the device-side output 118 may include a display screen, a speaker, an alarm system, or any other suitable output device, including haptic, tactile, olfactory, or gustatory ones. In some embodiments, such as where the information-generating device 102 includes a touchscreen, the device-side input 116 and the device-side output 118 may be the same device.


For communicating with remote computers and servers, the information-generating device 102 may include a device-side network adapter 120 in communication with the device-side processor 112. The device-side network adapter 120 may include wired or wireless network adapter devices (e.g., a wireless modem or Bluetooth) or a wired network port.


The information-generating device 102 may be coupled to or be in communication with a remote computing device 122. The remote computing device 122 may include a remote processor 124. The remote processor 124 can include, for example, computers, intellectual property (IP) cores, application-specific integrated circuits (ASICs), programmable logic arrays, optical processors, programmable logic controllers, microcode, microcontrollers, servers, microprocessors, digital signal processors, any other suitable circuit, or any combination thereof


The remote computing device 122 may include a remote memory 126 in communication with the remote processor 124. The remote memory 126 can include any type of memory capable of being accessed by a computer, such as read only memory (ROM), random access memory (RAM), a hard disk drive, a flash drive, a compact disc (CD), a digital video disc (DVD), solid state drive (SSD), or any other suitable type of memory. The remote memory 126 may store instructions that cause the remote processor 124 to perform a series of actions or processes.


The remote computing device 122 may include a remote input 128 in communication with the remote processor 124. Examples of the remote input 128 include a keyboard, a keypad, a mouse, a microphone supported by speech-to-text software, or any other suitable input device. The remote input 128 may be used by a medical system operator to input information, such as user-identifying information, observational notes, or any other suitable information. An operator is to be understood throughout this disclosure to include people, bots, robots, hardware, and/or computer software, such as programs or artificial intelligence, and any combination thereof.


The remote computing device 122 may include a remote output 130 in communication with the remote processor 124. The remote output 130 may be used to provide information to the operator or a user (or patient) of the remote computing device 122. For the purposes of this disclosure, user and patient are used interchangeably. Examples of the remote output 130 may include a display screen, a speaker, an alarm system, or any other suitable output device, including haptic, tactile, olfactory, or gustatory ones. In some embodiments, such as where the remote computing device 122 includes a touchscreen, the remote input 128 and the remote output 130 may be the same device.


For communicating with the information-generating device 102, as well as remote computers and servers, the remote computing device 122 may include a remote network adapter 132 in communication with the remote processor 124. The remote network adapter 122 may include wired or wireless network adapter devices (e.g., a wireless modem or Bluetooth) or a wired network port.


Both the device-side network adapter 120 and the remote network adapter 132 may be in communication with a network 134. Transmissions between the information-generating device 102 and the remote computing device 122 may pass through the network 134. The network 134 may be a public network (e.g., connected to the Internet via wired (Ethernet) or wireless (Wi-Fi)), a private network (e.g., a local area network (LAN) or wide area network (WAN)), a combination thereof, or any other suitable network.


Any time information is transmitted or communicated, the information may be in EDI file format or any other suitable file format. In any of the processes or steps of the method, file format conversions may take place. By utilizing Internet of Things (IoT) devices or gateways, data streams, ETL bucketing, EDI mastering, or any other suitable technique, data can be mapped, converted, translated, or transformed into a carrier-preferred state. As a result of the volume of data being transmitted, the data security requirements, and the data consistency requirements, an enterprise grade architecture may be utilized for reliable data transfer.



FIG. 1 is not intended to be limiting: the system 100, the information-generating device 102, and the remote computing device 122 may include more or fewer components than those illustrated in FIG. 1.



FIGS. 3A and 3B illustrate a computer-implemented method 300 for transmitting data and ordering asynchronous data. The method 300 may be performed by the system 100 using the information-generating device 102 and the remote computing device 122. The method 300 may be implemented on a pair of processors, such as the device-side processor 112 and the remote processor 124, which are together configured to perform the steps of the method 300. The method 300 may include operations implemented in instructions stored on one or more memory devices, such as the device-side memory 114 and the remote memory 126, and be executed by one or more processors, such as the device-side processor 112 and the remote processor 124. The steps of the method 300 may be stored in one or more non-transient computer-readable storage media.


At step 302, the method 300 includes, at the information-generating device 102, receiving data. For example, the device-side processor 112 can receive data from the electromechanical device 104, the sensor 106, the camera, 108, the imaging device 110, the device-side input 116, or any other suitable device. As a more specific example, the device-side processor 112 may receive an Mill image from an Mill imaging device (i.e., the imaging device 110). The data may be received as a stream of data. The stream of data may be a continuous stream of data. The device-side processor 112 may initially receive the data as a digital signal, an analog signal, or any other suitable signal. The device-side processor 112 may convert data from an analog signal to a digital signal.


At step 304, the method 300 includes, at the information-generating device, generating a map packet. The map packet contains data mapping information that indicates a means, a method, an approach or another mechanism for receiving the continuity packets. In some embodiments, the map packet includes end-of-file information that function as information against which data from later-received continuity packets can be compared for determining whether data transmission for a given file has ended. For example, the map packet may contain data mapping information indicating that the continuity packets will have a header following the format of “AA######AA”, and an end-of-file continuity packet will have an end-of-file header following the format of “AA######ZZ”. In this example, “######” indicates a numerical value starting at “000000” and going to a possible maximum of “999999” and “ZZ” functions as an end tag to indicate that the tagged continuity packet is the final continuity packet of the given file.


At step 306, the method 300 includes, at the information-generating device, transmitting the map packet. For example, the device-side processor 112 may direct the device-side network adapter 120 to transmit the map packet to the remote network adapter 132 of the remote computing device 122.


At step 308, the method 300 includes, at the information-generating device, generating the continuity packets. Each of the continuity packets is a data packet that includes a contiguous portion of the data. The continuity packets may be generated using the data. For example, the device-side processor 112 may take a contiguous portion of the data and place that contiguous portion into one of the continuity packets. One or more of the continuity packets may include header information that the processor can use to order the continuity packets. For example, a first continuity packet may include a first header including first header information of “AA000000AA”, and a second continuity packet may include a second header including second header information of “AA000001AA”. A contiguous portion of the data mapping information of the map packet may correspond to a contiguous portion of the header information. For example, the header information may include a contiguous portion of data, including the string “AA”. The string “AA” corresponds with a portion of the mapping information of the map packet, thereby indicating that header information of relevant continuity packets will contain the string “AA”. The header information may also include information pertaining to the portion of data contained in the continuity packet. The information-generating device generates the continuity packets in an initial order; however, a remote computing device 122 may not receive the continuity packets in the initial order (e.g., a first continuity packet may be generated first and a second continuity packet may be generated second, but the second packet may be received before the first packet is received). Thus, the header information may include information that the remote computing device 122 can use to order (e.g., reassemble) the continuity packets, such as the initial order that the continuity packets were generated. The header information of an end-of-file continuity packet can include an end tag corresponding to a contiguous portion of the end-of-file information. For example, an end-of-file continuity packet may include end-of-file header information of “AA000002ZZ”, where “ZZ” functions as the end tag. The generation of the continuity packets may occur all at once or be spread out over time as more data is received, so the end-of file header information is used to indicate an end of the data stream.


At step 310, the method 300 includes, at the information-generating device, transmitting the continuity packets. For example, the device-side processor 112 may direct the device-side network adapter 120 to transmit the continuity packets to the remote network adapter 132 of the remote computing device 122. This transmission may occur after all continuity packets have been generated, as the continuity packets are being generated, or any combination thereof. In cases where the generation of the continuity packets is spread out over time as more data is received, the generation and the transmission of the continuity packets allow for a reduced memory requirement and reduced peak network loads relative to first waiting for all of the data to be received. For instance, if, before generating the continuity packets, the information-generating device waits until all of the data is received (e.g., from the sensors), the device-side memory 114 may have to store the entirety of the data (i.e., which may require a substantial amount of memory to store an extremely large file), rather than temporarily storing a portion of the data while the device-side processor 112 generates and transmits each continuity packet. Similarly, if, before transmitting the continuity packets, the information-generating device waits until all of the data has been received and all of the continuity packets have been generated, the network loads required for the transmission may be higher because a larger amount of data is being transmitted at once (e.g., all of the continuity packets are being transmitted in a short time period).


At step 312, the method 300 includes, at the remote computing device (e.g., the remote computing device 122), receiving the map packet. The map packet may be received from the information-generating device 102. For example, the remote computing device 122 may receive the map packet by way of the remote network adapter 132.


At step 314, the method 300 includes, at the remote computing device, receiving continuity packets in an initial order. The continuity packets may be received from the information-generating device 102. For example, continuity packets may be received by the remote computing device 122 by way of the remote network adapter 132 in an initial order wherein the second continuity packet is received first, the first continuity packet is received second, and the end-of-file continuity packet is received third.


At step 316, the method 300 includes, at the remote computing device, generating an output file. Responsive to receiving at least two of the continuity packets and the map packet, the map packet may be used to generate an output file. The output file may be generated by ordering the continuity packets from the initial order into an output order. For example, given the initial order described above in step 314, the remote processor 124 may order the continuity packets, or contiguous portions of the continuity packets corresponding to contiguous portions of the data, into an output order. The output order may be as follows: 1) the first continuity packet, 2) the second continuity packet, and 3) the end-of-file continuity packet. In some embodiments, as the remote processor receives the continuity packets, the remote processor may contemporaneously generate the output file. For example, the remote computing device 124 may receive the second continuity packet first and the first continuity packet second, but not yet have received the end-of-file continuity packet, in which case the remote processor 124 may order the continuity packets into an output order having the first continuity packet first and the second continuity packet second. In some embodiments, while the output file is being generated, the continuity packets are configured to be readable by external processes. Examples of such external processes include maintenance processes configured to check for device maintenance status or error messages. Such external processes may be able to read and/or respond to maintenance requests or errors prior to ordering, such that an error message contained in the continuity packets can be read prior to completing the generation of the output file. For example, if a patient is undergoing a CT scan performed by a CT scanner, a processor may monitor and read the data in real-time or near real-time to detect an error message. In this example, if the CT scanner generates a continuity packet containing an error message indicating a fault with the CT scanner (e.g., the data obtained by the CT scanner will be unusable), then, at the direction of such an external monitoring process, the remote processor 124 may read the error message prior to ordering and generating the output file and stop the CT scanner during the CT scan. Stopping the CT scan prior to its completion would limit the patient's unnecessary exposure to X-rays, as any exposure after the error may not result in usable data.


At step 318, the method 300 may include, at the remote computing device, using the end tag to generate an end-of-file indicator. For example, a flag may be used or a variable may be set as an end-of-file indicator when the end-of-file continuity packet containing the end tag “ZZ” is received (i.e., the remote processor may change a variable “end-of-file-reached” from “false” to “true”).


At step 320, the method 300 may include using the header information, the map packet, and the end-of-file indicator to determine whether any continuity packets remain to be received. For example, if the first continuity packet containing the first header information of “AA000000AA” and the end-of-file continuity packet containing the end-of-file header information “AA000002ZZ” (and thus the end tag “ZZ”) have been received, the remote processor 124 may determine that the second continuity packet has not been received. If any continuity packets remain to be received, the method 300 proceeds to step 322. If all continuity packets have been received, the method 300 proceeds to step 330.


At step 322, if any continuity packets remain to be received, the method 300 may include determining a non-zero wait time period. For example, if the second continuity packet has not been received, the remote processor 124 may determine a wait time period. The wait time period may be between two seconds and ten seconds, or any other suitable period of time.


At step 324, the method 300 may include, at the remote computing device, determining if any continuity packets were received within the wait time period. For example, if the second continuity packet, which had not been previously received, is received within the wait time period, the remote computing device may determine that a continuity packet was received within the wait time period, subsequent to which the method 300 proceeds to step 326. However, if the second continuity packet is not received within the wait time period, the remote processor 124 may determine that the continuity packet was not received within the wait time period, subsequent to which the method 300 proceeds to step 328.


At step 326, responsive to receiving another continuity packet within the non-zero wait time period, the method 300 may include the remote computing device continuing to generate the output file. For example, if the determination is that the second continuity packet that had not been previously received is received within the wait time period, then the remote processor 124 may continue generating the output file. The method 300 may return to step 320.


At step 328, responsive to determining the non-zero wait time period and not receiving another continuity packet within the non-zero wait time period, the method 300 may include the remote computing device transmitting an error signal. For example, if the determination is that the second continuity packet that had not been previously received was not received within the wait time period, the remote processor 124 may direct the remote network adapter 132 to transmit an error message and/or the remote output 130 to present the error message (e.g., “Error: Incomplete Data”).


At step 330, responsive to determining that every continuity packet has been received, the method 300 includes transmitting the output file. For example, if the first continuity packet, the second continuity packet, and the end-of-file continuity packet have been received and ordered (e.g., into an output file), the remote processor 124 may direct the remote network adapter 132 to transmit the output file via the network 134.



FIG. 4 illustrates a computer-implemented method 400 for transmitting data. Using the information-generating device 102, the method 400 may be performed by the system 100. The method 400 may be implemented on a processor, such as the device-side processor 112 configured to perform the steps of the method 400. The method 400 may include operations implemented in instructions stored on a memory device, such as the device-side memory 114 executed by a processor, such as the device-side processor 112. The steps of the method 300 may be stored on a non-transient computer-readable storage medium.


At step 402, the method 400 includes, at the information-generating device (e.g., the information-generating device 102), receiving data. For example, the device-side processor 112 can receive data from the electromechanical device 104, the sensor 106, the camera 108, the imaging device 110, the device-side input 116, or any other suitable device. As a more specific example, the device-side processor 112 may receive an MM image from an Mill imaging device (i.e., the imaging device 110). The data may be received as a stream of data. The stream of data may be a continuous stream of data. The device-side processor 112 may initially receive the data as a digital signal, an analog signal, or any other suitable signal. The device-side processor 112 may convert data from an analog signal to a digital signal.


At step 404, the method 400 includes, at the information-generating device, generating a map packet. The map packet contains data mapping information that indicates a means, a method, an approach, or another mechanism for receiving the continuity packets. In some embodiments, the map packet includes end-of-file information that function as information against which data from later-received continuity packets can be compared for determining whether data transmission for a given file has ended. For example, the map packet may contain data mapping information indicating that the continuity packets will have a header following the format of “AA######AA”, and an end-of-file continuity packet will have an end-of-file header following the format of “AA######ZZ”. In this example, “######” indicates a numerical value starting at “000000” and going to a possible maximum of “999999” and “ZZ” functions as an end tag to indicate that the tagged continuity packet is the final continuity packet of the given file.


