Non-line-of-sight radar-based gesture recognition

Information

  • Patent Grant
  • 10664059
  • Patent Number
    10,664,059
  • Date Filed
    Monday, March 20, 2017
    7 years ago
  • Date Issued
    Tuesday, May 26, 2020
    4 years ago
Abstract
This document describes techniques and devices for non-line-of-sight radar-based gesture recognition. Through use of the techniques and devices described herein, users may control their devices through in-the-air gestures, even when those gestures are not within line-of-sight of their device's sensors. Thus, the techniques enable users to control their devices in many situations in which control is desired but conventional techniques do permit effective control, such as to turn the temperature down in a room when the user is obscured from a thermostat's gesture sensor, turn up the volume on a media player when the user is in a different room than the media player, or pause a television program when the user's gesture is obscured by a chair, couch, or other obstruction.
Description
BACKGROUND

As smart devices proliferate in homes, automobiles, and offices, the need to seamlessly and intuitively control these devices becomes increasingly important. For example, users desire to quickly and easily control their media players, televisions, and climate devices from wherever they happen to be. Current techniques for controlling smart devices, however, fail to provide seamless and intuitive control, instead relying on touch screens, hand-held remote controls, and clumsy audio interfaces.


This background description is provided for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, material described in this section is neither expressly nor impliedly admitted to be prior art to the present disclosure or the appended claims.


SUMMARY

This document describes techniques and devices for non-line-of-sight radar-based gesture recognition. Through use of the techniques and devices described herein, users may control their devices through in-the-air gestures, even when those gestures are not within line-of-sight of their device's sensors. Thus, the techniques enable users to control their devices in many situations in which control is desired but conventional techniques do permit effective control, such as to turn the temperature down in a room when the user is obscured from a thermostat's gesture sensor, turn up the volume on a media player when the user is in a different room than the media player, or pause a television program when the user's gesture is obscured by a chair, couch, or other obstruction.


This summary is provided to introduce simplified concepts relating to non-line-of-sight radar-based gesture recognition, which is further described below in the Detailed Description. This summary is not intended to identify essential features of the claimed subject matter, nor is it intended for use in determining the scope of the claimed subject matter.





BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of techniques and devices for non-line-of-sight radar-based gesture recognition are described with reference to the following drawings. The same numbers are used throughout the drawings to reference like features and components:



FIG. 1 illustrates an example environment in which non-line-of-sight radar-based gesture recognition can be implemented, including though use of direct and reflected radar fields.



FIG. 2 illustrates the smart device of FIG. 1 in greater detail.



FIG. 3 illustrates an example penetration radar field.



FIG. 4 illustrates an example method enabling non-line-of-sight radar-based gesture recognition using a reflected radar field.



FIG. 5 illustrates a room of FIG. 1, including volumes that do not have line-of-sight to a radar system and transmission paths through which a reflected radar field is provided within those volumes.



FIG. 6 illustrates an example method enabling non-line-of-sight radar-based gesture recognition effective to control or communicate with a smart device that does not have line-of-sight to a user.



FIG. 7 illustrates a ground floor of a home having multiple radar systems, some of which do not have line-of-sight to a user in the home.



FIG. 8 illustrates an example device embodying, or in which techniques may be implemented that enable use of, non-line-of-sight radar-based gesture recognition.





DETAILED DESCRIPTION

Overview


This document describes techniques and devices enabling non-line-of-sight radar-based gesture recognition. These techniques and devices enable greater control of smart devices through recognizing gestures when those gestures are made without being within line-of-sight of a smart device's sensors.


Consider, for example, a case where a user has many smart devices in his home. Assume that to control these devices he has numerous handheld remote controls; one for each device. Controlling these various smart devices is impractical due to the number of remote controls needed. Further, even if the user had one remote control capable of controlling multiple smart devices, he would still not be able to control all of multiple devices whenever he was not within line-of-sight of all of these various devices. And, even in the uncommon event of being in line-of-sight to many devices at once, the user still needs to carry around a remote control.


Consider other conventional ways in which to control smart devices, such as audio interfaces and line-of-sight cameras. Audio interfaces often fail to understand a user's intent and require the user to interrupt his or her ongoing conversations. Line-of-sight cameras, while allowing a user to forgo carrying a remote control in some cases, require line-of-sight and also can fail to provide robust and consistent gesture recognition. These are but three of many example controllers that fail to provide seamless and intuitive control.


In contrast, consider a case where a user is standing in her kitchen and desires to pause her television that is in her living room, turn off her microwave because her dinner is getting too hot, and turn up the heat in her home. Assume that the user's hands are blocked from her microwave by some hanging pots and pans and that her thermostat and television are within other rooms. The techniques described herein enable her to control all three of these devices, even though two are in other rooms and the third is obscured by various objects. None of these have line-of-sight to her, yet she can make a gesture to control each and every one of these three different devices seamlessly and intuitively.


This is but one way in which non-line-of-sight radar-based gesture recognition can be performed. This document now turns to an example environment, after which non-line-of-sight gesture recognition systems, example methods, and an example computing system are described.


Example Environment



FIG. 1 is an illustration of an example environment 100 in which techniques enabling non-line-of-sight radar-based gesture recognition can be performed. Environment 100 includes a room 102, a smart device 104, and a user 106. Room 102 includes obstructions 108, walls 110, a floor 112 (shown with squares), and a ceiling 114 (transparent in top-down view, show with circles), which are described in more detail below. Room 102 is shown in two identical illustrations (102-1 and 102-2) with the exception of one having a direct radar field and another having a reflected radar field, as noted below.


Smart device 104 includes non-line-of-sight gesture recognition system 116 (NLOS system 116), which provides a direct radar field 118. Direct radar field 118 does not have line-of-sight to some portions of room 102, here volumes 120. A first volume 120-1 does not have line-of-sight to NLOS system 116 due to couch 108-1, which is one of obstructions 108. A second volume 120-2 does not have line-of-sight to NLOS system 116 due to planter box 108-2, which is another of obstructions 108.


NLOS recognition system 116 is also capable of providing a reflected radar field 122 effective to enable recognition of gestures within some or all of volumes 120 in which direct line-of-sight is not available. This reflected radar field 122 is shown provided through radar transmission lines 124, though additional description of transmission lines is provided elsewhere herein. For visual clarity radar fields 118 and 122 are shown separately, though both radar fields can be used together.


While not shown in FIG. 1, NLOS system 116 can also provide a penetration radar field. This field is configured to penetrate various materials, such as wool, cotton, nylon, or leather, but reflect from human tissue, thereby further enabling recognition of gestures that are partially or fully not in line-of-sight or otherwise obscured from NLOS system 116.


In more detail, consider FIG. 2, which illustrates smart device 104. Smart device 104 includes one or more computer processors 202 and computer-readable media 204 (e.g., memory media and storage media). Applications and/or an operating system (not shown) embodied as computer-readable instructions on computer-readable media 204 can be executed by processors 202 to provide some of the functionalities described herein. Computer-readable media 204 also includes field manager 206 (described below).


Smart device 104 may also include network interfaces 208 for communicating data over wired, wireless, or optical networks. By way of example and not limitation, network interface 208 may communicate data over a local-area-network (LAN), a wireless local-area-network (WLAN), a personal-area-network (PAN), a wide-area-network (WAN), an intranet, the Internet, a peer-to-peer network, point-to-point network, a mesh network, and the like. Smart device 104 may also include a display 210, though this is not required.