At step 406, the method 400 includes, at the information-generating device, transmitting the map packet. For example, the device-side processor 112 may direct the device-side network adapter 120 to transmit the map packet to the remote network adapter 132 of the remote computing device 122.


At step 408, the method 400 includes, at the information-generating device, generating the continuity packets. Each of the continuity packets is a data packet that includes a contiguous portion of the data. The continuity packets may be generated using the data. For example, the device-side processor 112 may take a contiguous portion of the data and place that contiguous portion into one of the continuity packets. One or more of the continuity packets may include header information that the processor can use to order the continuity packets. For example, a first continuity packet may include a first header including first header information of “AA000000AA”, and a second continuity packet may include a second header including second header information of “AA000001AA”. A contiguous portion of the data mapping information of the map packet may correspond to a contiguous portion of the header information. For example, the header information may include a contiguous portion of data including the string “AA”. The string “AA” corresponds to a portion of the mapping information of the map packet, indicating that header information of relevant continuity packets will contain the string “AA”. The header information may also include information pertaining to the portion of data contained in the continuity packet. The information-generating device generates the continuity packets in an initial order; however, a remote computing device 122 may not receive the continuity packets in the initial order (e.g., a first continuity packet may be generated first and a second continuity packet may be generated second, but the second packet may be received before the first packet has been received). Thus, the header information may include information that the remote computing device 122 can use to order (e.g., reassemble) the continuity packets, such as the initial order that the continuity packets were generated. The header information of an end-of-file continuity packet can include an end tag corresponding to a contiguous portion of the end-of-file information. For example, an end-of-file continuity packet may include end-of-file header information of “AA000002ZZ”, where “ZZ” functions as the end tag. The generation of the continuity packets may occur all at once or be spread out over time as more data is received, so the end-of file header information may be used to indicate an end of the data stream.


At step 410, the method 400 includes, at the information-generating device, transmitting the continuity packets. For example, the device-side processor 112 may direct the device-side network adapter 120 to transmit the continuity packets to the remote network adapter 132 of the remote computing device 122. This transmission may occur after all continuity packets have been generated, as the continuity packets are being generated, or any combination thereof. In cases where the generation of the continuity packets is spread out over time as more data is received, the generation and the transmission of the continuity packets allow for a reduced memory requirement and reduced peak network loads relative to waiting for all of the data to be received. For instance, if, before generating the continuity packets, the information-generating device waits until all of the data is received (e.g., from the sensors), the device-side memory 114 may have to store the entirety of the data (i.e., which may require a substantial amount of memory to store an exceedingly large file), rather than temporarily storing a portion of the data while the device-side processor 112 generates and transmits each continuity packet. Similarly, if, before transmitting the continuity packets, the information-generating device waits until all of the data has been received and all of the continuity packets have been generated, the network loads required for the transmission may be higher because a larger amount of data is being transmitted at once (e.g., all of the continuity packets are being transmitted in a short time period). The method 400 may proceed to step 412 or step 416.


At step 412, the method 400 may include causing the remote computing device (e.g., the remote computing device 122) to receive the map packet. The map packet may be received from the information-generating device 102. For example, the remote computing device 122 may receive the map packet by way of the remote network adapter 132.


At step 414, the method 400 may include causing the remote computing device to receive continuity packets in an initial order. The continuity packets may be received from the information-generating device 102. For example, continuity packets may be received by the remote computing device 122 by way of the remote network adapter 132 in an initial order where the second continuity packet is received first, the first continuity packet is received second, and the end-of-file continuity packet is received third.


At step 416, the method 400 includes, at the remote computing device, generating an output file. Responsive to receiving at least two of the continuity packets and the map packet, the map packet may be used to generate an output file. The output file may be generated by ordering the continuity packets from the initial order into an output order. For example, given the initial order described above in step 414, the remote processor 124 may order the continuity packets, or contiguous portions of the continuity packets corresponding to contiguous portions of the data, into an output order. The output order may be as follows: 1) the first continuity packet, 2) the second continuity packet, and 3) the end-of-file continuity packet. In some embodiments, as the remote processor receives the continuity packets, the remote processor may contemporaneously generate the output file. For example, the remote computing device 124 may receive the second continuity packet first and the first continuity packet second, but not yet have received the end-of-file continuity packet, after which the remote processor 124 may order the continuity packets into an output order having the first continuity packet first and the second continuity packet second. In some embodiments, while the output file is being generated, the continuity packets are configured to be readable by external processes. Examples of such external processes include maintenance processes configured to check for device maintenance status or error messages. Such external process may be able to read and/or respond to maintenance requests or errors prior to ordering, such that an error message contained in the continuity packets can be read prior to completing the generation of the output file. For example, if a patient is undergoing a CT scan performed by a CT scanner, a processor may monitor and read the data in real-time or near real-time to detect an error message. In this example, if the CT scanner generates a continuity packet containing an error message indicating a fault with the CT scanner (e.g., the data obtained by the CT scanner will be unusable), then, at the direction of such an external monitoring process, the remote processor 124 may read the error message prior to ordering and generating the output file and stop the CT scanner during the CT scan. Stopping the CT scan prior to its completion would limit the patient's unnecessary exposure to X-rays, as any exposure after the error may not result in usable data.



FIGS. 5A and 5B illustrate a computer-implemented method 500 for ordering asynchronous data. The method 500 may be performed by the system 100 using the remote computing device 122. The method 500 may be implemented on a processor, such as the remote processor 124, configured to perform the steps of the method 500. The method 500 may include operations implemented in instructions stored on a memory devices, such as the remote memory 126, and executed on a processor, such as the remote processor 124. The steps of the method 500 may be stored in one or more non-transient computer-readable storage media.


At step 502, the method 500 includes, at the remote computing device (e.g., the remote computing device 122), receiving the map packet. The map packet may be received from the information-generating device 102. For example, the remote computing device 122 may receive the map packet by way of the remote network adapter 132. The map packet contains data mapping information that functions as an indicator of how continuity packets will be received. In some embodiments, the map packet includes end-of-file information that function as information against which data from later-received continuity packets can be compared for determining whether data transmission for a given file has ended. For example, the map packet may contain data mapping information indicating that the continuity packets will have a header following the format of “AA######AA”, and an end-of-file continuity packet will have an end-of-file header following the format of “AA######ZZ”. In this case, “######” indicates a numerical value starting at “000000” and going to a possible maximum of “999999” and “ZZ” functions as an end tag to indicate that the tagged continuity packet is the final continuity packet of the given file.


At step 504, the method 500 includes, at the remote computing device, receiving continuity packets in an initial order. The continuity packets may be received from the information-generating device 102. For example, continuity packets may be received by the remote computing device 122 by way of the remote network adapter 132 in an initial order where the second continuity packet is received first, the first continuity packet is received second, and the end-of-file continuity packet is received third. Each of the continuity packets is a data packet that includes a contiguous portion of the data. The continuity packets may be generated using the data. For example, the device-side processor 112 may take a contiguous portion of the data and place that contiguous portion into one of the continuity packets. One or more of the continuity packets may include header information that the processor can use to order the continuity packets. For example, a first continuity packet may include a first header including first header information of “AA000000AA”, and a second continuity packet may include a second header including second header information of “AA000001AA”. A contiguous portion of the data mapping information of the map packet may correspond to a contiguous portion of the header information. For example, the header information may include a contiguous portion of data including the string “AA”. The string “AA” corresponds to a portion of the mapping information of the map packet, indicating that header information of relevant continuity packets will contain the string “AA.” The header information may also include information pertaining to the portion of data contained in the continuity packet. The information-generating device generates the continuity packets in an initial order; however, a remote computing device 122 may not receive the continuity packets in the initial order (e.g., a first continuity packet may be generated first and a second continuity packet may be generated second, but the second packet may be received before the first packet is received). Thus, the header information may include information that the remote computing device 122 can use to order (e.g., reassemble) the continuity packets, such as in the initial order that the continuity packets were generated. The header information of an end-of-file continuity packet can include an end tag corresponding to a contiguous portion of the end-of-file information. For example, an end-of-file continuity packet may include end-of-file header information of “AA000002ZZ”, where “ZZ” functions as the end tag.


At step 506, the method 500 includes, at the remote computing device, generating an output file. Responsive to receiving at least two of the continuity packets and the map packet, the map packet may be used to generate an output file. The output file may be generated by ordering the continuity packets from the initial order into an output order. For example, given the initial order described above in step 504, the remote processor 124 may order the continuity packets, or contiguous portions of the continuity packets corresponding to contiguous portions of the data, into an output order. The output order may be as follows: 1) the first continuity packet, 2) the second continuity packet, and 3) the end-of-file continuity packet. In some embodiments, as the remote processor receives the continuity packets, the remote processor may contemporaneously generate the output file. For example, the remote computing device 124 may receive the second continuity packet first and the first continuity packet second, but not yet have received the end-of-file continuity packet; and after that, the remote processor 124 may order the continuity packets into an output order having the first continuity packet first and the second continuity packet second. In some embodiments, while the output file is being generated, the continuity packets are configured to be readable by external processes. Examples of such external processes include maintenance processes configured to check for device maintenance status or error messages. Such external process may be able to read and/or respond to maintenance requests or errors prior to ordering, such that an error message contained in the continuity packets can be read prior to completing the generation of the output file. For example, if a patient is undergoing a CT scan performed by a CT scanner, a processor may monitor and read the data in real-time or near real-time to detect an error message. In this example, if the CT scanner generates a continuity packet containing an error message indicating a fault with the CT scanner (e.g., the data obtained by the CT scanner will be unusable), then, at the direction of such an external monitoring process, the remote processor 124 may read the error message prior to ordering and generating the output file and stop the CT scanner during the CT scan. Stopping the CT scan prior to its completion would limit the patient's unnecessary exposure to X-rays, as any exposure after the error may not result in usable data.


At step 508, the method 500 may include, at the remote computing device, using the end tag to generate an end-of-file indicator. For example, a flag may be used or a variable may be set as an end-of-file indicator when the end-of-file continuity packet containing the end tag “ZZ” is received (i.e., the remote processor may change a variable “end-of-file-reached” from “false” to “true”).


At step 510, the method 500 may include using the header information, the map packet, and the end-of-file indicator to determine whether any continuity packets remain to be received. For example, if the first continuity packet containing the first header information of “AA000000AA” and the end-of-file continuity packet containing the end-of-file header information “AA000002ZZ” (and thus the end tag “ZZ”) have been received, the remote processor 124 may determine that the second continuity packet has not been received. If any continuity packets remain to be received, the method 500 proceeds to step 512. If all continuity packets have been received, the method 300 proceeds to step 520.


At step 512, if any continuity packets remain to be received, the method 500 may include determining a non-zero wait time period. For example, if the second continuity packet has not been received, the remote processor 124 may determine a wait time period. The wait time period may be between two seconds and ten seconds, or any other suitable period of time.


At step 514, the method 500 may include, at the remote computing device, determining if any continuity packets were received within the wait time period. For example, if the second continuity packet, which had not been previously received, is received within the wait time period, the remote computing device may determine that a continuity packet was received within the wait time period, subsequent to which the method 500 proceeds to step 516. However, if the second continuity packet is not received within the wait time period, the remote processor 124 may determine that the continuity packet was not received within the wait time period, subsequent to which the method 500 proceeds to step 518.


At step 516, responsive to receiving another continuity packet within the non-zero wait time period, the method 500 may include the remote computing device continuing to generate the output file. For example, if the determination is that the second continuity packet that had not been previously received is received within the wait time period, then the remote processor 124 may continue generating the output file. The method 500 may then return to step 520.


At step 518, responsive to determining the non-zero wait time period and not receiving another continuity packet within the non-zero wait time period, the method 500 may include the remote computing device transmitting an error signal. For example, if the determination is that the second continuity packet that had not been previously received was not received within the wait time period, the remote processor 124 may direct the remote network adapter 132 to transmit an error message and/or the remote output 130 to present the error message (e.g., “Error: Incomplete Data”).


At step 520, responsive to determining that every continuity packet has been received, the method 500 includes transmitting the output file. For example, if the first continuity packet, the second continuity packet, and the end-of-file continuity packet have been received and ordered (e.g., into an output file), the remote processor 124 may direct the remote network adapter 132 to transmit the output file via the network 134.



FIGS. 3A, 3B, 4, 5A, and 5B are not intended to be limiting: the methods 300, 400, and 500 can include more or fewer steps and/or processes than those illustrated in FIGS. 3A, 3B, 4, 5A and 5B. Further, the order of the steps of the methods 300, 400, and 500 is not intended to be limiting; the steps can be arranged in any suitable order.


The term “computer-readable storage medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” shall also be taken to include any medium capable of storing, encoding or carrying a set of instructions for execution by the machine and causing the machine to perform any one or more of the methodologies of the present disclosure. The term “computer-readable storage medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical media, and magnetic media.


Any of the systems and methods described in this disclosure may be used in connection with rehabilitation. Unless expressly stated otherwise, is to be understood that rehabilitation includes prehabilitation (also referred to as “pre-habilitation” or “prehab”). Prehabilitation may be used as a preventative procedure or as a pre-surgical or pre-treatment procedure. Prehabilitation may include any action performed by or on a patient (or directed to be performed by or on a patient, including, without limitation, remotely or distally through telemedicine) to, without limitation, prevent or reduce a likelihood of injury (e.g., prior to the occurrence of the injury); improve recovery time subsequent to surgery; improve strength subsequent to surgery; or any of the foregoing with respect to any non-surgical clinical treatment plan to be undertaken for the purpose of ameliorating or mitigating injury, dysfunction, or other negative consequence of surgical or non-surgical treatment on any external or internal part of a patient's body. For example, a mastectomy may require prehabilitation to strengthen muscles or muscle groups affected directly or indirectly by the mastectomy. As a further non-limiting example, the removal of an intestinal tumor, the repair of a hernia, open-heart surgery or other procedures performed on internal organs or structures, whether to repair those organs or structures, to excise them or parts of them, to treat them, etc., can require cutting through and harming numerous muscles and muscle groups in or about, without limitation, the abdomen, the ribs and/or the thoracic cavity. Prehabilitation can improve a patient's speed of recovery, measure of quality of life, level of pain, etc. in all the foregoing procedures. In one embodiment of prehabilitation, a pre-surgical procedure or a pre-non-surgical-treatment may include one or more sets of exercises for a patient to perform prior to such procedure or treatment. The patient may prepare an area of his or her body for the surgical procedure by performing the one or more sets of exercises, thereby strengthening muscle groups, improving existing and/or establishing new muscle memory, enhancing mobility, improving blood flow, and/or the like.


In some embodiments, the systems and methods described herein may use artificial intelligence and/or machine learning to generate a prehabilitation treatment plan for a user. Additionally, or alternatively, the systems and methods described herein may use artificial intelligence and/or machine learning to recommend an optimal exercise machine configuration for a user. For example, a data model may be trained on historical data such that the data model may be provided with input data relating to the user and may generate output data indicative of a recommended exercise machine configuration for a specific user. Additionally, or alternatively, the systems and methods described herein may use machine learning and/or artificial intelligence to generate other types of recommendations relating to prehabilitation, such as recommended reading material to educate the patient, a recommended health professional specialist to contact, and/or the like.


Consistent with the above disclosure, the examples of systems and method enumerated in the following clauses are specifically contemplated and are intended as a non-limiting set of examples.


Clause 1. A system for transmitting data comprising:

    • an information-generating device;
    • a processor in communication with the information-generating device, wherein the processor is configured to:
      • receive data;
      • generate a map packet;
      • transmit the map packet;
      • using the data, generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data;
      • transmit the continuity packets; and
      • using the map packet and the continuity packets, cause an output file to be generated.


Clause 2. The system of any clause herein, wherein the processor is further configured to:

    • cause a remote processor to receive the map packet;
    • cause the remote processor to receive the continuity packets; and
    • wherein, responsive to the remote processor receiving the map packet and at least two of the continuity packets, the remote processor generates the output file.


Clause 3. The system of any clause herein, wherein, as the continuity packets are received, the remote processor generates the output file in real-time or near real time.


Clause 4. The system of any clause herein, wherein the remote processor receives the continuity packets in an initial order; and

    • wherein, using the map packet, the processor is configured to cause the remote processor to generate the output file by ordering the continuity packets from the initial order into an output order.


Clause 5. The system of any clause herein, wherein one or more of the continuity packets comprise header information; and

    • wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.


Clause 6. The system of any clause herein, wherein each of the continuity packets comprises header information.


Clause 7. The system of any clause herein, wherein the map packet comprises end-of-file information;

    • wherein one or more of the continuity packets comprise header information; and
    • wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of the end-of-file information.


Clause 8. The system of any clause herein, wherein the information-generating device comprises a medical device.


Clause 9. The system of any clause herein, wherein the medical device is an orthopedic rehabilitation device.


Clause 10. The system of any clause herein, further comprising a memory device operatively coupled to the processor, wherein the memory device stores instructions, and wherein the processor is configured to execute the instructions.


Clause 11. A method for operating an information-generating device, comprising:

    • receiving data;
    • generating a map packet;
    • transmitting the map packet;
    • using the data to generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data;
    • transmitting the continuity packets; and
    • using the map packet and the continuity packets to cause an output file to be generated.


Clause 12. The method of any clause herein, further comprising:

    • causing a remote processor to receive the map packet;
    • causing the remote processor to receive the continuity packets; and
    • wherein, responsive to the remote processor receiving the map packet and at least two of the continuity packets, the remote processor generates the output file.


Clause 13. The method of any clause herein, wherein, as the continuity packets are received, the remote processor generates the output file in real-time or near real time.


Clause 14. The method of any clause herein, wherein the remote processor receives the continuity packets in an initial order; and

    • wherein, using the map packet, the method further comprises causing the remote processor to generate the output file by ordering the continuity packets from the initial order into an output order.


Clause 15. The method of any clause herein, wherein one or more of the continuity packets comprise header information; and

    • wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.


Clause 16. The method of any clause herein, wherein each of the continuity packets comprises header information.


Clause 17. The method of any clause herein, wherein the map packet comprises end-of-file information;

    • wherein one or more of the continuity packets comprise header information; and
    • wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of the end-of-file information.


Clause 18. The method of any clause herein, wherein the information-generating device comprises a medical device.


Clause 19. The method of any clause herein, wherein the medical device is an orthopedic rehabilitation device.


Clause 20. A tangible, non-transitory computer-readable storage medium storing instructions that, when executed, cause a processor to:

    • receive data from an information-generating device;
    • generate a map packet;
    • transmit the map packet;
    • using the data, generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data;
    • transmit the continuity packets; and
    • using the map packet and the continuity packets, cause an output file to be generated.


Clause 21. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the instructions further cause the processor to:

    • cause a remote processor to receive the map packet;
    • cause the remote processor to receive the continuity packets; and
    • responsive to the remote processor receiving the map packet and at least two of the continuity packets, cause the remote processor to generate the output file.


Clause 22. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein, as the continuity packets are received, the remote processor generates the output file.


Clause 23. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the remote processor receives the continuity packets in an initial order; and

    • wherein, using the map packet, the instructions further cause the processor to cause the remote processor to generate the output file by ordering the continuity packets from the initial order into an output order.


Clause 24. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein one or more of the continuity packets comprise header information; and

    • wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.


Clause 25. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein each of the continuity packets comprises header information.


Clause 26. The tangible, non-transitory computer-readable storage medium of any clause herein wherein the map packet comprises end-of-file information;

    • wherein one or more of the continuity packets comprise header information; and
    • wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of the end-of-file information.


Clause 27. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the information-generating device comprises a medical device.


Clause 28. The tangible, non-transitory computer-readable storage medium of any preceding clause, wherein the medical device is an orthopedic rehabilitation device.


Clause 29. A system for ordering of asynchronously transmitted data, comprising:

    • a processor configured to:
      • receive, from an information-generating device, a map packet;
      • receive, from the information-generating device, continuity packets in an initial order; and
      • responsive to receiving the map packet and at least two of the continuity packets, use the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


Clause 30. The system of any clause herein, wherein, as the continuity packets are received, the processor is configured to generate the output file in real-time or near real time.


Clause 31. The system of any clause herein, wherein, while the output file is being generated, the continuity packets are configured to be readable by external processes.


Clause 32. The system of any clause herein, wherein one or more of the continuity packets comprise header information; and

    • wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.


Clause 33. The system of any clause herein, wherein each of the continuity packets comprises header information.


Clause 34. The system of any clause herein, wherein the map packet comprises end-of-file information;

    • wherein one or more of the continuity packets comprise header information; and
    • wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of the end-of-file information.


Clause 35. The system of any clause herein, wherein, using the end tag, the processor is further configured to generate an end-of-file indication.


Clause 36. The system of any clause herein, wherein the processor is further configured to:

    • use the header information, the map packet, and the end-of-file indication, to determine whether any continuity packet remains to be received;
    • responsive to any continuity packets remaining to be received, determine a non-zero wait time period;
    • responsive to receiving another continuity packet within the non-zero wait time period, continue to generate the output file; and
    • responsive to receiving no further continuity packets within the non-zero wait time period, transmit an error signal.


Clause 37. The system of any clause herein, wherein the processor is further configured to:

    • use the header information, the map packet, and the end-of-file indication to determine whether every continuity packet has been received; and
    • if every continuity packet has been received, transmit the output file.


Clause 38. The system of any clause herein, wherein the information-generating device comprises a medical device.


Clause 39. The system of any clause herein, wherein the medical device is an orthopedic rehabilitation device.


Clause 40. The system of any clause herein, further comprising a memory device operatively coupled to the processor, wherein the memory device stores instructions, and wherein the processor is configured to execute the instructions.


Clause 41. A method for operating a computing device, comprising:

    • receiving, from an information-generating device, a map packet;
    • receiving, from the information-generating device, continuity packets in an initial order; and
    • responsive to receiving the map packet and at least two of the continuity packets, using the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


Clause 42. The method of any clause herein, wherein, as the continuity packets are received, the output file is generated in real-time or near real-time.


Clause 43. The method of any clause herein, wherein, while the output file is being generated, the continuity packets are configured to be readable by external processes.


Clause 44. The method of any clause herein, wherein one or more of the continuity packets comprise header information; and

    • wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.


Clause 45. The method of any clause herein, wherein each of the continuity packets comprises header information.


Clause 46. The method of any clause herein, wherein the map packet comprises end-of-file information;

    • wherein one or more of the continuity packets comprise header information; and
    • wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of the end-of-file information.


Clause 47. The method of any clause herein, further comprising using the end tag to generate an end-of-file indication.


Clause 48. The method of any clause herein, further comprising:

    • using the header information, the map packet, and the end-of-file indication to determine whether every continuity packet has been received;
    • responsive to any continuity packets remaining to be received, determining a non-zero wait time period;
    • responsive to receiving another continuity packet within the non-zero wait time period, continuing to generate the output file; and
    • responsive to receiving no further continuity packets within the non-zero wait time period, transmitting an error signal.


Clause 49. The method of any clause herein, further comprising:

    • using the header information, the map packet, and the end-of-file indication to determine whether every continuity packet has been received; and
    • if every continuity packet has been received, transmitting the output file.


Clause 50. The method of any clause herein, wherein the information-generating device comprises a medical device.


Clause 51. The method of any clause herein, wherein the medical device is an orthopedic rehabilitation device.


Clause 52. A tangible, non-transitory computer-readable storage medium storing instructions that, when executed, cause a processor to:

    • receive, from an information-generating device, a map packet;
    • receive, from the information-generating device, continuity packets in an initial order; and
    • responsive to receiving the map packet and at least two of the continuity packets, using the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


Clause 53. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein, as the continuity packets are received, the processor contemporaneously generates the output file.


Clause 54. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the continuity packets are configured to be readable by external processes while the output file is being generated.


Clause 55. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein one or more of the continuity packets comprise header information; and

    • wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.


Clause 56. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein each of the continuity packets comprises header information.


Clause 57. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the map packet comprises end-of-file information;

    • wherein one or more of the continuity packets comprise header information; and
    • wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of the end-of-file information.


Clause 58. The tangible, non-transitory computer-readable storage medium of any preceding clause, wherein the instructions further cause the processor to use the end tag to generate an end-of-file indication.


Clause 59. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the instructions further cause the processor to:

    • use the header information, the map packet, and the end-of-file indication, to determine whether any continuity packet remains to be received;
    • responsive to any continuity packet remaining to be received, determine a non-zero wait time period;
    • responsive to receiving another continuity packet within the non-zero wait time period, continue generating the output file; and
    • responsive to receiving no further continuity packets within the non-zero wait time period, transmit an error signal.


Clause 60. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the instructions further cause the processor to:

    • use the header information, the map packet, and the end-of-file indication to determine whether every continuity packet has been received; and
    • responsive to determining that every continuity packet has been received, transmit the output file.


Clause 61. The tangible, non-transitory computer-readable storage medium of any clause herein, wherein the information-generating device comprises a medical device.


Clause 62. The tangible, non-transitory computer-readable storage medium of any preceding clause, wherein the medical device is an orthopedic rehabilitation device.


Clause 63. A system for transmitting data and ordering asynchronous data, comprising:

    • an information-generating device comprising a device-side processor configured to:
      • receive data;
      • generate a map packet;
      • transmit the map packet;
      • use the data to generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data;
      • transmit the continuity packets; and
    • a remote computing device comprising a remote processor configured to:
      • receive, from the information-generating device, the map packet;
      • receive, from the information-generating device, the continuity packets in an initial order; and
      • responsive to receiving at least two of the continuity packets and the map packet, use the map packet to generate an output file by ordering the continuity packets from the initial order into an output order.


Clause 64. The system of any clause herein, wherein, as the remote processor receives the continuity packets, the remote processor contemporaneously generates the output file.


Clause 65. The system of any clause herein, wherein, while the output file is being generated, the continuity packets are configured to be readable by external processes.


Clause 66. The system of any clause herein, wherein one or more of the continuity packets comprise header information; and

    • wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.


Clause 67. The system of any clause herein, wherein each of the continuity packets comprises header information.


Clause 68. The system of any clause herein, wherein the map packet comprises end-of-file information;

    • wherein one or more of the continuity packets comprise header information; and
    • wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of the end-of-file information.


Clause 69. The system of any clause herein, wherein the remote processor is further configured to, using the end tag, generate an end-of-file indication.


Clause 70. The system of any clause herein, wherein the remote processor is further configured to:

    • use the header information, the map packet, and the end-of-file indication to determine whether any continuity packets remain to be received;
    • if any continuity packets remain to be received, determine a non-zero wait time period;
    • responsive to determining the non-zero wait time period and receiving another continuity packet within the non-zero wait time period, continue generating the output file; and
    • responsive to determining the non-zero wait time period and not receiving another continuity packet within the non-zero wait time period, transmit an error signal.


Clause 71. The system of any clause herein, wherein the remote processor is further configured to:

    • use the header information, the map packet, and the end-of-file indication to determine whether every continuity packet has been received; and
    • responsive to determining that every continuity packet has been received, transmit the output file.


Clause 72. The system of any clause herein, wherein the information-generating device comprises a medical device.


Clause 73. The system of any clause herein, wherein the medical device is an orthopedic rehabilitation device.


Clause 74. The system of any clause herein, further comprising a device-side memory device operatively coupled to the device-side processor, wherein the device-side memory device stores device-side instructions, and wherein the device-side processor is configured to execute the device-side instructions.


Clause 75. The system of any clause herein, further comprising a remote memory device operatively coupled to the remote processor, wherein the remote memory device stores remote instructions, and wherein the remote processor is configured to execute the remote instructions.


Clause 76. A computer-implemented system, comprising:

    • an electromechanical device configured to be manipulated by a patient while performing an exercise session;
    • a processor in communication with the electromechanical device, wherein the processor is configured to:
    • receive data;
    • generate a map packet;
    • transmit the map packet;
    • using the data, generate continuity packets, wherein each of the continuity packets comprises a contiguous portion of the data;
    • transmit the continuity packets; and
    • using the map packet and the continuity packets, cause an output file to be generated.


Clause 77. The computer-implemented system of any clause herein, wherein the processor is further configured to:

    • cause a remote processor to receive the map packet;
    • cause the remote processor to receive the continuity packets; and
    • wherein, responsive to the remote processor receiving the map packet and at least two of the continuity packets, the remote processor generates the output file.


Clause 78. The computer-implemented system of any clause herein, wherein, as the continuity packets are received, the remote processor generates the output file in real-time or near real time.


No part of the description in this application should be read as implying that any particular element, step, or function is an essential element that must be included in the claim scope. The scope of patented subject matter is defined only by the claims. Moreover, none of the claims is intended to invoke 35 U.S.C. § 112(f) unless the exact words “means for” are followed by a participle.


The foregoing description, for purposes of explanation, use specific nomenclature to provide a thorough understanding of the described embodiments. However, it should be apparent to one skilled in the art that the specific details are not required to practice the described embodiments. Thus, the foregoing descriptions of specific embodiments are presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the described embodiments to the precise forms disclosed. It should be apparent to one of ordinary skill in the art that many modifications and variations are possible in view of the above teachings.