Smart device 104 also includes or has access to NLOS system 116, as noted above, which is configured to provide radar fields by which to sense gestures. To enable this, NLOS system 116 includes a microwave radio element 212, an antenna element 214, and a signal processor 216. Generally, microwave radio element 212 is configured to provide a radar field having a direct radar field and a reflected radar field as noted above, though a penetration radar field may also be included. While examples shown herein generally show one NLOS system 116 per device, multiples can be used, thereby increasing coverage of a volume (e.g., room 102), as well as a number, complexity, accuracy, resolution, and robust recognition of gestures.


Microwave radio element 212 can be configured to emit one or multiple sets of continuously modulated radiation, ultra-wideband radiation, or sub-millimeter-frequency radiation. Microwave radio element 212, in some cases, is configured to form radiation in beams, the beams aiding antenna element 214 and signal processor 216 to determine which of the beams are interrupted, and thus locations of interactions (e.g., by a hand) within the radar field. In more detail, microwave radio element 212 can be configured to emit microwave radiation in a 1 GHz to 300 GHz range, as well as 57 GHz to 63 GHz, to provide the radar field. This range affects antenna element 214's ability to sense interactions, such as to track locations of two or more targets to a resolution of about two to about 25 millimeters. Microwave radio element 212 can be configured, along with other entities of NLOS system 116, to have a relatively fast update rate, which can aid in resolution of the interactions. By selecting particular frequencies, NLOS system 116 can operate to provide a direct radar field to reflect from line-of-sight gestures, a reflected radar field to reflect first from some object or objects and then from non-line-of-sight gestures, and/or a penetration radar field to penetrate clothing and similar materials while reflecting from human tissue.


Antenna element 214 is configured to receive reflections of, or sense interactions in, the radar field, and signal processor 216 is configured to process the reflections or sensed interactions in the radar field sufficient to provide gesture data usable to determine a gesture from the sensed interactions. Antenna element 214 can include one or many sensors, such as an array of radiation sensors, the number in the array based on a desired resolution and whether the radar field is direct, reflected, or penetration. Alternately or additionally, antenna element 214 may include one or many antennas, such as an array of antennas, directional or otherwise, coupled with respective radiation sensors and/or signal processor 216.


Further, antenna element 214 or signal processor 216 can be configured to differentiate between interactions in the radar field that are from radar transmissions that are direct, through a material, or after being reflected. Thus, a media player having NLOS system 116 may differentiate between radar reflecting directly from a user's hand to radar that was first bounced off of a ceiling (e.g., a painted, gypsum drywall ceiling) and then reflected off of the user's hand.


The radar field provided by microwave radio element 212 can include one or multiple three-dimensional (3D) volumes, planes, or surfaces (e.g., a surface applied to a user's hand) In each of these cases, antenna element 214 is configured to sense interactions of one or multiple targets (e.g., two hands, fingers of one or two hands, etc.), and signal processor 216 is configured to process the sensed interactions sufficient to provide gesture data usable to determine gestures in three dimensions.


With the provided radar field, such as direct radar field 118 and reflected radar field 124 of FIG. 1, a user may perform complex or simple gestures with a hand or device (e.g., a stylus) that interrupts the field. Example gestures include the many gestures usable with current touch-sensitive displays, such as swipes, two-finger pinch and spread, tap, and so forth. Other gestures are enabled that are complex, or simple but three-dimensional, examples include the many sign-language gestures, e.g., those of American Sign Language (ASL) and other sign languages worldwide. A few of these include an up-and-down fist, which in ASL means “Yes”, an open index and middle finger moving to connect to an open thumb, which means “No”, a flat hand moving up a step, which means “Advance”, a flat and angled hand moving up and down, which means “Afternoon”, clenched fingers and open thumb moving to open fingers and an open thumb, which means “taxicab”, an index finger moving up in a roughly vertical direction, which means “up”, and so forth. These are but a few of many gestures that can be mapped to particular devices or applications, such as the “Advance” gesture to skip to another song being played by a media player through a non-line-of-sight gesture.


As noted above, NLOS system 116 can provide a penetration radar field capable of penetrating some objects and materials and then reflect off of human tissue. This is illustrated at FIG. 3, which shows hand 302 having a penetration radar field 304 contacting a surface 306 of hand 302. This penetration radar field 304 penetrates chair 308 to then be reflected from surface 306 and received back at antenna element 214 of NLOS system 116. Microwave radio element 212 (not shown) provides penetration radar field 304, while antenna element 214 is configured to receive a reflection caused by an interaction on surface 306 of hand 302 that penetrates and then reflects back through chair 308, at which point signal processor 216 is configured to process the received reflection sufficient to provide gesture data usable to determine a gesture.


Gestures can be associated with various smart devices, such as a device other than smart device 104. To do so, gestures can map to a pre-configured control gesture associated with a control input for an application associated with any of these devices. Thus, a gesture can be set to control the application and/or device based on the gesture itself, rather than first selecting which device or application to which the control is intended. For example, many complex and unique gestures can be recognized by NLOS system 116, thereby permitting precise and/or single-gesture control, even for multiple applications. Mapping these many gestures to various different devices and application permits control, with or without explicitly selecting (usually through a gesture) which device is intended to be controlled.


Smart device 104 is illustrated with various non-limiting example devices: smartphone 104-1, refrigerator 104-2, microwave oven 104-3, laptop 104-4, tablet 104-5, and television 104-6, though other devices may also be used, such as climate control devices (e.g., a thermostat or ceiling fan), wearable devices, desktop computers, netbooks, e-readers, cameras, automotive systems, and so forth.


NLOS system 116 also includes a transceiver 218 configured to transmit gesture data to a remote device, such as in cases where NLOS system 116 is not integrated with smart device 104. Gesture data can be provided in a format usable by the receiving device sufficient to recognize a gesture using the gesture data.


NLOS system 116 may also include one or more system processors 220 and system media 222 (e.g., one or more computer-readable storage media). System media 222 includes system manager 224, which can perform various operations, including determining a gesture based on gesture data from signal processor 216, mapping the determined gesture to a pre-configured control gesture associated with a control input for an application associated with a remote smart device, and causing transceiver 218 to transmit the control input to the remote smart device effective to enable control of the application or device. This is but one of the ways in which the above-mentioned control through NLOS system 116 can be enabled. Note also that while NLOS system 116 is shown integral with smart device 104, it can instead be part of a device having few or no computing capabilities and still provide gesture data to be recognized and/or mapped to a control input. Operations of NLOS system 116, system manager 224, and field manager 206 are provided in greater detail as part of methods 400 and 600 below.


These and other capabilities and configurations, as well as ways in which entities of FIGS. 1-3 act and interact, are set forth in greater detail below. These entities may be further divided, combined, and so on. The environment 100 of FIG. 1 and the detailed illustrations of FIGS. 2 and 3 illustrate some of many possible environments and devices capable of employing the described techniques.


Example Methods



FIGS. 4 and 6 depict methods 400 and 600. Method 400 enables non-line-of-sight radar-based gesture recognition using a reflected radar field, and can be performed separate from or integrated in whole or in part with method 600. Method 600 enables non-line-of-sight radar-based gesture recognition where a direct line-of-sight is not present for one radar system but a gesture is recognized through another radar system and then passed to the other radar system through direct or indirect radar fields.


These methods are shown as sets of operations (or acts) performed but are not necessarily limited to the order or combinations in which the operations are shown herein. Further, any of one or more of the operations may be repeated, combined, reorganized, or linked to provide a wide array of additional and/or alternate methods. In portions of the following discussion reference may be made to environment 100 of FIG. 1 and entities and examples detailed in FIGS. 2, 3, 5, and 7, reference to which is made for example only. The techniques are not limited to performance by one entity or multiple entities operating on one device.


At 402, a volume of a room in which there is no line-of-sight to a radar system is determined. The techniques may determine that there is such a volume in various manners, such as through tracking a moving entity, a camera, bounced (e.g., reflected) radar transmissions, and so forth.


For example, field manager 206 may track, with a radar transmission, a person or animal's movement in the room. If, during a portion of the person or animal's movement field manager 206 does not receive a reflection from the person or animal, field manager 206 may determine, based on the person or animal's projected path or a part of the person or animal no longer trackable (e.g., a person's legs walking behind a couch), that a volume in the room exists where direct line-of-sight is not available.


Field manager 206 may also or instead use a camera or other image sensor, using radar or otherwise. Field manager 206 captures an image using the camera to provide an image of the room from a perspective of NLOS system 116. Field manager 206 then receives or determines (e.g., through sonar or radar reflection) dimensions for the room (e.g., 4 meters wide, 7 meters deep, 3 meters high). With these dimensions and the image of the room, non-imaged but existing floor, wall, or ceiling areas can be determined. With this data, field manager 206 may then determine the volume of the room in which there is no line-of-sight to NLOS system 116.


Further still, field manager 206 may determine non-line-of-sight volumes based on obstructions. Thus, on providing a direct radar field to receive reflections from objects in the room, field manager 206 assumes that regions behind obstructions are likely to be volumes in which a potential gesture may be made, and in any case, these are very likely to part of the room and do not have line-of-sight. As part of this determination obstructions are objects other than floors, walls, or ceilings of the room. Some objects reflect radar and some are those through which radar may pass. Because of this, portions of the objects penetrated by the radar field can reduce the size of the volume.


At 404, a set of transmission paths sufficient to cause a reflected radar field to be provided within at least a portion of the volume is determined by providing radar transmissions from the radar system into the room. As noted in part above, determining a volume in which no line-of-sight is available may include radar reflection, in which case some transmission paths may be known. In many cases, however, while the volume is known the transmission paths to cause a reflected radar field are not yet known.


To determine these transmission path, field manager 206 may iteratively provide radar transmissions and receive reflections from the provided radar transmissions. Some of these radar transmissions may not pass through the determined volume, and thus are not needed. Some others, however, pass through one of the determined volumes and are then correlated with that volume. In still further cases, a person or animal passes through the determined volume and radar transmission are iteratively provided and then, on reflection from the person or animal, correlated to the volume. In so doing various types and frequencies of radar transmissions can be used, including narrow-beam transmission and reflection.


By way of example, consider FIG. 5, which illustrates room 102 of FIG. 1, including smart device 104, user 106, obstructions 108, walls 110, floor 112, ceiling 114, NLOS system 116, and volumes 120-1 and 120-2. Two transmission paths are shown, wall-and-object-reflection path 502 and ceiling-and-floor path 504. These illustrate but two of many different transmission paths capable of providing reflection radar field 122 (shown in FIG. 1 and omitted for clarity in FIG. 5).


Wall-and-object-reflection path 502 includes eight portions, each reflecting off of, or resulting from a reflection off of, a wall or object. Thus, path 502 proceeds from NLOS system 116 to one of walls 110, then again off of another of walls 110, then off of a back of couch 108-1, back to the other of walls 110, to couch 108-1, to the other of the walls 110, than off planter box 108-2, and then back to NLOS system 116. Some transmission paths do not result in a reflection returning, and thus can be forgone, while others pass only within volumes that are in line-of-site of NLOS system 116, and can also be forgone. Path 504 proceeds from NLOS system 116 to ceiling 114 (shown reflected at a circle), then to one of walls 110, off floor 112 (shown reflected at a square), off ceiling 114, and then back to NLOS system 116. These two paths 502, 504 provide but two example transmission paths by which NLOS system 116 and field manager 206 may provide a reflected radar field (e.g., 122 of FIG. 1) in a volume in which line-of-sight to NLOS system 116 is not available. As noted, this reflected radar field enables rejection of gestures made within some or all of volumes 120.


At 406, a radar field is provided within the one or more volumes within the room, the radar field including at least the reflected radar field. In some cases, the radar field also includes a direct radar field or a penetration radar field as noted herein. By so doing, a radar field usable to recognize gestures can be provided for gestures that do not have direct line-of-sight from a radar system.


At 408, a reflection of a gesture interaction made within the radar field within the room is received. This reflection enables capture of data about the gesture interaction that can then be used to determine the gesture being made. This reflection can be within a reflected, direct, or penetration radar field as noted above.


At 410, a gesture is determined based on captured data associated with the reflection of the gesture interaction. The gesture determined can be one of many gestures noted above, including those mapping directly to a device or application and a control command, such as to mute a television set.


At 412, the determined gesture is provided to a device or application effective to control the device or application. As part of this provision, field manager 206 may determine to which device or application to send the control, such as by analyzing a map of gestures to various devices and applications.



FIG. 6 illustrates method 600, which enables non-line-of-sight radar-based gesture recognition effective to control or communicate with a smart device that does not have line-of-sight to a user.


At 602, a radar field is provided, such as a field having one or more of a direct, reflected, or penetration radar field, as described above. This radar field can be provided by a radar system that does or does not have line-of-sight to a user making a gesture.


At 604, reflections from an interaction that is within the radar field are sensed through a radar system. This radar system is assumed to have line-of-sight, or is able to compensate for not having line-of-sight, effective to receive reflections from a user. Another smart device, however, which may or may not have a radar system, does not have line-of-sight to the user and is not able to compensate. Thus, both devices may not have line-of-sight to a user but one of those devices is able to sense reflections, such as through a penetration or reflection radar field.


By way of example, consider FIG. 7, which illustrates a ground floor 702 of a home. This home includes four rooms 704, media room 704-1, piano room 704-2, living room 704-3, and kitchen/dining room 704-4. As shown, there are five radar systems 706, a media-player 708's radar system 706-1, a thermostat 710's radar system 706-2, a television 712's radar system 706-3, an oven 714's radar system 706-4, and a microwave-oven 716's radar system 706-5. Multiple scenarios in which the techniques enable gesture recognition without line-of-sight to a smart device intended to be controlled are shown in FIG. 7, such as when user 718 wants to control television 712 while in kitchen 704-4. To do so, field manager 206 receives reflections from user 718 at an NLOS system 116 of one of radar systems 706 that is not in the same room as user 718.


By way of a particular example, assume that user 718 is in kitchen/dining room 704-4 and wants to turn down the heat in the house by controlling thermostat 710, which is in piano room 704-2. To do so, user 718 makes a gesture to turn down the heat while standing in kitchen/dining room 704-4, which, at operation 604, an NLOS system 116 operating in oven 714's radar system 706-4 receives. The gesture is received by receiving user 718's reflection within radar field 720 at an antenna of NLOS system 116.


At 606, a gesture is recognized based on the reflections received. This can be performed at a smart device associated with a radar system at which the reflection is received, or gesture data for the reflection can be received at a smart device intended to be controlled. Thus, field manager 206 or system manager 224 may receive the reflection and pass gesture data for the reflection to other smart devices, such as to all of the other radar systems and/or devices in a home or office. In such a case, the smart devices can determine if the control is intended for them based on the gesture determined from the gesture data, such as having received a prior gesture selecting to control that device or receiving a gesture associated with the smart device.


At 608, the gesture is determined to be associated with (or not associated with) a non-line-of-sight smart device. Generally, field manager 206 may determine that the gesture is associated with a non-line-of-sight smart device by mapping the gesture to a pre-configured gesture intended to establish communication with the non-line-of-sight smart device. In some cases this pre-configured gesture establishes communication with the non-line-of-sight smart device effective to enable a future gesture determined at the smart device to control the non-line-of-sight smart device. In some other cases, field manager 206 may determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to a unique gesture. This unique gesture can be of a set of unique gestures uniquely mapped to each of a set of smart devices within some group, such as smart devices on ground floor 702 of FIG. 7.