The above discussion is meant to be illustrative of the principles and various embodiments of the present invention. Once the above disclosure is fully appreciated, numerous variations and modifications will become apparent to those skilled in the art. It is intended that the following claims be interpreted to embrace all such variations and modifications.

Claims
  • 1. A method for operating a remote processor, comprising: receiving a map packet;receiving at least two continuity packets, wherein each comprises a contiguous portion of data, wherein: another processor generates the map packet and uses data received by an electromechanical device to generate the at least two continuity packets, andthe remote processor receives the at least two continuity packets in an initial order; andgenerating, using the map packet, an output file in real-time or near real-time, wherein:the remote processor generates the output file by ordering the at least two continuity packets from the initial order into an output order, wherein the output order is one of the same order as the initial order or a reordering of the initial order.
  • 2. The method of claim 1, wherein one or more of the at least two continuity packets comprise header information.
  • 3. The method of claim 2, wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.
  • 4. The method of claim 1, wherein each of the at least two continuity packets comprises header information.
  • 5. The method of claim 1, wherein the map packet comprises end-of-file information.
  • 6. The method of claim 1, wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of end-of-file information in the map packet.
  • 7. The method of claim 1, wherein the electromechanical device comprises a rehabilitation device.
  • 8. A system comprising: a memory device storing instructions; anda remote processor communicatively coupled to the memory device, wherein the remote processor executes the instructions to: receive a map packet;receive at least two continuity packets, wherein each comprises a contiguous portion of data, wherein: another processor generates the map packet and uses data received by an electromechanical device to generate the at least two continuity packets, andthe remote processor receives the at least two continuity packets in an initial order; andgenerate, using the map packet, an output file in real-time or near real-time, wherein:the remote processor generates the output file by ordering the at least two continuity packets from the initial order into an output order, wherein the output order is one of the same order as the initial order or a reordering of the initial order.
  • 9. The system of claim 8, wherein one or more of the at least two continuity packets comprise header information.
  • 10. The system of claim 9, wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.
  • 11. The system of claim 8, wherein each of the at least two continuity packets comprises header information.
  • 12. The system of claim 9, wherein the map packet comprises end-of-file information.
  • 13. The system of claim 8, wherein header information of an end-of-file continuity packet comprises an end tag corresponding to a contiguous portion of end-of-file information in the map packet.
  • 14. The system of claim 8, wherein the electromechanical device comprises a rehabilitation device.
  • 15. A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a remote processor to: receive a map packet;receive at least two continuity packets, wherein each comprises a contiguous portion of data, wherein: another processor generates the map packet and uses data received by an electromechanical device to generate the at least two continuity packets, andthe remote processor receives the at least two continuity packets in an initial order; andgenerate, using the map packet, an output file in real-time or near real-time, wherein:the remote processor generates the output file by ordering the at least two continuity packets from the initial order into an output order, wherein the output order is one of the same order as the initial order or a reordering of the initial order.
  • 16. The computer-readable medium of claim 15, wherein one or more of the at least two continuity packets comprise header information.
  • 17. The computer-readable medium of claim 16, wherein a contiguous portion of the map packet corresponds to a contiguous portion of the header information.
  • 18. The computer-readable medium of claim 15, wherein each of the at least two continuity packets comprises header information.
CROSS-REFERENCES TO RELATED APPLICATIONS

This application is continuation of U.S. patent application Ser. No. 17/149,457, filed Jan. 14, 2021, titled “System and Method for Transmitting Data and Ordering Asynchronous Data”, which is a continuation-in-part of U.S. patent application Ser. No. 17/021,895, filed Sep. 15, 2020, titled “Telemedicine for Orthopedic Treatment,” which claims priority to and the benefit of U.S. Provisional Patent Application Ser. No. 62/910,232, filed Oct. 3, 2019, titled “Telemedicine for Orthopedic Treatment,” the entire disclosures of which are hereby incorporated by reference for all purposes. As a continuation of U.S. patent application Ser. No. 17/149,457, this application also claims priority to and the benefit of U.S. Provisional Patent application Ser. No. 63/028,399, filed May 21, 2020, titled “System and Method for Transmitting Data and Ordering Asynchronous Data,” the entire disclosures of which are hereby incorporated by reference for all purposes.

US Referenced Citations (876)
Number Name Date Kind
823712 Uhlmann Jun 1906 A
4499900 Petrofsky et al. Feb 1985 A
4822032 Whitmore et al. Apr 1989 A
4860763 Schminke Aug 1989 A
4869497 Stewart et al. Sep 1989 A
4932650 Bingham et al. Jun 1990 A
5137501 Mertesdorf Aug 1992 A
5161430 Febey Nov 1992 A
5202794 Schnee et al. Apr 1993 A
5240417 Smithson et al. Aug 1993 A
5247853 Dalebout Sep 1993 A
5256117 Potts et al. Oct 1993 A
D342299 Birrell et al. Dec 1993 S
5282748 Little Feb 1994 A
5284131 Gray Feb 1994 A
5316532 Butler May 1994 A
5318487 Golen Jun 1994 A
5324241 Artigues et al. Jun 1994 A
5336147 Sweeney, III Aug 1994 A
5338272 Sweeney, III Aug 1994 A
5356356 Hildebrandt Oct 1994 A
5361649 Slocum, Jr. Nov 1994 A
D359777 Hildebrandt Jun 1995 S
5429140 Burdea et al. Jul 1995 A
5458022 Mattfeld et al. Oct 1995 A
5487713 Butler Jan 1996 A
5566589 Buck Oct 1996 A
5580338 Scelta et al. Dec 1996 A
5676349 Wilson Oct 1997 A
5685804 Whan-Tong et al. Nov 1997 A
5738636 Saringer et al. Apr 1998 A
5860941 Saringer et al. Jan 1999 A
5950813 Hoskins et al. Sep 1999 A
6007459 Burgess Dec 1999 A
D421075 Hildebrandt Feb 2000 S
6053847 Stearns et al. Apr 2000 A
6077201 Cheng Jun 2000 A
6102834 Chen Aug 2000 A
6110130 Kramer Aug 2000 A
6155958 Goldberg Dec 2000 A
6162189 Girone et al. Dec 2000 A
6182029 Friedman Jan 2001 B1
D438580 Shaw Mar 2001 S
6253638 Bermudez Jul 2001 B1
6267735 Blanchard et al. Jul 2001 B1
6273863 Avni et al. Aug 2001 B1
D450100 Hsu Nov 2001 S
D450101 Hsu Nov 2001 S
D451972 Easley Dec 2001 S
D452285 Easley Dec 2001 S
D454605 Lee Mar 2002 S
6371891 Speas Apr 2002 B1
D459776 Lee Jul 2002 S
6413190 Wood et al. Jul 2002 B1
6430436 Richter Aug 2002 B1
6436058 Krahner et al. Aug 2002 B1
6450923 Vatti Sep 2002 B1
6474193 Farney Nov 2002 B1
6491649 Ombrellaro Dec 2002 B1
6514085 Slattery et al. Feb 2003 B2
6535861 OConnor et al. Mar 2003 B1
6543309 Heim Apr 2003 B2
6589139 Butterworth Jul 2003 B1
6601016 Brown et al. Jul 2003 B1
6602191 Quy Aug 2003 B2
6613000 Reinkensmeyer et al. Sep 2003 B1
6626800 Casler Sep 2003 B1
6626805 Lightbody Sep 2003 B1
6640122 Manoli Oct 2003 B2
6640662 Baxter Nov 2003 B1
6652425 Martin et al. Nov 2003 B1
6820517 Farney Nov 2004 B1
6865969 Stevens Mar 2005 B2
6890312 Priester et al. May 2005 B1
6895834 Baatz May 2005 B1
6902513 McClure Jun 2005 B1
7058453 Nelson et al. Jun 2006 B2
7063643 Arai Jun 2006 B2
7156665 OConnor et al. Jan 2007 B1
7156780 Fuchs et al. Jan 2007 B1
7169085 Killin et al. Jan 2007 B1
7204788 Andrews Apr 2007 B2
7209886 Kimmel Apr 2007 B2
7226394 Johnson Jun 2007 B2
RE39904 Lee Oct 2007 E
7406003 Burkhardt et al. Jul 2008 B2
7507188 Nurre Mar 2009 B2
7594879 Johnson Sep 2009 B2
7628730 Watterson et al. Dec 2009 B1
D610635 Hildebrandt Feb 2010 S
7778851 Schoenberg et al. Aug 2010 B2
7809601 Shaya et al. Oct 2010 B2
7815551 Merli Oct 2010 B2
7833135 Radow et al. Nov 2010 B2
7837472 Elsmore et al. Nov 2010 B1
7955219 Birrell et al. Jun 2011 B2
7969315 Ross et al. Jun 2011 B1
7988599 Ainsworth et al. Aug 2011 B2
8012107 Einav et al. Sep 2011 B2
8021270 D'Eredita Sep 2011 B2
8038578 Olrik et al. Oct 2011 B2
8079937 Bedell et al. Dec 2011 B2
8113991 Kutliroff Feb 2012 B2
8172724 Solomon May 2012 B2
8177732 Einav et al. May 2012 B2
8287434 Zavadsky et al. Oct 2012 B2
8298123 Hickman Oct 2012 B2
8371990 Shea Feb 2013 B2
8419593 Ainsworth et al. Apr 2013 B2
8465398 Lee et al. Jun 2013 B2
8506458 Dugan Aug 2013 B2
8515777 Rajasenan Aug 2013 B1
8540515 Williams et al. Sep 2013 B2
8540516 Williams et al. Sep 2013 B2
8556778 Dugan Oct 2013 B1
8607465 Edwards Dec 2013 B1
8613689 Dyer et al. Dec 2013 B2
8615529 Reiner Dec 2013 B2
8672812 Dugan Mar 2014 B2
8751264 Beraja et al. Jun 2014 B2
8784273 Dugan Jul 2014 B2
8818496 Dziubinski et al. Aug 2014 B2
8823448 Shen Sep 2014 B1
8845493 Watterson et al. Sep 2014 B2
8849681 Hargrove et al. Sep 2014 B2
8864628 Boyette et al. Oct 2014 B2
8893287 Gjonej et al. Nov 2014 B2
8911327 Boyette Dec 2014 B1
8979711 Dugan Mar 2015 B2
9004598 Weber Apr 2015 B2
9044630 Lampert et al. Jun 2015 B1
9167281 Petrov et al. Oct 2015 B2
D744050 Colburn Nov 2015 S
9248071 Benda et al. Feb 2016 B1
9272185 Dugan Mar 2016 B2
9283434 Wu Mar 2016 B1
9295878 Corbalis et al. Mar 2016 B2
9311789 Gwin Apr 2016 B1
9312907 Auchinleck et al. Apr 2016 B2
9367668 Flynt et al. Jun 2016 B2
9409054 Dugan Aug 2016 B2
9443205 Wall Sep 2016 B2
9474935 Abbondanza et al. Oct 2016 B2
9480873 Chuang Nov 2016 B2
9481428 Gros et al. Nov 2016 B2
9514277 Hassing et al. Dec 2016 B2
9566472 Dugan Feb 2017 B2
9579056 Rosenbek et al. Feb 2017 B2
9629558 Yuen et al. Apr 2017 B2
9640057 Ross May 2017 B1
9707147 Levital et al. Jul 2017 B2
9713744 Suzuki Jul 2017 B2
D794142 Zhou Aug 2017 S
9717947 Lin Aug 2017 B2
9737761 Govindarajan Aug 2017 B1
9757612 Weber Sep 2017 B2
9782621 Chiang et al. Oct 2017 B2
9802076 Murray et al. Oct 2017 B2
9802081 Ridgel et al. Oct 2017 B2
9813239 Chee et al. Nov 2017 B2
9827445 Marcos et al. Nov 2017 B2
9849337 Roman et al. Dec 2017 B2
9868028 Shin Jan 2018 B2
9872087 DelloStritto et al. Jan 2018 B2
9872637 Kording et al. Jan 2018 B2
9914053 Dugan Mar 2018 B2
9919198 Romeo et al. Mar 2018 B2
9937382 Dugan Apr 2018 B2
9939784 Berardinelli Apr 2018 B1
9977587 Mountain May 2018 B2
9993181 Ross Jun 2018 B2
9997082 Kaleal Jun 2018 B2
10004946 Ross Jun 2018 B2
10026052 Brown et al. Jul 2018 B2
D826349 Oblamski Aug 2018 S
10055550 Goetz Aug 2018 B2
10058473 Oshima et al. Aug 2018 B2
10074148 Cashman et al. Sep 2018 B2
10089443 Miller et al. Oct 2018 B2
10111643 Shulhauser et al. Oct 2018 B2
10130311 De Sapio et al. Nov 2018 B1
10137328 Baudhuin Nov 2018 B2
10143395 Chakravarthy et al. Dec 2018 B2
10155134 Dugan Dec 2018 B2
10159872 Sasaki et al. Dec 2018 B2
10173094 Gomberg et al. Jan 2019 B2
10173095 Gomberg et al. Jan 2019 B2
10173096 Gomberg et al. Jan 2019 B2
10173097 Gomberg et al. Jan 2019 B2
10198928 Ross et al. Feb 2019 B1
10226663 Gomberg et al. Mar 2019 B2
10231664 Ganesh Mar 2019 B2
10244990 Hu et al. Apr 2019 B2
10258823 Cole Apr 2019 B2
10322315 Foley et al. Jun 2019 B2
10325070 Beale et al. Jun 2019 B2
10327697 Stein et al. Jun 2019 B1
10369021 Zoss et al. Aug 2019 B2
10380866 Ross et al. Aug 2019 B1
10413222 Kayyali Sep 2019 B1
10413238 Cooper Sep 2019 B1
10424033 Romeo Sep 2019 B2
10430552 Mihai Oct 2019 B2
D866957 Ross et al. Nov 2019 S
10468131 Macoviak et al. Nov 2019 B2
10475323 Ross Nov 2019 B1
10475537 Purdie et al. Nov 2019 B2
10492977 Kapure et al. Dec 2019 B2
10507358 Kinnunen et al. Dec 2019 B2
10542914 Forth et al. Jan 2020 B2
10546467 Luciano, Jr. et al. Jan 2020 B1
10569122 Johnson Feb 2020 B2
10572626 Balram Feb 2020 B2
10576331 Kuo Mar 2020 B2
10581896 Nachenberg Mar 2020 B2
10625114 Ercanbrack Apr 2020 B2
10646746 Gomberg et al. May 2020 B1
10660534 Lee et al. May 2020 B2
10678890 Bitran et al. Jun 2020 B2
10685092 Paparella et al. Jun 2020 B2
10777200 Will et al. Sep 2020 B2
D899605 Ross et al. Oct 2020 S
10792495 Izvorski et al. Oct 2020 B2
10814170 Wang et al. Oct 2020 B2
10857426 Neumann Dec 2020 B1
10867695 Neagle Dec 2020 B2
10874905 Belson et al. Dec 2020 B2
D907143 Ach et al. Jan 2021 S
10881911 Kwon et al. Jan 2021 B2
10918332 Belson et al. Feb 2021 B2
10931643 Neumann Feb 2021 B1
10987176 Poltaretskyi et al. Apr 2021 B2
10991463 Kutzko et al. Apr 2021 B2
11000735 Orady et al. May 2021 B2
11045709 Putnam Jun 2021 B2
11065170 Yang et al. Jul 2021 B2
11065527 Putnam Jul 2021 B2
11069436 Mason et al. Jul 2021 B2
11071597 Posnack et al. Jul 2021 B2
11075000 Mason et al. Jul 2021 B2
D928635 Hacking et al. Aug 2021 S
11087865 Mason et al. Aug 2021 B2
11094400 Riley et al. Aug 2021 B2
11101028 Mason et al. Aug 2021 B2
11107591 Mason Aug 2021 B1
11139060 Mason et al. Oct 2021 B2
11185735 Am et al. Nov 2021 B2
11185738 McKirdy et al. Nov 2021 B1
D939096 Lee Dec 2021 S
D939644 Ach et al. Dec 2021 S
D940797 Ach et al. Jan 2022 S
D940891 Lee Jan 2022 S
11229727 Tatonetti Jan 2022 B2
11265234 Guaneri Mar 2022 B2
11270795 Mason et al. Mar 2022 B2
11272879 Wiedenhoefer et al. Mar 2022 B2
11278766 Lee Mar 2022 B2
11282599 Mason et al. Mar 2022 B2
11282604 Mason et al. Mar 2022 B2
11282608 Mason et al. Mar 2022 B2
11284797 Mason et al. Mar 2022 B2
D948639 Ach et al. Apr 2022 S
11295848 Mason et al. Apr 2022 B2
11298284 Bayerlein Apr 2022 B2
11309085 Mason et al. Apr 2022 B2
11317975 Mason et al. May 2022 B2
11325005 Mason et al. May 2022 B2
11328807 Mason et al. May 2022 B2
11337648 Mason May 2022 B2
11347829 Sclar et al. May 2022 B1
11348683 Guaneri et al. May 2022 B2
11376470 Weldemariam Jul 2022 B2
11404150 Guaneri et al. Aug 2022 B2
11410768 Mason et al. Aug 2022 B2
11422841 Jeong Aug 2022 B2
11437137 Harris Sep 2022 B1
11495355 McNutt et al. Nov 2022 B2
11508258 Nakashima et al. Nov 2022 B2
11508482 Mason et al. Nov 2022 B2
11515021 Mason Nov 2022 B2
11515028 Mason Nov 2022 B2
11524210 Kim et al. Dec 2022 B2
11527326 McNair et al. Dec 2022 B2
11532402 Farley et al. Dec 2022 B2
11534654 Silcock et al. Dec 2022 B2
D976339 Li Jan 2023 S
11541274 Hacking Jan 2023 B2
11553969 Lang et al. Jan 2023 B1
11621067 Nolan Apr 2023 B1
11636944 Hanrahan et al. Apr 2023 B2
11654327 Phillips et al. May 2023 B2
11663673 Pyles May 2023 B2
11701548 Posnack et al. Jul 2023 B2
11957960 Bissonnette et al. Apr 2024 B2
12057210 Akinola et al. Aug 2024 B2
12205704 Hosoi et al. Jan 2025 B2
20010044573 Manoli Nov 2001 A1
20020010596 Matory Jan 2002 A1
20020072452 Torkelson Jun 2002 A1
20020143279 Porter et al. Oct 2002 A1
20020160883 Dugan Oct 2002 A1
20020183599 Castellanos Dec 2002 A1
20030013072 Thomas Jan 2003 A1
20030036683 Kehr et al. Feb 2003 A1
20030064860 Yamashita et al. Apr 2003 A1
20030064863 Chen Apr 2003 A1
20030083596 Kramer et al. May 2003 A1
20030092536 Romanelli et al. May 2003 A1
20030181832 Carnahan et al. Sep 2003 A1
20040072652 Alessandri et al. Apr 2004 A1
20040102931 Ellis et al. May 2004 A1
20040106502 Sher Jun 2004 A1
20040147969 Mann et al. Jul 2004 A1
20040172093 Rummerfield Sep 2004 A1
20040194572 Kim Oct 2004 A1
20040197727 Sachdeva et al. Oct 2004 A1
20040204959 Moreano et al. Oct 2004 A1
20050015118 Davis et al. Jan 2005 A1
20050020411 Andrews Jan 2005 A1
20050043153 Krietzman Feb 2005 A1
20050049122 Vallone et al. Mar 2005 A1
20050085346 Johnson Apr 2005 A1
20050085353 Johnson Apr 2005 A1
20050115561 Stahmann Jun 2005 A1
20050143641 Tashiro Jun 2005 A1
20050274220 Reboullet Dec 2005 A1
20060003871 Houghton et al. Jan 2006 A1
20060046905 Doody et al. Mar 2006 A1
20060058648 Meier Mar 2006 A1
20060064136 Wang Mar 2006 A1
20060064329 Abolfathi et al. Mar 2006 A1
20060129432 Choi et al. Jun 2006 A1
20060199700 LaStayo et al. Sep 2006 A1
20060247095 Rummerfield Nov 2006 A1
20070042868 Fisher et al. Feb 2007 A1
20070118389 Shipon May 2007 A1
20070137307 Gruben et al. Jun 2007 A1
20070173392 Stanford Jul 2007 A1
20070184414 Perez Aug 2007 A1
20070194939 Alvarez et al. Aug 2007 A1
20070219059 Schwartz Sep 2007 A1
20070271065 Gupta et al. Nov 2007 A1
20070287597 Cameron Dec 2007 A1
20080021834 Holla et al. Jan 2008 A1
20080077619 Gilley et al. Mar 2008 A1
20080082356 Friedlander et al. Apr 2008 A1
20080096726 Riley et al. Apr 2008 A1
20080153592 James-Herbert Jun 2008 A1
20080161166 Lo Jul 2008 A1
20080161733 Einav et al. Jul 2008 A1
20080183500 Banigan Jul 2008 A1
20080281633 Burdea et al. Nov 2008 A1
20080300914 Karkanias et al. Dec 2008 A1
20090011907 Radow et al. Jan 2009 A1
20090058635 LaLonde et al. Mar 2009 A1
20090070138 Langheier et al. Mar 2009 A1
20090211395 Mule Aug 2009 A1
20090270227 Ashby et al. Oct 2009 A1
20090287503 Angell et al. Nov 2009 A1
20090299766 Friedlander et al. Dec 2009 A1
20100048358 Tchao et al. Feb 2010 A1
20100076786 Dalton et al. Mar 2010 A1
20100121160 Stark et al. May 2010 A1
20100173747 Chen et al. Jul 2010 A1
20100216168 Heinzman et al. Aug 2010 A1
20100234184 Le Page et al. Sep 2010 A1
20100248899 Bedell et al. Sep 2010 A1
20100248905 Lu Sep 2010 A1
20100262052 Lunau et al. Oct 2010 A1
20100268304 Matos Oct 2010 A1
20100298102 Bosecker et al. Nov 2010 A1
20100326207 Topel Dec 2010 A1
20110010188 Yoshikawa et al. Jan 2011 A1
20110047108 Chakrabarty et al. Feb 2011 A1
20110119212 De Bruin et al. May 2011 A1
20110172059 Watterson et al. Jul 2011 A1
20110195819 Shaw et al. Aug 2011 A1
20110218814 Coats Sep 2011 A1
20110275483 Dugan Nov 2011 A1
20110281249 Gammell et al. Nov 2011 A1
20110306846 Osorio Dec 2011 A1
20120041771 Cosentino et al. Feb 2012 A1
20120065987 Farooq et al. Mar 2012 A1
20120116258 Lee May 2012 A1
20120130196 Jain et al. May 2012 A1