Continuing the ongoing example of FIG. 7, assume that field manager 206 operating at NLOS system 116 of oven 714's radar system 706-4 recognizes a gesture made by user 718. This gesture may then be determined to indicate control of thermostat 710, after which another gesture is recognized and then determined to be associated with thermostat 710 based on the prior gesture indicating control of thermostat 710 is intended. Assume, for example, that a unique, complex gesture with a closed hand and exposed thumb that moves up and the down is associated with thermostat 710. A second gesture, here assumed to be a non-unique magnitude gesture of a cupped hand moving clockwise or counter-clockwise, indicates to turn up or down something, respectively. Because this second gesture is received soon after the first gesture indicating control of thermostat 710 is intended, it is then recognized by repeating steps of method 600 and then passed (at operation 610) to thermostat 710 effective to turn the heat up or down. This repetition is shown at a dashed arrow in FIG. 6.


Similarly, if the first gesture is associated with control of media player 708, the second gesture indicating to turn up or down, would instead turn up or turn down the volume of media player 708, all without line-of-sight from the intended smart device.


At 610, the gesture is passed to the non-line-of-sight smart device. Thus, the gesture can be passed from one smart device to another smart device effective to enable the gesture to control the non-line-of-sight smart device or establish communication with the non-line-of-sight smart device.


The preceding discussion describes methods relating to non-line-of-sight radar-based gesture recognition. Aspects of these methods may be implemented in hardware (e.g., fixed logic circuitry), firmware, software, manual processing, or any combination thereof. These techniques may be embodied on one or more of the entities shown in FIGS. 1-3, 5, 7, and 8 (computing system 800 is described with reference to FIG. 8 below), which may be further divided, combined, and so on. Thus, these figures illustrate some of the many possible systems or apparatuses capable of employing the described techniques. The entities of these figures generally represent software, firmware, hardware, whole devices or networks, or a combination thereof.


Example Computing System



FIG. 8 illustrates various components of example computing system 800 that can be implemented as any type of client, server, and/or smart device as described with reference to the previous FIGS. 1-7 to implement non-line-of-sight radar-based gesture recognition. In embodiments, computing system 800 can be implemented as one or a combination of a wired and/or wireless wearable device, System-on-Chip (SoC), and/or as another type of device or portion thereof. Computing system 800 may also be associated with a user (e.g., a person) and/or an entity that operates the device such that a device describes logical devices that include users, software, firmware, and/or a combination of devices.


Computing system 800 includes communication devices 802 that enable wired and/or wireless communication of device data 804 (e.g., received data, data that is being received, data scheduled for broadcast, data packets of the data, etc.). Device data 804 or other device content can include configuration settings of the device, media content stored on the device, and/or information associated with a user of the device. Media content stored on computing system 800 can include any type of audio, video, and/or image data. Computing system 800 includes one or more data inputs 806 via which any type of data, media content, and/or inputs can be received, such as human utterances, interactions with a radar field, user-selectable inputs (explicit or implicit), messages, music, television media content, recorded video content, and any other type of audio, video, and/or image data received from any content and/or data source.


Computing system 800 also includes communication interfaces 808, which can be implemented as any one or more of a serial and/or parallel interface, a wireless interface, any type of network interface, a modem, and as any other type of communication interface. Communication interfaces 808 provide a connection and/or communication links between computing system 800 and a communication network by which other electronic, computing, and communication devices communicate data with computing system 800.


Computing system 800 includes one or more processors 810 (e.g., any of microprocessors, controllers, and the like), which process various computer-executable instructions to control the operation of computing system 800 and to enable techniques for, or in which can be embodied, non-line-of-sight radar-based gesture recognition. Alternatively or in addition, computing system 800 can be implemented with any one or combination of hardware, firmware, or fixed logic circuitry that is implemented in connection with processing and control circuits which are generally identified at 812. Although not shown, computing system 800 can include a system bus or data transfer system that couples the various components within the device. A system bus can include any one or combination of different bus structures, such as a memory bus or memory controller, a peripheral bus, a universal serial bus, and/or a processor or local bus that utilizes any of a variety of bus architectures.


Computing system 800 also includes computer-readable media 814, such as one or more memory devices that enable persistent and/or non-transitory data storage (i.e., in contrast to mere signal transmission), examples of which include random access memory (RAM), non-volatile memory (e.g., any one or more of a read-only memory (ROM), flash memory, EPROM, EEPROM, etc.), and a disk storage device. A disk storage device may be implemented as any type of magnetic or optical storage device, such as a hard disk drive, a recordable and/or rewriteable compact disc (CD), any type of a digital versatile disc (DVD), and the like. Computing system 800 can also include a mass storage media device 816.


Computer-readable media 814 provides data storage mechanisms to store device data 804, as well as various device applications 818 and any other types of information and/or data related to operational aspects of computing system 800. For example, an operating system 820 can be maintained as a computer application with computer-readable media 814 and executed on processors 810. Device applications 818 may include a device manager, such as any form of a control application, software application, signal-processing and control module, code that is native to a particular device, a hardware abstraction layer for a particular device, and so on.


Device applications 818 also include any system components, engines, or managers to implement non-line-of-sight radar-based gesture recognition. In this example, device applications 818 include field manager 206 and system manager 224.


CONCLUSION

Although embodiments of techniques using, and apparatuses enabling, non-line-of-sight radar-based gesture recognition have been described in language specific to features and/or methods, it is to be understood that the subject of the appended claims is not necessarily limited to the specific features or methods described. Rather, the specific features and methods are disclosed as example implementations enabling non-line-of-sight radar-based gesture recognition.