20120130197 Kugler et al. May 2012 A1
20120167709 Chen et al. Jul 2012 A1
20120183939 Aragones et al. Jul 2012 A1
20120190502 Paulus et al. Jul 2012 A1
20120232438 Cataldi et al. Sep 2012 A1
20120259648 Mallon et al. Oct 2012 A1
20120259649 Mallon et al. Oct 2012 A1
20120278759 Curl et al. Nov 2012 A1
20120295240 Walker et al. Nov 2012 A1
20120296455 Ohnemus et al. Nov 2012 A1
20120310667 Altman et al. Dec 2012 A1
20130108594 Martin-Rendon et al. May 2013 A1
20130110545 Smallwood May 2013 A1
20130123071 Rhea May 2013 A1
20130123667 Komatireddy et al. May 2013 A1
20130137550 Skinner et al. May 2013 A1
20130137552 Kemp et al. May 2013 A1
20130178334 Brammer Jul 2013 A1
20130211281 Ross et al. Aug 2013 A1
20130253943 Lee et al. Sep 2013 A1
20130274069 Watterson et al. Oct 2013 A1
20130296987 Rogers et al. Nov 2013 A1
20130318027 Almogy et al. Nov 2013 A1
20130332616 Landwehr Dec 2013 A1
20130345025 van der Merwe Dec 2013 A1
20140006042 Keefe et al. Jan 2014 A1
20140011640 Dugan Jan 2014 A1
20140031174 Huang Jan 2014 A1
20140062900 Kaula et al. Mar 2014 A1
20140074179 Heldman et al. Mar 2014 A1
20140089836 Damani et al. Mar 2014 A1
20140113261 Akiba Apr 2014 A1
20140113768 Lin et al. Apr 2014 A1
20140155129 Dugan Jun 2014 A1
20140163439 Uryash et al. Jun 2014 A1
20140172442 Broderick Jun 2014 A1
20140172460 Kohli Jun 2014 A1
20140172514 Schumann et al. Jun 2014 A1
20140188009 Lange et al. Jul 2014 A1
20140194250 Reich et al. Jul 2014 A1
20140194251 Reich et al. Jul 2014 A1
20140207264 Quy Jul 2014 A1
20140207486 Carty et al. Jul 2014 A1
20140228649 Rayner et al. Aug 2014 A1
20140246499 Proud et al. Sep 2014 A1
20140256511 Smith Sep 2014 A1
20140257837 Walker et al. Sep 2014 A1
20140274565 Boyette et al. Sep 2014 A1
20140274622 Leonhard Sep 2014 A1
20140303540 Baym Oct 2014 A1
20140309083 Dugan Oct 2014 A1
20140322686 Kang Oct 2014 A1
20140347265 Aimone et al. Nov 2014 A1
20140371816 Matos Dec 2014 A1
20140372133 Austrum et al. Dec 2014 A1
20150025816 Ross Jan 2015 A1
20150045700 Cavanagh et al. Feb 2015 A1
20150051721 Cheng Feb 2015 A1
20150065213 Dugan Mar 2015 A1
20150073814 Linebaugh Mar 2015 A1
20150088544 Goldberg Mar 2015 A1
20150094192 Skwortsow et al. Apr 2015 A1
20150099458 Weisner et al. Apr 2015 A1
20150099952 Lain et al. Apr 2015 A1
20150111644 Larson Apr 2015 A1
20150112230 Iglesias Apr 2015 A1
20150112702 Joao et al. Apr 2015 A1
20150130830 Nagasaki May 2015 A1
20150141200 Murray et al. May 2015 A1
20150142142 Campana Aguilera et al. May 2015 A1
20150149217 Kaburagi May 2015 A1
20150151162 Dugan Jun 2015 A1
20150157938 Domansky et al. Jun 2015 A1
20150161331 Oleynik Jun 2015 A1
20150161876 Castillo Jun 2015 A1
20150174446 Chiang Jun 2015 A1
20150196805 Koduri Jul 2015 A1
20150217056 Kadavy et al. Aug 2015 A1
20150251074 Ahmed et al. Sep 2015 A1
20150257679 Ross Sep 2015 A1
20150265209 Zhang Sep 2015 A1
20150290061 Stafford et al. Oct 2015 A1
20150339442 Oleynik Nov 2015 A1
20150341812 Dion et al. Nov 2015 A1
20150351664 Ross Dec 2015 A1
20150351665 Ross Dec 2015 A1
20150360069 Marti et al. Dec 2015 A1
20150379232 Mainwaring et al. Dec 2015 A1
20150379430 Dirac et al. Dec 2015 A1
20160004820 Moore Jan 2016 A1
20160007885 Basta et al. Jan 2016 A1
20160015995 Leung et al. Jan 2016 A1
20160023081 Popa-Simil et al. Jan 2016 A1
20160045170 Migita Feb 2016 A1
20160096073 Rahman et al. Apr 2016 A1
20160117471 Belt et al. Apr 2016 A1
20160132643 Radhakrishna et al. May 2016 A1
20160140319 Stark May 2016 A1
20160143593 Fu et al. May 2016 A1
20160151670 Dugan Jun 2016 A1
20160158534 Guarraia et al. Jun 2016 A1
20160166833 Bum Jun 2016 A1
20160166881 Ridgel et al. Jun 2016 A1
20160193306 Rabovsky et al. Jul 2016 A1
20160197918 Turgeman et al. Jul 2016 A1
20160213924 Coleman Jul 2016 A1
20160275259 Nolan et al. Sep 2016 A1
20160287166 Tran Oct 2016 A1
20160302666 Shaya Oct 2016 A1
20160302721 Wiedenhoefer et al. Oct 2016 A1
20160317869 Dugan Nov 2016 A1
20160322078 Bose et al. Nov 2016 A1
20160325140 Wu Nov 2016 A1
20160332028 Melnik Nov 2016 A1
20160345841 Jang et al. Dec 2016 A1
20160354636 Jang Dec 2016 A1
20160361025 Reicher et al. Dec 2016 A1
20160361597 Cole et al. Dec 2016 A1
20160373477 Moyle Dec 2016 A1
20170004260 Moturu et al. Jan 2017 A1
20170011179 Arshad et al. Jan 2017 A1
20170032092 Mink et al. Feb 2017 A1
20170033375 Ohmori et al. Feb 2017 A1
20170042467 Herr et al. Feb 2017 A1
20170046488 Pereira Feb 2017 A1
20170065851 Deluca et al. Mar 2017 A1
20170080320 Smith Mar 2017 A1
20170091422 Kumar et al. Mar 2017 A1
20170095670 Ghaffari et al. Apr 2017 A1
20170095692 Chang et al. Apr 2017 A1
20170095693 Chang et al. Apr 2017 A1
20170100637 Princen et al. Apr 2017 A1
20170106242 Dugan Apr 2017 A1
20170113092 Johnson Apr 2017 A1
20170128769 Long et al. May 2017 A1
20170132947 Maeda et al. May 2017 A1
20170136296 Barrera et al. May 2017 A1
20170143261 Wiedenhoefer et al. May 2017 A1
20170147752 Toru May 2017 A1
20170147789 Wiedenhoefer et al. May 2017 A1
20170148297 Ross May 2017 A1
20170168555 Munoz et al. Jun 2017 A1
20170181698 Wiedenhoefer et al. Jun 2017 A1
20170190052 Jaekel et al. Jul 2017 A1
20170202724 De Rossi Jul 2017 A1
20170209766 Riley et al. Jul 2017 A1
20170220751 Davis Aug 2017 A1
20170228517 Saliman et al. Aug 2017 A1
20170235882 Orlov et al. Aug 2017 A1
20170235906 Dorris et al. Aug 2017 A1
20170243028 LaFever et al. Aug 2017 A1
20170258370 Plotnik-Peleg et al. Sep 2017 A1
20170262604 Francois Sep 2017 A1
20170265800 Auchinleck et al. Sep 2017 A1
20170266501 Sanders et al. Sep 2017 A1
20170270260 Shetty Sep 2017 A1
20170278209 Olsen et al. Sep 2017 A1
20170282015 Wicks et al. Oct 2017 A1
20170283508 Demopulos et al. Oct 2017 A1
20170286621 Cox Oct 2017 A1
20170296861 Burkinshaw Oct 2017 A1
20170300654 Stein et al. Oct 2017 A1
20170304024 Nobrega Oct 2017 A1
20170312614 Tran et al. Nov 2017 A1
20170323481 Tran et al. Nov 2017 A1
20170329917 McRaith et al. Nov 2017 A1
20170329933 Brust Nov 2017 A1
20170333755 Rider Nov 2017 A1
20170337033 Duyan et al. Nov 2017 A1
20170337334 Stanczak Nov 2017 A1
20170344726 Duffy et al. Nov 2017 A1
20170347923 Roh Dec 2017 A1
20170360586 Dempers et al. Dec 2017 A1
20170368413 Shavit Dec 2017 A1
20180017806 Wang et al. Jan 2018 A1
20180036591 King et al. Feb 2018 A1
20180036593 Ridgel et al. Feb 2018 A1
20180052962 Van Der Koijk et al. Feb 2018 A1
20180056104 Cromie et al. Mar 2018 A1
20180056130 Bitran et al. Mar 2018 A1
20180060494 Dias et al. Mar 2018 A1
20180071565 Gomberg et al. Mar 2018 A1
20180071566 Gomberg et al. Mar 2018 A1
20180071569 Gomberg et al. Mar 2018 A1
20180071570 Gomberg et al. Mar 2018 A1
20180071571 Gomberg et al. Mar 2018 A1
20180071572 Gomberg et al. Mar 2018 A1
20180075205 Moturu et al. Mar 2018 A1
20180078843 Tran et al. Mar 2018 A1
20180085615 Astolfi et al. Mar 2018 A1
20180096111 Wells et al. Apr 2018 A1
20180099178 Schaefer et al. Apr 2018 A1
20180102190 Hogue et al. Apr 2018 A1
20180113985 Gandy et al. Apr 2018 A1
20180116741 Garcia Kilroy et al. May 2018 A1
20180117417 Davis May 2018 A1
20180130555 Chronis et al. May 2018 A1
20180140927 Kito May 2018 A1
20180146870 Shemesh May 2018 A1
20180177612 Trabish et al. Jun 2018 A1
20180178061 O'larte et al. Jun 2018 A1
20180199855 Odame et al. Jul 2018 A1
20180200577 Dugan Jul 2018 A1
20180220935 Tadano et al. Aug 2018 A1
20180228682 Bayerlein et al. Aug 2018 A1
20180232492 Al-Alul et al. Aug 2018 A1
20180236307 Hyde et al. Aug 2018 A1
20180240552 Tuyl et al. Aug 2018 A1
20180253991 Tang et al. Sep 2018 A1
20180255110 Dowlatkhah et al. Sep 2018 A1
20180256079 Yang et al. Sep 2018 A1
20180263530 Jung Sep 2018 A1
20180263535 Cramer Sep 2018 A1
20180263552 Graman et al. Sep 2018 A1
20180264312 Pompile et al. Sep 2018 A1
20180271432 Auchinleck et al. Sep 2018 A1
20180272184 Vassilaros et al. Sep 2018 A1
20180280784 Romeo et al. Oct 2018 A1
20180296143 Anderson et al. Oct 2018 A1
20180296157 Bleich et al. Oct 2018 A1
20180318122 LeCursi et al. Nov 2018 A1
20180326243 Badi et al. Nov 2018 A1
20180330058 Bates Nov 2018 A1
20180330810 Gamarnik Nov 2018 A1
20180330824 Athey et al. Nov 2018 A1
20180290017 Fung Dec 2018 A1
20180353812 Lannon et al. Dec 2018 A1
20180360340 Rehse et al. Dec 2018 A1
20180366225 Mansi Dec 2018 A1
20180373844 Ferrandez-Escamez et al. Dec 2018 A1
20190009135 Wu Jan 2019 A1
20190019163 Batey et al. Jan 2019 A1
20190019573 Lake et al. Jan 2019 A1
20190019578 Vaccaro Jan 2019 A1
20190030415 Volpe, Jr. Jan 2019 A1
20190031284 Fuchs Jan 2019 A1
20190046794 Goodall et al. Feb 2019 A1
20190060708 Fung Feb 2019 A1
20190065970 Bonutti et al. Feb 2019 A1
20190066832 Kang et al. Feb 2019 A1
20190076701 Dugan Mar 2019 A1
20190080802 Ziobro et al. Mar 2019 A1
20190083846 Eder Mar 2019 A1
20190088356 Oliver et al. Mar 2019 A1
20190090744 Mahfouz Mar 2019 A1
20190096534 Joao Mar 2019 A1
20190105551 Ray Apr 2019 A1
20190111299 Radcliffe et al. Apr 2019 A1
20190115097 Macoviak et al. Apr 2019 A1
20190117156 Howard et al. Apr 2019 A1
20190118038 Tana et al. Apr 2019 A1
20190126099 Hoang May 2019 A1
20190132948 Longinotti-Buitoni et al. May 2019 A1
20190134454 Mahoney et al. May 2019 A1
20190137988 Cella et al. May 2019 A1
20190143191 Ran et al. May 2019 A1
20190145774 Ellis May 2019 A1
20190163876 Remme et al. May 2019 A1
20190167988 Shahriari et al. Jun 2019 A1
20190172587 Park et al. Jun 2019 A1
20190175988 Volterrani et al. Jun 2019 A1
20190183715 Kapure et al. Jun 2019 A1
20190200920 Tien et al. Jul 2019 A1
20190209891 Fung Jul 2019 A1
20190214119 Wachira et al. Jul 2019 A1
20190223797 Tran Jul 2019 A1
20190224528 Omid-Zohoor et al. Jul 2019 A1
20190228856 Leifer Jul 2019 A1
20190232108 Kovach et al. Aug 2019 A1
20190240103 Hepler et al. Aug 2019 A1
20190240541 Denton et al. Aug 2019 A1
20190244540 Errante et al. Aug 2019 A1
20190251456 Constantin Aug 2019 A1
20190261959 Frankel Aug 2019 A1
20190262084 Roh Aug 2019 A1
20190269343 Ramos Murguialday et al. Sep 2019 A1
20190274523 Bates et al. Sep 2019 A1
20190275368 Maroldi Sep 2019 A1
20190304584 Savolainen Oct 2019 A1
20190307983 Goldman Oct 2019 A1
20190314681 Yang Oct 2019 A1
20190344123 Rubin et al. Nov 2019 A1
20190354632 Mital et al. Nov 2019 A1
20190362242 Pillai et al. Nov 2019 A1
20190366146 Tong et al. Dec 2019 A1
20190385199 Bender et al. Dec 2019 A1
20190388728 Wang et al. Dec 2019 A1
20190392936 Arric et al. Dec 2019 A1
20190392939 Basta et al. Dec 2019 A1
20200005928 Daniel Jan 2020 A1
20200034707 Kivatinos et al. Jan 2020 A1
20200038703 Cleary et al. Feb 2020 A1
20200051446 Rubinstein et al. Feb 2020 A1
20200066390 Svendrys et al. Feb 2020 A1
20200085300 Kwatra et al. Mar 2020 A1
20200090802 Maron Mar 2020 A1
20200093418 Kluger et al. Mar 2020 A1
20200143922 Chekroud et al. May 2020 A1
20200151595 Jayalath et al. May 2020 A1
20200151646 De La Fuente Sanchez May 2020 A1
20200152339 Pulitzer et al. May 2020 A1
20200160198 Reeves et al. May 2020 A1
20200170876 Kapure et al. Jun 2020 A1
20200176098 Lucas et al. Jun 2020 A1
20200197744 Schweighofer Jun 2020 A1
20200221975 Basta et al. Jul 2020 A1
20200237291 Raja Jul 2020 A1
20200237452 Wolf et al. Jul 2020 A1
20200267487 Siva Aug 2020 A1
20200275886 Mason Sep 2020 A1
20200289045 Hacking et al. Sep 2020 A1
20200289046 Hacking et al. Sep 2020 A1
20200289879 Hacking et al. Sep 2020 A1
20200289880 Hacking et al. Sep 2020 A1
20200289881 Hacking et al. Sep 2020 A1
20200289889 Hacking et al. Sep 2020 A1
20200293712 Potts et al. Sep 2020 A1
20200303063 Sharma et al. Sep 2020 A1
20200312447 Bohn et al. Oct 2020 A1
20200334972 Gopalakrishnan Oct 2020 A1
20200353314 Messinger Nov 2020 A1
20200357299 Patel et al. Nov 2020 A1
20200365256 Hayashitani et al. Nov 2020 A1
20200395112 Ronner Dec 2020 A1
20200398083 Al-Alul et al. Dec 2020 A1
20200401224 Cotton Dec 2020 A1
20200402662 Esmailian et al. Dec 2020 A1
20200410374 White Dec 2020 A1
20200410385 Otsuki Dec 2020 A1
20200411162 Lien et al. Dec 2020 A1
20210005224 Rothschild et al. Jan 2021 A1
20210005319 Otsuki et al. Jan 2021 A1
20210008413 Asikainen et al. Jan 2021 A1
20210015560 Boddington et al. Jan 2021 A1
20210027889 Neil et al. Jan 2021 A1
20210035674 Volosin et al. Feb 2021 A1
20210050086 Rose et al. Feb 2021 A1
20210065855 Pepin et al. Mar 2021 A1
20210074178 Ilan et al. Mar 2021 A1
20210076981 Hacking et al. Mar 2021 A1
20210077860 Posnack et al. Mar 2021 A1
20210077884 De Las Casas Zolezzi et al. Mar 2021 A1
20210082554 Kalia et al. Mar 2021 A1
20210093891 Sheng Apr 2021 A1
20210098129 Neumann Apr 2021 A1
20210101051 Posnack et al. Apr 2021 A1
20210113890 Posnack et al. Apr 2021 A1
20210125696 Liu et al. Apr 2021 A1
20210127974 Mason et al. May 2021 A1
20210128080 Mason et al. May 2021 A1
20210128255 Mason et al. May 2021 A1
20210128978 Gilstrom et al. May 2021 A1
20210134412 Guaneri et al. May 2021 A1
20210134425 Mason et al. May 2021 A1
20210134428 Mason et al. May 2021 A1
20210134430 Mason et al. May 2021 A1
20210134432 Mason et al. May 2021 A1
20210134456 Posnack et al. May 2021 A1
20210134457 Mason et al. May 2021 A1
20210134458 Mason et al. May 2021 A1
20210134463 Mason et al. May 2021 A1
20210138304 Mason et al. May 2021 A1
20210142875 Mason et al. May 2021 A1
20210142893 Guaneri et al. May 2021 A1
20210142898 Mason et al. May 2021 A1
20210142903 Mason et al. May 2021 A1
20210144074 Guaneri et al. May 2021 A1
20210186419 Van Ee et al. Jun 2021 A1
20210187348 Phillips et al. Jun 2021 A1
20210202090 ODonovan et al. Jul 2021 A1
20210202103 Bostic et al. Jul 2021 A1
20210236020 Matijevich et al. Aug 2021 A1
20210244998 Hacking et al. Aug 2021 A1
20210245003 Turner Aug 2021 A1
20210251562 Jain Aug 2021 A1
20210272677 Barbee Sep 2021 A1
20210338469 Dempers Nov 2021 A1
20210343384 Purushothaman et al. Nov 2021 A1
20210345879 Mason et al. Nov 2021 A1
20210345975 Mason et al. Nov 2021 A1
20210350888 Guaneri et al. Nov 2021 A1
20210350898 Mason et al. Nov 2021 A1
20210350899 Mason et al. Nov 2021 A1
20210350901 Mason et al. Nov 2021 A1
20210350902 Mason et al. Nov 2021 A1
20210350914 Guaneri et al. Nov 2021 A1
20210350926 Mason et al. Nov 2021 A1
20210361514 Choi et al. Nov 2021 A1
20210366587 Mason et al. Nov 2021 A1
20210383909 Mason et al. Dec 2021 A1
20210391091 Mason Dec 2021 A1
20210398668 Chock et al. Dec 2021 A1
20210407670 Mason et al. Dec 2021 A1
20210407681 Mason et al. Dec 2021 A1
20220000556 Casey et al. Jan 2022 A1
20220015838 Posnack et al. Jan 2022 A1
20220016480 Bissonnette et al. Jan 2022 A1
20220016482 Bissonnette Jan 2022 A1
20220016485 Bissonnette et al. Jan 2022 A1
20220016486 Bissonnette Jan 2022 A1
20220020469 Tanner Jan 2022 A1
20220044806 Sanders et al. Feb 2022 A1
20220047921 Bissonnette et al. Feb 2022 A1
20220079690 Mason et al. Mar 2022 A1
20220080256 Arn et al. Mar 2022 A1
20220080265 Watterson Mar 2022 A1
20220105384 Hacking et al. Apr 2022 A1
20220105385 Hacking et al. Apr 2022 A1
20220105390 Yuasa Apr 2022 A1
20220115133 Mason et al. Apr 2022 A1
20220118218 Bense et al. Apr 2022 A1
20220122724 Durlach et al. Apr 2022 A1
20220126169 Mason Apr 2022 A1
20220133576 Choi et al. May 2022 A1
20220148725 Mason et al. May 2022 A1
20220176039 Lintereur et al. Jun 2022 A1
20220181004 Zilca et al. Jun 2022 A1
20220193491 Mason et al. Jun 2022 A1
20220230729 Mason Jul 2022 A1
20220238222 Neuberg Jul 2022 A1
20220238223 Mason et al. Jul 2022 A1
20220258935 Kraft Aug 2022 A1
20220262483 Rosenberg et al. Aug 2022 A1
20220262504 Bratty et al. Aug 2022 A1
20220266094 Mason et al. Aug 2022 A1
20220270738 Mason et al. Aug 2022 A1
20220273985 Jeong et al. Sep 2022 A1
20220273986 Mason Sep 2022 A1
20220288460 Mason Sep 2022 A1
20220288461 Ashley et al. Sep 2022 A1
20220288462 Ashley et al. Sep 2022 A1
20220293257 Guaneri et al. Sep 2022 A1
20220300787 Wall et al. Sep 2022 A1
20220304881 Choi et al. Sep 2022 A1
20220304882 Choi Sep 2022 A1
20220305328 Choi et al. Sep 2022 A1
20220314072 Bissonnette et al. Oct 2022 A1
20220314075 Mason et al. Oct 2022 A1
20220323826 Khurana Oct 2022 A1
20220327714 Cook et al. Oct 2022 A1
20220327807 Cook et al. Oct 2022 A1
20220328181 Mason et al. Oct 2022 A1
20220330823 Janssen Oct 2022 A1
20220331663 Mason Oct 2022 A1
20220338761 Maddahi et al. Oct 2022 A1
20220339052 Kim Oct 2022 A1
20220339501 Mason et al. Oct 2022 A1
20220370851 Guidarelli et al. Nov 2022 A1
20220384012 Mason Dec 2022 A1
20220392591 Guaneri et al. Dec 2022 A1
20220395232 Locke Dec 2022 A1
20220401783 Choi Dec 2022 A1
20220415469 Mason Dec 2022 A1
20220415471 Mason Dec 2022 A1
20230001268 Bissonnette et al. Jan 2023 A1
20230013530 Mason Jan 2023 A1
20230014598 Mason et al. Jan 2023 A1
20230029639 Roy Feb 2023 A1
20230047253 Gnanasambandam et al. Feb 2023 A1
20230048040 Hacking et al. Feb 2023 A1
20230051751 Hacking et al. Feb 2023 A1
20230058605 Mason Feb 2023 A1
20230060039 Mason Feb 2023 A1
20230072368 Mason Mar 2023 A1
20230078793 Mason Mar 2023 A1
20230119461 Mason Apr 2023 A1
20230190100 Stump Jun 2023 A1
20230201656 Hacking et al. Jun 2023 A1
20230207097 Mason Jun 2023 A1
20230207124 Walsh et al. Jun 2023 A1
20230215539 Rosenberg et al. Jul 2023 A1
20230215552 Khotilovich et al. Jul 2023 A1
20230218950 Belson et al. Jul 2023 A1
20230245747 Rosenberg et al. Aug 2023 A1
20230245748 Rosenberg et al. Aug 2023 A1
20230245750 Rosenberg et al. Aug 2023 A1
20230245751 Rosenberg et al. Aug 2023 A1
20230253089 Rosenberg et al. Aug 2023 A1
20230255555 Sundaram et al. Aug 2023 A1
20230263428 Hull et al. Aug 2023 A1
20230274813 Rosenberg et al. Aug 2023 A1
20230282329 Mason et al. Sep 2023 A1
20230364472 Posnack Nov 2023 A1
20230368886 Rosenberg Nov 2023 A1
20230377710 Chen et al. Nov 2023 A1
20230377711 Rosenberg Nov 2023 A1
20230377712 Rosenberg Nov 2023 A1
20230386639 Rosenberg Nov 2023 A1
20230395231 Rosenberg Dec 2023 A1
20230395232 Rosenberg Dec 2023 A1
20240029856 Rosenberg Jan 2024 A1
Foreign Referenced Citations (287)
Number Date Country
3193419 Mar 2022 CA
2885238 Apr 2007 CN
101964151 Feb 2011 CN
201889024 Jul 2011 CN
202220794 May 2012 CN
102670381 Sep 2012 CN
103263336 Aug 2013 CN
103390357 Nov 2013 CN
103473631 Dec 2013 CN
103488880 Jan 2014 CN
103501328 Jan 2014 CN
103721343 Apr 2014 CN
203677851 Jul 2014 CN
104335211 Feb 2015 CN
105620643 Jun 2016 CN
105683977 Jun 2016 CN
103136447 Aug 2016 CN
105894088 Aug 2016 CN
105930668 Sep 2016 CN
205626871 Oct 2016 CN
106127646 Nov 2016 CN
106236502 Dec 2016 CN
106510985 Mar 2017 CN
106621195 May 2017 CN
107066819 Aug 2017 CN
107430641 Dec 2017 CN
107551475 Jan 2018 CN
107736982 Feb 2018 CN
107930021 Apr 2018 CN
108078737 May 2018 CN
208224811 Dec 2018 CN
109191954 Jan 2019 CN
109363887 Feb 2019 CN
208573971 Mar 2019 CN
110148472 Aug 2019 CN
110201358 Sep 2019 CN
110215188 Sep 2019 CN
110322957 Oct 2019 CN
110808092 Feb 2020 CN
110931103 Mar 2020 CN
110993057 Apr 2020 CN
111105859 May 2020 CN
111111110 May 2020 CN
111370088 Jul 2020 CN
111460305 Jul 2020 CN
111790111 Oct 2020 CN
112071393 Dec 2020 CN
212141371 Dec 2020 CN
112289425 Jan 2021 CN
212624809 Feb 2021 CN
112603295 Apr 2021 CN
213190965 May 2021 CN
113384850 Sep 2021 CN
113499572 Oct 2021 CN
215136488 Dec 2021 CN
113885361 Jan 2022 CN
114049961 Feb 2022 CN
114203274 Mar 2022 CN
216258145 Apr 2022 CN
114632302 Jun 2022 CN
114694824 Jul 2022 CN
114898832 Aug 2022 CN
114983760 Sep 2022 CN
217472652 Sep 2022 CN
110270062 Oct 2022 CN
218420859 Feb 2023 CN
115954081 Apr 2023 CN
95019 Jan 1897 DE
7628633 Dec 1977 DE
8519150 Oct 1985 DE
3732905 Jul 1988 DE
19619820 Dec 1996 DE
29620008 Feb 1997 DE
19947926 Apr 2001 DE
102018202497 Aug 2018 DE
102018211212 Jan 2019 DE
102019108425 Aug 2020 DE
199600 Oct 1986 EP
0383137 Aug 1990 EP
634319 Jan 1995 EP
0919259 Jun 1999 EP
1034817 Sep 2000 EP
1159989 Dec 2001 EP
1391179 Feb 2004 EP
1968028 Sep 2008 EP
2564904 Mar 2013 EP
2575064 Apr 2013 EP
1909730 Apr 2014 EP
2815242 Dec 2014 EP
2869805 May 2015 EP
2997951 Mar 2016 EP
2688472 Apr 2016 EP
3264303 Jan 2018 EP
3323473 May 2018 EP
3547322 Oct 2019 EP
3627514 Mar 2020 EP
3671700 Jun 2020 EP
3688537 Aug 2020 EP
3731733 Nov 2020 EP
3984508 Apr 2022 EP
3984509 Apr 2022 EP
3984510 Apr 2022 EP
3984511 Apr 2022 EP
3984512 Apr 2022 EP
3984513 Apr 2022 EP
4054699 Sep 2022 EP
4112033 Jan 2023 EP
2527541 Dec 1983 FR
3127393 Mar 2023 FR
141664 Nov 1920 GB
2336140 Oct 1999 GB
2372459 Aug 2002 GB
2512431 Oct 2014 GB
2591542 Mar 2022 GB
201811043670 Jul 2018 IN
2000005339 Jan 2000 JP
2003225875 Aug 2003 JP
2005227928 Aug 2005 JP
2005227928 Aug 2005 JP
2009112336 May 2009 JP
2013515995 May 2013 JP
2014104139 Jun 2014 JP
3193662 Oct 2014 JP
3198173 Jun 2015 JP
5804063 Nov 2015 JP
2018102842 Jul 2018 JP
2019028647 Feb 2019 JP
2019134909 Aug 2019 JP
6573739 Sep 2019 JP
6659831 Mar 2020 JP
2020057082 Apr 2020 JP
6710357 Jun 2020 JP
6775757 Oct 2020 JP
2021027917 Feb 2021 JP
6871379 May 2021 JP
2022521378 Apr 2022 JP
3238491 Jul 2022 JP
7198364 Dec 2022 JP
7202474 Jan 2023 JP
7231750 Mar 2023 JP
7231751 Mar 2023 JP
7231752 Mar 2023 JP
20020009724 Feb 2002 KR
200276919 May 2002 KR
20020065253 Aug 2002 KR
100582596 May 2006 KR
101042258 Jun 2011 KR
101258250 Apr 2013 KR
101325581 Nov 2013 KR
20140128630 Nov 2014 KR
20150017693 Feb 2015 KR
20150078191 Jul 2015 KR
101580071 Dec 2015 KR
101647620 Aug 2016 KR
20160093990 Aug 2016 KR
20170038837 Apr 2017 KR
20180004928 Jan 2018 KR
20190029175 Mar 2019 KR
20190056116 May 2019 KR
101988167 Jun 2019 KR
101969392 Aug 2019 KR
102055279 Dec 2019 KR
102088333 Mar 2020 KR
20200025290 Mar 2020 KR
20200029180 Mar 2020 KR
102097190 Apr 2020 KR
102116664 May 2020 KR
102116968 May 2020 KR
20200056233 May 2020 KR
102120828 Jun 2020 KR
102121586 Jun 2020 KR
102142713 Aug 2020 KR
102162522 Oct 2020 KR
20200119665 Oct 2020 KR
102173553 Nov 2020 KR
102180079 Nov 2020 KR
102188766 Dec 2020 KR
102196793 Dec 2020 KR
20210006212 Jan 2021 KR
102224188 Mar 2021 KR
102224618 Mar 2021 KR
102246049 Apr 2021 KR
102246050 Apr 2021 KR
102246051 Apr 2021 KR
102246052 Apr 2021 KR
20210052028 May 2021 KR
102264498 Jun 2021 KR
102352602 Jan 2022 KR
102352603 Jan 2022 KR
102352604 Jan 2022 KR
20220004639 Jan 2022 KR
102387577 Apr 2022 KR
102421437 Jul 2022 KR
20220102207 Jul 2022 KR
102427545 Aug 2022 KR
102467495 Nov 2022 KR
102467496 Nov 2022 KR
102469723 Nov 2022 KR
102471990 Nov 2022 KR
20220145989 Nov 2022 KR
20220156134 Nov 2022 KR
102502744 Feb 2023 KR
20230019349 Feb 2023 KR
20230019350 Feb 2023 KR
20230026556 Feb 2023 KR
20230026668 Feb 2023 KR
20230040526 Mar 2023 KR
20230050506 Apr 2023 KR
20230056118 Apr 2023 KR
102528503 May 2023 KR
102531930 May 2023 KR
102532766 May 2023 KR
102539190 Jun 2023 KR
2014131288 Feb 2016 RU
2607953 Jan 2017 RU
M474545 Mar 2014 TW
I442956 Jul 2014 TW
M638437 Mar 2023 TW
1998009687 Mar 1998 WO
0149235 Jul 2001 WO
0151083 Jul 2001 WO
2001050387 Jul 2001 WO
2001056465 Aug 2001 WO
02062211 Aug 2002 WO
02093312 Nov 2002 WO
2003043494 May 2003 WO
2005018453 Mar 2005 WO
2006004430 Jan 2006 WO
2006012694 Feb 2006 WO
2007102709 Sep 2007 WO
2008114291 Sep 2008 WO
2009003170 Dec 2008 WO
2009008968 Jan 2009 WO
2011025322 Mar 2011 WO
2012128801 Sep 2012 WO
2013002568 Jan 2013 WO
2023164292 Mar 2013 WO
2013122839 Aug 2013 WO
2014011447 Jan 2014 WO
2014163976 Oct 2014 WO
2015026744 Feb 2015 WO
2015065298 May 2015 WO
2015082555 Jun 2015 WO
2016151364 Sep 2016 WO
2016154318 Sep 2016 WO
2017030781 Feb 2017 WO
2017166074 May 2017 WO
2017091691 Jun 2017 WO
2017165238 Sep 2017 WO
2018081795 May 2018 WO
2018171853 Sep 2018 WO
2019022706 Jan 2019 WO
2019143940 Jul 2019 WO
2020075190 Apr 2020 WO
2020130979 Jun 2020 WO
2020149815 Jul 2020 WO
2020229705 Nov 2020 WO
2020245727 Dec 2020 WO
2020249855 Dec 2020 WO
2020252599 Dec 2020 WO
2020256577 Dec 2020 WO
2021021447 Feb 2021 WO
2021022003 Feb 2021 WO
2021038980 Mar 2021 WO
2021055427 Mar 2021 WO
2021061061 Apr 2021 WO
2021090267 May 2021 WO
2021138620 Jul 2021 WO
2021216881 Oct 2021 WO
2021236961 Nov 2021 WO
2022047006 Mar 2022 WO
2022092493 May 2022 WO
2022092494 May 2022 WO
2022212883 Oct 2022 WO
2022212921 Oct 2022 WO
2022216498 Oct 2022 WO
2022251420 Dec 2022 WO
2023008680 Feb 2023 WO
2023008681 Feb 2023 WO
2023022319 Feb 2023 WO
2023022320 Feb 2023 WO
2023052695 Apr 2023 WO
2023091496 May 2023 WO
2023215155 Nov 2023 WO
2023230075 Nov 2023 WO
2024013267 Jan 2024 WO
2024107807 May 2024 WO
Non-Patent Literature Citations (72)
Entry
Alcaraz et al., “Machine Learning as Digital Therapy Assessment for Mobile Gait Rehabilitation,” 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), Aalborg, Denmark, 2018, 6 pages.
Androutsou et al., “A Smartphone Application Designed to Engage the Elderly in Home-Based Rehabilitation,” Frontiers in Digital Health, Sep. 2020, vol. 2, Article 15, 13 pages.
Silva et al., “SapoFitness: A mobile health application for dietary evaluation,” 2011 IEEE 13th International Conference on U e-Health Networking, Applications and Services, Columbia, MO, USA, 2011, 6 pages.
Wang et al., “Interactive wearable systems for upper body rehabilitation: a systematic review,” Journal of NeuroEngineering and Rehabilitation, 2017, 21 pages.
Marzolini et al., “Eligibility, Enrollment, and Completion of Exercise-Based Cardiac Rehabilitation Following Stroke Rehabilitation: What Are the Barriers?,” Physical Therapy, vol. 100, No. 1, 2019, 13 pages.