Claims
  • 1. A smart device associated with a radar field, the smart device comprising: a non-line-of-sight gesture-recognition system configured to: provide the radar field, the radar field including a direct radar field and a reflected radar field, the reflected radar field provided in one or more volumes in a room to which direct line-of-sight from the non-line-of-sight gesture-recognition system is not available;sense radar reflections from an interaction that is within the reflected radar field, the radar reflections sensed by receiving the radar reflections from a surface of the room and at an antenna of the non-line-of-sight gesture-recognition system;recognize, based on the radar reflections from the interaction that is within the reflected radar field, a gesture; anddetermine that the gesture is associated with a non-line-of-sight smart device; anda transceiver or network interface configured to pass the gesture from the smart device associated with the radar field to the non-line-of-sight smart device in a format usable by the non-line-of-site smart device to recognize the gesture and effective to enable the gesture to control the non-line-of-sight smart device or establish communication with the non-line-of-sight smart device.
  • 2. The smart device of claim 1, wherein: the radar field further includes a penetration radar field;the penetration radar field is provided in one or more volumes in a room to which direct line-of-sight from the non-line-of-sight gesture-recognition system is not available; andthe non-line-of-sight gesture-recognition system is further configured to sense additional radar reflections from a second interaction that is within the penetration radar field.
  • 3. The smart device of claim 2, wherein the non-line-of-sight gesture-recognition system is further configured to sense the additional radar reflections from the second interaction that is within the penetration radar field by receiving the additional radar reflections at the antenna of the non-line-of-sight gesture-recognition system and through an object occluding the second interaction that is within the penetration radar field.
  • 4. The smart device of claim 1, wherein: the non-line-of-sight recognition system is further configured to receive a second gesture from a second non-line-of-sight gesture-recognition system,the second non-line-of-sight gesture-recognition system is associated with the non-line-of-sight smart device,the second gesture is associated with the smart device, andthe non-line-of-sight gesture-recognition system is further configured to control the smart device based on the second gesture.
  • 5. The smart device of claim 1, wherein the non-line-of-sight recognition system is further configured to determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to a pre-configured control gesture associated with a control input for an application associated with the non-line-of-sight smart device.
  • 6. The smart device of claim 1, wherein the non-line-of-sight recognition system is further configured to determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to a pre-configured communication-establishment gesture associated with the non-line-of-sight smart device.
  • 7. The smart device of claim 1, wherein the non-line-of-sight recognition system is further configured to determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to a unique gesture of a set of unique gestures unique to each of a set of smart devices.
  • 8. The smart device of claim 1, wherein the transceiver or network interface is further configured to pass the gesture from the smart device to the non-line-of-sight smart device by passing the gesture as gesture data that maps the gesture to a pre-configured control gesture for an application executing at the non-line-of-sight smart device.
  • 9. The smart device of claim 1, wherein the format usable by the non-line-of-site smart device to recognize the gesture is further effective to enable the non-line-of-sight smart device or an application executing at the non-line-of-sight smart device to determine if the gesture maps to a pre-configured control gesture for an application executing at the non-line-of-sight smart device.
  • 10. A smart device associated with a radar field, the smart device comprising: a non-line-of-sight gesture-recognition system configured to: provide the radar field;sense radar reflections from an interaction that is within the radar field;recognize, based on the radar reflections from the interaction that is within the radar field, a gesture; anddetermine that the gesture is associated with a non-line-of-sight smart device; anda transceiver or network interface configured to: pass the gesture from the smart device associated with the radar field to the non-line-of-sight smart device in a format usable by the non-line-of-site smart device to recognize the gesture and effective to establish communication with the non-line-of-sight smart device; andestablish communication with the non-line-of-sight smart device responsive to a determination that the gesture is for establishing communication with the non-line-of-sight smart device to enable control of the non-line-of-sight smart device through a future gesture determined at the smart device and sensed through the non-line-of-sight gesture-recognition system of the smart device.
  • 11. The smart device of claim 10, wherein the non-line-of-sight recognition system is further configured to determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to a pre-configured control gesture associated with a control input for an application associated with the non-line-of-sight smart device.
  • 12. The smart device of claim 10, wherein the non-line-of-sight recognition system is further configured to determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to a pre-configured communication-establishment gesture associated with the non-line-of-sight smart device.
  • 13. The smart device of claim 10, wherein the non-line-of-sight recognition system is further configured to determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to a unique gesture of a set of unique gestures unique to each of a set of smart devices.
  • 14. The smart device of claim 10, wherein the transceiver or network interface is further configured to pass the gesture from the smart device to the non-line-of-sight smart device by passing the gesture as gesture data that maps the gesture to a pre-configured control gesture for an application executing at the non-line-of-sight smart device.
  • 15. The smart device of claim 10, wherein the format usable by the non-line-of-site smart device to recognize the gesture is further effective to enable the non-line-of-sight smart device or an application executing at the non-line-of-sight smart device to determine if the gesture maps to a pre-configured control gesture for an application executing at the non-line-of-sight smart device.
  • 16. A system comprising: a non-line-of-sight gesture-recognition system configured to: provide a radar field within a room, the radar field including reflected radar fields, the reflected radar fields being reflected off of one or more surfaces of the room and provided in one or more volumes in the room to which direct line-of-sight from the non-line-of-sight gesture-recognition system is not available; andreceive a radar reflection of a gesture interaction made within the one or more volumes in the room to which direct line-of-sight from the non-line-of-sight gesture-recognition system is not available, the radar reflection enabling capture of data about the gesture interaction,one or more processors; andone or more computer readable storage media having instructions stored thereon that, responsive to execution by the one or more processors, implement a system manager, the system manager configured to: determine a gesture based on the data about the gesture interaction; andprovide the gesture to a device or application effective to control the device or application.
  • 17. The system of claim 16, wherein the radar reflection of the gesture interaction is made within one of the reflected radar fields and the radar reflection is received by an antenna of the non-line-of-sight gesture-recognition system from a second radar reflection off of one of the one or more surfaces of the room.
  • 18. The system of claim 16, wherein the non-line-of-sight gesture-recognition system is further configured to provide the radar field within the room further by providing penetration radar fields within portions of the one or more volumes of the room to which direct line-of-sight from the non-line-of-sight gesture-recognition system is not available.
  • 19. The system of claim 18, wherein the radar reflection of the gesture interaction is made within one of the penetration radar fields.
  • 20. The system of claim 16, wherein the non-line-of-sight recognition system is further configured to determine that the gesture is associated with the non-line-of-sight smart device by mapping the gesture to: a pre-configured control gesture associated with a control input for an application associated with the non-line-of-sight smart device;a pre-configured communication-establishment gesture associated with the non-line-of-sight smart device; ora unique gesture of a set of unique gestures unique to each of a set of smart devices.
PRIORITY APPLICATION

This application is a continuation of Ser. No. 14/582,896 titled “Non-Line-of-Sight Radar-Based Gesture Recognition,” and filed on Dec. 24, 2014 and claims priority under 35 U.S.C. § 119(e) to U.S. Patent Application Ser. No. 62/059,099, titled “Non-Line-of-Sight Radar-Based Gesture Recognition,” and filed on Oct. 2, 2014, the disclosure of which is incorporated by reference herein in its entirety.

US Referenced Citations (563)
Number Name Date Kind
3610874 Gagliano Oct 1971 A
3752017 Lloyd et al. Aug 1973 A
3953706 Harris et al. Apr 1976 A
4104012 Ferrante Aug 1978 A
4700044 Hokanson et al. Oct 1987 A
4795998 Dunbar et al. Jan 1989 A
4838797 Dodier Jun 1989 A
5016500 Conrad et al. May 1991 A
5298715 Chalco et al. Mar 1994 A
5341979 Gupta Aug 1994 A
5410471 Alyfuku et al. Apr 1995 A
5468917 Brodsky et al. Nov 1995 A
5564571 Zanotti Oct 1996 A
5656798 Kubo et al. Aug 1997 A
5724707 Kirk et al. Mar 1998 A
5798798 Rector et al. Aug 1998 A
6032450 Blum Mar 2000 A
6080690 Lebby et al. Jun 2000 A
6101431 Niwa et al. Aug 2000 A
6210771 Post et al. Apr 2001 B1
6254544 Hayashi Jul 2001 B1
6313825 Gilbert Nov 2001 B1
6340979 Beaton et al. Jan 2002 B1
6380882 Hegnauer Apr 2002 B1
6386757 Konno May 2002 B1
6440593 Ellison et al. Aug 2002 B2
6492980 Sandbach Dec 2002 B2
6493933 Post et al. Dec 2002 B1
6513833 Breed et al. Feb 2003 B2
6513970 Tabata et al. Feb 2003 B1
6524239 Reed et al. Feb 2003 B1
6543668 Fujii et al. Apr 2003 B1
6616613 Goodman Sep 2003 B1
6711354 Kameyama Mar 2004 B2
6717065 Hosaka et al. Apr 2004 B2
6802720 Weiss et al. Oct 2004 B2
6833807 Flacke et al. Dec 2004 B2
6835898 Eldridge et al. Dec 2004 B2
6854985 Weiss Feb 2005 B1
6929484 Weiss et al. Aug 2005 B2
6997882 Parker et al. Feb 2006 B1
7019682 Louberg et al. Mar 2006 B1
7134879 Sugimoto et al. Nov 2006 B2
7158076 Fiore et al. Jan 2007 B2
7164820 Eves et al. Jan 2007 B2
7194371 McBride et al. Mar 2007 B1
7205932 Fiore Apr 2007 B2
7223105 Weiss et al. May 2007 B2
1230610 Jung et al. Jun 2007 A1
7249954 Weiss Jul 2007 B2
7266532 Sutton et al. Sep 2007 B2
7299964 Jayaraman et al. Nov 2007 B2
7310236 Takahashi et al. Dec 2007 B2
7317416 Flom et al. Jan 2008 B2
7348285 Dhawan et al. Mar 2008 B2
7365031 Swallow et al. Apr 2008 B2
7421061 Boese et al. Sep 2008 B2
7462035 Lee et al. Dec 2008 B2
7528082 Krans et al. May 2009 B2
7544627 Tao et al. Jun 2009 B2
7578195 DeAngelis et al. Aug 2009 B2
7644488 Aisenbrey Jan 2010 B2
7647093 Bojovic et al. Jan 2010 B2
7670144 Ito et al. Mar 2010 B2
7677729 Vilser et al. Mar 2010 B2
7691067 Westbrook et al. Apr 2010 B2
7698154 Marchosky Apr 2010 B2
7791700 Bellamy Sep 2010 B2
7834276 Chou et al. Nov 2010 B2
7845023 Swatee Dec 2010 B2
7941676 Glaser May 2011 B2
7952512 Delker et al. May 2011 B1
8062220 Kurtz et al. Nov 2011 B2
8063815 Valo et al. Nov 2011 B2
8169404 Boillot May 2012 B1
8179604 Prada Gomez et al. May 2012 B1
8193929 Siu et al. Jun 2012 B1
8199104 Park et al. Jun 2012 B2
8282232 Hsu et al. Oct 2012 B2
8289185 Alonso Oct 2012 B2
8301232 Albert et al. Oct 2012 B2
8314732 Oswald et al. Nov 2012 B2
8334226 Nhan et al. Dec 2012 B2
8341762 Balzano Jan 2013 B2
8344949 Moshfeghi Jan 2013 B2
8367942 Howell et al. Feb 2013 B2
8475367 Yuen et al. Jul 2013 B1
8505474 Kang et al. Aug 2013 B2
8509882 Albert et al. Aug 2013 B2
8514221 King et al. Aug 2013 B2
8527146 Jackson et al. Sep 2013 B1
8549829 Song et al. Oct 2013 B2
8560972 Wilson Oct 2013 B2
8562526 Heneghan et al. Oct 2013 B2
8569189 Bhattacharya et al. Oct 2013 B2
8614689 Nishikawa et al. Dec 2013 B2
8655004 Prest et al. Feb 2014 B2
8700137 Albert Apr 2014 B2
8758020 Burdea et al. Jun 2014 B2
8759713 Sheats Jun 2014 B2
8764651 Tran Jul 2014 B2
8785778 Streeter et al. Jul 2014 B2
8790257 Libbus et al. Jul 2014 B2
8814574 Selby et al. Aug 2014 B2
8860602 Nohara et al. Oct 2014 B2
8921473 Hyman Dec 2014 B1
8948839 Longinotti-Buitoni et al. Feb 2015 B1
9055879 Selby et al. Jun 2015 B2
9075429 Karakotsios et al. Jul 2015 B1
9093289 Vicard et al. Jul 2015 B2
9125456 Chow Sep 2015 B2
9141194 Keyes et al. Sep 2015 B1
9148949 Guofu et al. Sep 2015 B2
9223494 DeSalvo et al. Dec 2015 B1
9229102 Wright et al. Jan 2016 B1
9230160 Kanter Jan 2016 B1
9235241 Newham et al. Jan 2016 B2
9316727 Sentelle et al. Apr 2016 B2
9331422 Nazzaro et al. May 2016 B2
9335825 Rautianinen et al. May 2016 B2
9346167 O'Connor et al. May 2016 B2
9354709 Heller et al. May 2016 B1
9508141 Khachaturian et al. Nov 2016 B2
9511877 Masson Dec 2016 B2
9569001 Mistry et al. Feb 2017 B2
9575560 Poupyrev et al. Feb 2017 B2
9588625 Poupyrev Mar 2017 B2
9594443 Vanblon et al. Mar 2017 B2
9600080 Poupyrev Mar 2017 B2
9693592 Robinson et al. Jul 2017 B2
9746551 Scholten et al. Aug 2017 B2
9766742 Papakostas Sep 2017 B2
9778749 Poupyrev Oct 2017 B2
9811164 Poupyrev Nov 2017 B2
9817109 Saboo et al. Nov 2017 B2
9837780 Karagozler et al. Dec 2017 B2
9848780 Debusschere et al. Dec 2017 B1
9921660 Poupyrev Mar 2018 B2
9933908 Poupyrev Apr 2018 B2
9947080 Nguyen et al. Apr 2018 B2
9971414 Gollakota et al. May 2018 B2
9971415 Poupyrev et al. May 2018 B2
9983747 Poupyrev May 2018 B2
9994233 Diaz-Jimenez et al. Jun 2018 B2
10016162 Rogers et al. Jul 2018 B1
10034630 Lee et al. Jul 2018 B2
10073590 Dascola et al. Sep 2018 B2
10080528 Debusschere et al. Sep 2018 B2
10082950 Lapp Sep 2018 B2
10088908 Poupyrev et al. Oct 2018 B1
10139916 Poupyrev Nov 2018 B2
10155274 Robinson et al. Dec 2018 B2
10175781 Karagozler et al. Jan 2019 B2
10203763 Poupyrev et al. Feb 2019 B1
10222469 Gillian et al. Mar 2019 B1
10241581 Lien et al. Mar 2019 B2
10268321 Poupyrev Apr 2019 B2
10285456 Poupyrev et al. May 2019 B2
10300370 Amihood et al. May 2019 B1
10310620 Lien et al. Jun 2019 B2
10310621 Lien et al. Jun 2019 B1
10376195 Reid et al. Aug 2019 B1
10379621 Schwesig et al. Aug 2019 B2
10401490 Gillian et al. Sep 2019 B2
10409385 Poupyrev Sep 2019 B2
10459080 Schwesig et al. Oct 2019 B1
10492302 Karagozler et al. Nov 2019 B2
10496182 Lien et al. Dec 2019 B2
10503883 Gillian et al. Dec 2019 B1
10509478 Poupyrev et al. Dec 2019 B2
10540001 Poupyrev et al. Jan 2020 B1