Nijjar et al., “Randomized Trial of Mindfulness-Based Stress Reduction in Cardiac Patients Eligible for Cardiac Rehabilitation,” Scientific Reports, 2019, 12 pages.
Lara et al., “Human-Robot Sensor Interface for Cardiac Rehabilitation,” IEEE International Conference on Rehabilitation Robotics, Jul. 2017, 8 pages.
Ishraque et al., “Artificial Intelligence-Based Rehabilitation Therapy Exercise Recommendation System,” 2018 IEEE MIT Undergraduate Research Technology Conference (URTC), Cambridge, MA, USA, 2018, 5 pages.
Zakari et al., “Are There Limitations to Exercise Benefits in Peripheral Arterial Disease?,” Frontiers in Cardiovascular Medicine, Nov. 2018, vol. 5, Article 173, 12 pages.
You et al., “Including Blood Vasculature into a Game-Theoretic Model of Cancer Dynamics,” Games 2019, 10, 13, 22 pages.
Jeong et al., “Computer-assisted upper extremity training using interactive biking exercise (iBikE) platform,” Sep. 2012, 34th Annual International Conference of the IEEE EMBS, 5 pages.
Barrett et al., “Artificial intelligence supported patient self-care in chronic heart failure: a paradigm shift from reactive to predictive, preventive and personalised care,” EPMA Journal (2019), pp. 445-464.
Oerkild et al., “Home-based cardiac rehabilitation is an attractive alternative to no cardiac rehabilitation for elderly patients with coronary heart disease: results from a randomised clinical trial,” BMJ Open Accessible Medical Research, Nov. 22, 2012, pp. 1-9.
Bravo-Escobar et al., “Effectiveness and safety of a home-based cardiac rehabilitation programme of mixed surveillance in patients with ischemic heart disease at moderate cardiovascular risk: A randomised, controlled clinical trial,” BMC Cardiovascular Disorders, 2017, pp. 1-11, vol. 17:66.
Thomas et al., “Home-Based Cardiac Rehabilitation,” Circulation, 2019, pp. e69-e89, vol. 140.
Thomas et al., “Home-Based Cardiac Rehabilitation,” Journal of the American College of Cardiology, Nov. 1, 2019, pp. 133-153, vol. 74.
Thomas et al., “Home-Based Cardiac Rehabilitation,” HHS Public Access, Oct. 2, 2020, pp. 1-39.
Dittus et al., “Exercise-Based Oncology Rehabilitation: Leveraging the Cardiac Rehabilitation Model,” Journal of Cardiopulmonary Rehabilitation and Prevention, 2015, pp. 130-139, vol. 35.
Chen et al., “Home-based cardiac rehabilitation improves quality of life, aerobic capacity, and readmission rates in patients with chronic heart failure,” Medicine, 2018, pp. 1-5 vol. 97:4.
Lima de Melo Ghisi et al., “A systematic review of patient education in cardiac patients: Do they increase knowledge and promote health behavior change?,” Patient Education and Counseling, 2014, pp. 1-15.
Fang et al., “Use of Outpatient Cardiac Rehabilitation Among Heart Attack Survivors—20 States and the District of Columbia, 2013 and Four States, 2015,” Morbidity and Mortality Weekly Report, vol. 66, No. 33, Aug. 25, 2017, pp. 869-873.
Beene et al., “AI and Care Delivery: Emerging Opportunities for Artificial Intelligence to Transform How Care Is Delivered,” Nov. 2019, American Hospital Association, pp. 1-12.
Chrif et al., “Control design for a lower-limb paediatric therapy device using linear motor technology,” Article, 2017, pp. 119-127, Science Direct, Switzerland.
Robben et al., “Delta Features From Ambient Sensor Data are Good Predictors of Change in Functional Health,” Article, 2016, pp. 2168-2194, vol. 21, No. 4, IEEE Journal of Biomedical and Health Informatics.
Kantoch et al., “Recognition of Sedentary Behavior by Machine Learning Analysis of Wearable Sensors during Activities of Daily Living for Telemedical Assessment of Cardiovascular Risk,” Article, 2018, 17 pages, Sensors, Poland.
Warburton et al., “International Launch of the PAR-⋅Q+ and ePARmed-⋅X+ Validation of the PAR-⋅Q+ and ePARmed⋅⋅X+,” Health & Fitness Journal of Canada, 2011, 9 pages, vol. 4, No. 2.
Malloy, Online Article “AI-enabled EKGs find difference between numerical age and biological age significantly affects health, longevity”, Website: https://newsnetwork.mayoclinic.org/discussion/ai-enabled-ekgs-find-difference-between-numerical-age-and-biological-age-significantly-affects-health-longevity/, Mayo Clinic News Network, May 20, 2021, retrieved: Jan. 23, 2023, p. 1-4.
Davenport et al., “The Potential for Artificial Intelligence In Healthcare”, 2019, Future Healthcare Journal 2019, vol. 6, No. 2: Year: 2019, pp. 1-5.
Ahmed et al., “Artificial Intelligence With Multi-Functional Machine Learning Platform Development for Better Healthcare and Precision Medicine”, 2020, Database (Oxford), 2020:baaa010. doi: 10.1093/database/baaa010 (Year: 2020), pp. 1-35.
Ruiz Ivan et al., “Towards a physical rehabilitation system using a telemedicine approach”, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol. 8, No. 6, Jul. 28, 2020, pp. 671-680, XP055914810.
De Canniere Helene et al., “Wearable Monitoring and Interpretable Machine Learning Can Objectively Track Progression in Patients during Cardiac Rehabilitation”, Sensors, vol. 20, No. 12, Jun. 26, 2020, XP055914617, pp. 1-15.
Boulanger Pierre et al., “A Low-cost Virtual Reality Bike for Remote Cardiac Rehabilitation”, Dec. 7, 2017, Advances in Biometrics: International Conference, ICB 2007, Seoul, Korea, pp. 155-166.
Yin Chieh et al., “A Virtual Reality-Cycling Training System for Lower Limb Balance Improvement”, BioMed Research International, vol. 2016, pp. 1-10.
Gerbild et al., “Physical Activity to Improve Erectile Dysfunction: A Systematic Review of Intervention Studies,” Sexual Medicine, 2018, 15 pages.
Jeong et al., “Computer-assisted upper extremity training using interactive biking exercise (iBikE) platform,” Sep. 2012, pp. 1-5, 34th Annual International Conference of the IEEE EMBS.
International Search Report and Written Opinion for PCT/US2023/014137, dated Jun. 9, 2023, 13 pages.
Website for “Esino 2022 Physical Therapy Equipments Arm Fitness Indoor Trainer Leg Spin Cycle Machine Exercise Bike for Elderly,” https://www.made-in-china.com/showroom/esinogroup/product-detailYdZlwGhCMKVR/China-Esino-2022-Physical-Therapy-Equipments-Arm-Fitness-Indoor-Trainer-Leg-Spin-Cycle-Machine-Exercise-Bike-for-Elderly.html, retrieved on Aug. 29, 2023, 5 pages.
Abedtash, “An Interoperable Electronic Medical Record-Based Platform for Personalized Predictive Analytics”, ProQuest LLC, Jul. 2017, 185 pages.
Claris Healthcare Inc., Claris Reflex Patient Rehabilitation System Brochure, retrieved on Oct. 2, 2019, 5 bages, https://clarisreflex.com/.
Fysiomed, 16983—Vario adjustable pedal arms, retrieved from timestamp of Jun. 7, 2017 from https://web.archive.org/web/20160607052632/https://www.fysiomed.com/en/products/16983-vario-adjustable-pedal-arms on Dec. 15, 2021, 4 pages.
HCL Fitness, HCI Fitness PhysioTrainer Upper Body Ergonometer, announced 2009 [online], retrieved on Aug. 19, 2021, 8 pages, www.amazon.com/HCI-Fitness-PhysioTrainer-Upper-Ergonometer/dp/B001 P5GUGM.
HCL Fitness, HCI Fitness PhysioTrainer Pro, 2017, retrieved on Aug. 19, 2021, 7 pages, https://www.amazon.com/HCI-Fitness-Physio Trainer-Electronically-Controlled/dp/B0759YMW78/.
International Preliminary Report on Patentability of International Application No. PCT/US2017/50895, Date of Mailing Dec. 11, 2018, 52 pages.
International Searching Authority, Search Report and Written Opinion for International Application No. PCT/US2017/50895, Date of Mailing Jan. 12, 2018, 6 pages.
International Searching Authority, Search Report and Written Opinion for International Application No. PCT/US2020/021876, Date of Mailing May 28, 2020, 8 pages.
International Searching Authority, Search Report and Written Opinion for International Application No. PCT/US2020/051008, Date of Mailing Dec. 10, 2020, 9 pages.
International Searching Authority, Search Report and Written Opinion for International Application No. PCT/US2020/056661, Date of Mailing Feb. 12, 2021, 12 pages.
Matrix, R3xm Recumbent Cycle, retrieved on Aug. 4, 2020, 7 pages, https://www.matrixfitness.com/en/cardio/cycles/r3xm-recumbent.
ROM3 Rehab, ROM3 Rehab System, Apr. 20, 2015, retrieved on Aug. 31, 2018, 12 pages, https://vimeo.com/125438463.
International Searching Authority, Search Report and Written Opinion for International Application No. PCT/US2021/032807, Date of Mailing Sep. 6, 2021, 11 pages.
Jennifer Bresnick, “What is the Role of Natural Language Processing in Healthcare?”, pp. 1-7, published Aug. 18, 2016, retrieved on Feb. 1, 2022 from https://healthitanalytics.com/ featu res/what-is-the-role-of-natural-language-processing-in-healthcare.
Alex Bellec, “Part-of-Speech tagging tutorial with the Keras Deep Learning library,” pp. 1-16, published Mar. 27, 2018, retrieved on Feb. 1, 2022 from https://becominghuman.ai/part-of-speech-tagging-tutorial-with-the-keras-deep-learning-library-d7f93fa05537.
Kavita Ganesan, All you need to know about text preprocessing for NLP and Machine Learning, pp. 1-14, published Feb. 23, 2019, retrieved on Feb. 1, 2022 from https:// towardsdatascience.com/all-you-need-to-know-about-text-preprocessing-for-nlp-and-machine-learning-bcl c5765ff67.
Badreesh Shetty, “Natural Language Processing (NPL) for Machine Learning,” pp. 1-13, published Nov. 24, 2018, retrieved on Feb. 1, 2022 from https://towardsdatascience. com/natural-language-processing-nlp-for-machine-learning-d44498845d5b.
Website for “Pedal Exerciser”, p. 1, retrieved on Sep. 9, 2022 from https://www.vivehealth.com/collections/physical-therapy-equipment/products/pedalexerciser.
Website for “Functional Knee Brace with ROM”, p. 1, retrieved on Sep. 9, 2022 from http://medicalbrace.gr/en/product/functional-knee-brace-with-goniometer-mbtelescopicknee/.
Website for “ComfySplints Goniometer Knee”, pp. 1-5, retrieved on Sep. 9, 2022 from https://www.comfysplints.com/product/knee-splints/.
Website for “BMI FlexEze Knee Corrective Orthosis (KCO)”, pp. 1-4, retrieved on Sep. 9, 2022 from https://orthobmi.com/products/bmi-flexeze%C2%AE-knee-corrective-orthosis-kco.
Website for “Neoprene Knee Brace with goniometer—Patella Rom MB.4070”, pp. 1-4, retrieved on Sep. 9, 2022 from https://www.fortuna.com.gr/en/product/neoprene-knee-brace-with-goniometer-patella-rom-mb-4070/.
Kuiken et al., “Computerized Biofeedback Knee Goniometer: Acceptance and Effect on Exercise Behavior in Post-total Knee Arthroplasty Rehabilitation,” Biomedical Engineering Faculty Research and Publications, 2004, pp. 1-10.
Ahmed et al., “Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine,” Database, 2020, pp. 1-35.
Davenport et al., “The potential for artificial intelligence in healthcare,” Digital Technology, Future Healthcare Journal, 2019, pp. 1-5, vol. 6, No. 2.
Website for “OxeFit XS1”, pp. 1-3, retrieved on Sep. 9, 2022 from https://www.oxefit.com/xs1.
Website for “Preva Mobile”, pp. 1-6, retrieved on Sep. 9, 2022 from https://www.precor.com/en-us/resources/introducing-preva-mobile.
Website for “J-Bike”, pp. 1-3, retrieved on Sep. 9, 2022 from https://www.magneticdays.com/en/cycling-for-physical-rehabilitation.
Website for “Excy”, pp. 1-12, retrieved on Sep. 9, 2022 from https://excy.com/portable-exercise-rehabilitation-excy-xcs-pro/.
Website for “OxeFit XP1”, p. 1, retrieved on Sep. 9, 2022 from https://www.oxefit.com/xp1.
Jeong et al., “Remotely controlled biking is associated with improved adherence to prescribed cycling speed,” Technology and Health Care 23, 2015, 7 pages.
Laustsen et al., “Telemonitored exercise-based cardiac rehabilitation improves physical capacity and health-related quality of life,” Journal of Telemedicine and Telecare, 2020, DOI: 10.1177/1357633X18792808, 9 pages.
Blasiak et al., “CURATE.AI: Optimizing Personalized Medicine with Artificial Intelligence,”SLAS TECHNOLOGY: Translating Life Sciences Innovation, 2020, 11 pages.
Ahmed et al., “Artificial Intelligence With Multi-Functional Machine Learning Platform Development for Better Healthcare and Precision Medicine,” Database (Oxford), 2020, pp. 1-35, vol. 2020.
Davenport et al., “The Potential for Artificial Intelligence in Healthcare,” Future Healthcare Journal, 2019, pp. 94-98, vol. 6, No. 2.
Related Publications (1)
Number Date Country
20220158916 A1 May 2022 US
Provisional Applications (2)
Number Date Country
63028399 May 2020 US
62910232 Oct 2019 US
Continuations (1)
Number Date Country
Parent 17149457 Jan 2021 US
Child 17589409 US
Continuation in Parts (1)
Number Date Country
Parent 17021895 Sep 2020 US
Child 17149457 US