10572027 Poupyrev et al. Feb 2020 B2
10579150 Gu et al. Mar 2020 B2
20010035836 Miceli et al. Nov 2001 A1
20020009972 Amento et al. Jan 2002 A1
20020080156 Abbott et al. Jun 2002 A1
20020170897 Hall Nov 2002 A1
20030005030 Sutton et al. Jan 2003 A1
20030093000 Nishio et al. May 2003 A1
20030100228 Bungo et al. May 2003 A1
20030119391 Swallow et al. Jun 2003 A1
20030122677 Kail Jul 2003 A1
20040009729 Hill et al. Jan 2004 A1
20040102693 Jenkins May 2004 A1
20040249250 McGee et al. Dec 2004 A1
20040259391 Jung et al. Dec 2004 A1
20050069695 Jung et al. Mar 2005 A1
20050128124 Greneker et al. Jun 2005 A1
20050148876 Endoh et al. Jul 2005 A1
20050231419 Mitchell Oct 2005 A1
20050267366 Murashita et al. Dec 2005 A1
20060035554 Glaser et al. Feb 2006 A1
20060040739 Wells Feb 2006 A1
20060047386 Kanevsky et al. Mar 2006 A1
20060061504 Leach, Jr. et al. Mar 2006 A1
20060125803 Westerman et al. Jun 2006 A1
20060136997 Telek et al. Jun 2006 A1
20060139162 Flynn Jun 2006 A1
20060148351 Tao et al. Jul 2006 A1
20060157734 Onodero et al. Jul 2006 A1
20060166620 Sorensen Jul 2006 A1
20060170584 Romero et al. Aug 2006 A1
20060209021 Yoo et al. Sep 2006 A1
20060258205 Locher et al. Nov 2006 A1
20060284757 Zemany Dec 2006 A1
20070024488 Zemany et al. Feb 2007 A1
20070026695 Lee et al. Feb 2007 A1
20070027369 Pagnacco et al. Feb 2007 A1
20070118043 Oliver et al. May 2007 A1
20070161921 Rausch Jul 2007 A1
20070164896 Suzuki et al. Jul 2007 A1
20070176821 Flom et al. Aug 2007 A1
20070192647 Glaser Aug 2007 A1
20070197115 Eves et al. Aug 2007 A1
20070197878 Shklarski Aug 2007 A1
20070210074 Maurer et al. Sep 2007 A1
20070237423 Tico et al. Oct 2007 A1
20080001735 Tran Jan 2008 A1
20080002027 Kondo et al. Jan 2008 A1
20080015422 Wessel Jan 2008 A1
20080024438 Collins et al. Jan 2008 A1
20080039731 McCombie et al. Feb 2008 A1
20080059578 Albertson et al. Mar 2008 A1
20080065291 Breed Mar 2008 A1
20080074307 Boric-Lubecke et al. Mar 2008 A1
20080134102 Movold et al. Jun 2008 A1
20080136775 Conant Jun 2008 A1
20080168396 Matas et al. Jul 2008 A1
20080194204 Duet et al. Aug 2008 A1
20080194975 MacQuarrie et al. Aug 2008 A1
20080211766 Westerman et al. Sep 2008 A1
20080233822 Swallow et al. Sep 2008 A1
20080282665 Speleers Nov 2008 A1
20080291158 Park et al. Nov 2008 A1
20080303800 Elwell Dec 2008 A1
20080316085 Rofougaran Dec 2008 A1
20080320419 Matas et al. Dec 2008 A1
20090018408 Ouchi et al. Jan 2009 A1
20090018428 Dias et al. Jan 2009 A1
20090033585 Lang Feb 2009 A1
20090053950 Surve Feb 2009 A1
20090056300 Chung et al. Mar 2009 A1
20090058820 Hinckley Mar 2009 A1
20090113298 Jung et al. Apr 2009 A1
20090115617 Sano et al. May 2009 A1
20090118648 Kandori et al. May 2009 A1
20090149036 Lee et al. Jun 2009 A1
20090177068 Stivoric et al. Jul 2009 A1
20090203244 Toonder Aug 2009 A1
20090226043 Angell et al. Sep 2009 A1
20090253585 Diatchenko et al. Oct 2009 A1
20090270690 Roos et al. Oct 2009 A1
20090278915 Kramer et al. Nov 2009 A1
20090288762 Wolfel Nov 2009 A1
20090295712 Ritzau Dec 2009 A1
20090319181 Khosravy et al. Dec 2009 A1
20100013676 Do et al. Jan 2010 A1
20100050133 Nishihara et al. Feb 2010 A1
20100053151 Marti et al. Mar 2010 A1
20100065320 Urano Mar 2010 A1
20100069730 Bergstrom et al. Mar 2010 A1
20100071205 Graumann et al. Mar 2010 A1
20100094141 Puswella Apr 2010 A1
20100109938 Oswald et al. May 2010 A1
20100152600 Droitcour et al. Jun 2010 A1
20100179820 Harrison et al. Jul 2010 A1
20100198067 Mahfouz et al. Aug 2010 A1
20100201586 Michalk Aug 2010 A1
20100204550 Heneghan et al. Aug 2010 A1
20100205667 Anderson et al. Aug 2010 A1
20100208035 Pinault et al. Aug 2010 A1
20100225562 Smith Sep 2010 A1
20100234094 Gagner et al. Sep 2010 A1
20100241009 Petkie Sep 2010 A1
20100002912 Solinsky Oct 2010 A1
20100281438 Latta et al. Nov 2010 A1
20100292549 Schuler Nov 2010 A1
20100306713 Geisner et al. Dec 2010 A1
20100313414 Sheats Dec 2010 A1
20100324384 Moon et al. Dec 2010 A1
20100325770 Chung et al. Dec 2010 A1
20110003664 Richard Jan 2011 A1
20110010014 Oexman et al. Jan 2011 A1
20110029038 Hyde et al. Feb 2011 A1
20110073353 Lee et al. Mar 2011 A1
20110083111 Forutanpour et al. Apr 2011 A1
20110093820 Zhang et al. Apr 2011 A1
20110118564 Sankai May 2011 A1
20110166940 Bangera et al. Jul 2011 A1
20110181509 Rautiainen et al. Jul 2011 A1
20110181510 Hakala et al. Jul 2011 A1
20110197263 Stinson, III Aug 2011 A1
20110202404 van der Riet Aug 2011 A1
20110213218 Weiner et al. Sep 2011 A1
20110221666 Newton et al. Sep 2011 A1
20110234492 Ajmera et al. Sep 2011 A1
20110245688 Arora et al. Oct 2011 A1
20110279303 Smith Nov 2011 A1
20110286585 Hodge Nov 2011 A1
20110303341 Meiss et al. Dec 2011 A1
20110307842 Chiang et al. Dec 2011 A1
20110316888 Sachs et al. Dec 2011 A1
20110318985 McDermid Dec 2011 A1
20120001875 Li et al. Jan 2012 A1
20120013571 Yeh et al. Jan 2012 A1
20120019168 Noda et al. Jan 2012 A1
20120029369 Icove et al. Feb 2012 A1
20120047468 Santos et al. Feb 2012 A1
20120068876 Bangera et al. Mar 2012 A1
20120092284 Rofougaran et al. Apr 2012 A1
20120123232 Najarian et al. May 2012 A1
20120127082 Kushler et al. May 2012 A1
20120144934 Russell et al. Jun 2012 A1
20120150493 Casey et al. Jun 2012 A1
20120154313 Au et al. Jun 2012 A1
20120156926 Kato et al. Jun 2012 A1
20120174299 Balzano Jul 2012 A1
20120174736 Wang et al. Jul 2012 A1
20120182222 Moloney Jul 2012 A1
20120193801 Gross et al. Aug 2012 A1
20120220835 Chung Aug 2012 A1
20120248093 Ulrich et al. Oct 2012 A1
20120254810 Heck et al. Oct 2012 A1
20120268416 Pirogov et al. Oct 2012 A1
20120270564 Gum et al. Oct 2012 A1
20120280900 Wang et al. Nov 2012 A1
20120298748 Factor et al. Nov 2012 A1
20120310665 Xu et al. Dec 2012 A1
20130016070 Starner et al. Jan 2013 A1
20130027218 Schwarz et al. Jan 2013 A1
20130035563 Angellides Feb 2013 A1
20130046544 Kay et al. Feb 2013 A1
20130053653 Cuddihy et al. Feb 2013 A1
20130078624 Holmes et al. Mar 2013 A1
20130082922 Miller Apr 2013 A1
20130083173 Geisner et al. Apr 2013 A1
20130086533 Stienstra Apr 2013 A1
20130096439 Lee et al. Apr 2013 A1
20130102217 Jeon Apr 2013 A1
20130104084 Mlyniec et al. Apr 2013 A1
20130113647 Sentelle et al. May 2013 A1
20130117377 Miller May 2013 A1
20130132931 Bruns et al. May 2013 A1
20130147833 Aubauer et al. Jun 2013 A1
20130150735 Cheng Jun 2013 A1
20130161078 Li Jun 2013 A1
20130169471 Lynch Jul 2013 A1
20130176161 Derham et al. Jul 2013 A1
20130176258 Dahl et al. Jul 2013 A1
20130194173 Zhu et al. Aug 2013 A1
20130195330 Kim et al. Aug 2013 A1
20130196716 Khurram Aug 2013 A1
20130207962 Oberdorfer et al. Aug 2013 A1
20130229508 Li et al. Sep 2013 A1
20130241765 Kozma et al. Sep 2013 A1
20130245986 Grokop et al. Sep 2013 A1
20130249793 Zhu et al. Sep 2013 A1
20130253029 Jain et al. Sep 2013 A1
20130278499 Anderson Oct 2013 A1
20130278501 Bulzacki Oct 2013 A1
20130280830 Ito et al. Oct 2013 A1
20130322729 Mestha et al. Dec 2013 A1
20130332438 Li et al. Dec 2013 A1
20130345569 Mestha et al. Dec 2013 A1
20140005809 Frei et al. Jan 2014 A1
20140022108 Alberth et al. Jan 2014 A1
20140028539 Newham et al. Jan 2014 A1
20140049487 Konertz et al. Feb 2014 A1
20140050354 Heim et al. Feb 2014 A1
20140051941 Messerschmidt Feb 2014 A1
20140070957 Longinotti-Buitoni et al. Mar 2014 A1
20140072190 Wu et al. Mar 2014 A1
20140073486 Ahmed et al. Mar 2014 A1
20140073969 Zou et al. Mar 2014 A1
20140081100 Muhsin et al. Mar 2014 A1
20140095480 Marantz et al. Apr 2014 A1
20140097979 Nohara et al. Apr 2014 A1
20140121540 Raskin May 2014 A1
20140135631 Brumback et al. May 2014 A1
20140139422 Mistry et al. May 2014 A1
20140139616 Pinter et al. May 2014 A1
20140143678 Mistry et al. May 2014 A1
20140149859 Van Dyken et al. May 2014 A1
20140181509 Liu Jun 2014 A1
20140184496 Gribetz et al. Jul 2014 A1
20140184499 Kim Jul 2014 A1
20140188989 Stekkelpak et al. Jul 2014 A1
20140191939 Penn et al. Jul 2014 A1
20140200416 Kashef et al. Jul 2014 A1
20140201690 Holz Jul 2014 A1
20140208275 Mongia et al. Jul 2014 A1
20140215389 Walsh et al. Jul 2014 A1
20140239065 Zhou et al. Aug 2014 A1
20140244277 Krishna Rao et al. Aug 2014 A1
20140246415 Wittkowski Sep 2014 A1
20140247212 Kim et al. Sep 2014 A1
20140250515 Jakobsson Sep 2014 A1
20140253431 Gossweiler et al. Sep 2014 A1
20140253709 Bresch et al. Sep 2014 A1
20140262478 Harris et al. Sep 2014 A1
20140275854 Venkatraman et al. Sep 2014 A1
20140280295 Kurochikin et al. Sep 2014 A1
20140281975 Anderson Sep 2014 A1
20140282877 Mahaffey et al. Sep 2014 A1
20140297006 Sadhu Oct 2014 A1
20140298266 Lapp Oct 2014 A1
20140300506 Alton et al. Oct 2014 A1
20140306936 Dahl et al. Oct 2014 A1
20140309855 Tran Oct 2014 A1
20140316261 Lux et al. Oct 2014 A1
20140318699 Longinotti-Buitoni et al. Oct 2014 A1
20140324888 Xie et al. Oct 2014 A1
20140329567 Chan et al. Nov 2014 A1
20140333467 Inomata Nov 2014 A1
20140343392 Yang Nov 2014 A1
20140347295 Kim et al. Nov 2014 A1
20140357369 Callens et al. Dec 2014 A1
20140368441 Touloumtzis Dec 2014 A1
20140376788 Xu et al. Dec 2014 A1
20150002391 Chen Jan 2015 A1
20150009096 Lee et al. Jan 2015 A1
20150026815 Barrett Jan 2015 A1
20150029050 Driscoll et al. Jan 2015 A1
20150030256 Brady et al. Jan 2015 A1
20150040040 Balan et al. Feb 2015 A1
20150046183 Cireddu Feb 2015 A1
20150062033 Ishihara Mar 2015 A1
20150068069 Tran et al. Mar 2015 A1
20150077282 Mohamadi Mar 2015 A1
20150085060 Fish et al. Mar 2015 A1
20150091820 Rosenberg et al. Apr 2015 A1
20150091858 Rosenberg et al. Apr 2015 A1
20150091859 Rosenberg et al. Apr 2015 A1
20150095987 Potash et al. Apr 2015 A1
20150099941 Tran Apr 2015 A1
20150100328 Kress et al. Apr 2015 A1
20150106770 Shah et al. Apr 2015 A1
20150109164 Takaki Apr 2015 A1
20150112606 He et al. Apr 2015 A1
20150133017 Liao et al. May 2015 A1
20150143601 Longinotti-Buitoni et al. May 2015 A1
20150145805 Liu May 2015 A1
20150162729 Reversat et al. Jun 2015 A1
20150177866 Hwang et al. Jun 2015 A1
20150185314 Corcos et al. Jul 2015 A1
20150199045 Robucci et al. Jul 2015 A1
20150223733 Al-Alusi Aug 2015 A1
20150226004 Thompson Aug 2015 A1
20150229885 Offenhaeuser Aug 2015 A1
20150256763 Niemi Sep 2015 A1
20150261320 Leto Sep 2015 A1
20150268027 Gerdes Sep 2015 A1
20150268799 Starner et al. Sep 2015 A1
20150277569 Sprenger et al. Oct 2015 A1
20150280102 Tajitsu et al. Oct 2015 A1
20150285906 Hooper et al. Oct 2015 A1
20150287187 Redtel Oct 2015 A1
20150312041 Choi Oct 2015 A1
20150314780 Stenneth et al. Nov 2015 A1
20150317518 Fujimaki et al. Nov 2015 A1
20150323993 Levesque et al. Nov 2015 A1
20150332075 Burch Nov 2015 A1
20150341550 Lay Nov 2015 A1
20150346820 Poupyrev et al. Dec 2015 A1
20150350902 Baxley et al. Dec 2015 A1
20150351703 Phillips et al. Dec 2015 A1
20150375339 Sterling et al. Dec 2015 A1
20160018948 Parvarandeh et al. Jan 2016 A1
20160026253 Bradski et al. Jan 2016 A1
20160038083 Ding et al. Feb 2016 A1
20160041617 Poupyrev Feb 2016 A1
20160041618 Poupyrev Feb 2016 A1
20160042169 Polehn Feb 2016 A1
20160048235 Poupyrev Feb 2016 A1
20160048236 Poupyrev Feb 2016 A1
20160048672 Lux et al. Feb 2016 A1
20160054792 Poupyrev Feb 2016 A1
20160054803 Poupyrev Feb 2016 A1
20160054804 Gollakata Feb 2016 A1
20160055201 Poupyrev et al. Feb 2016 A1
20160090839 Stolarcyzk Mar 2016 A1
20160098089 Poupyrev Apr 2016 A1
20160100166 Dragne et al. Apr 2016 A1
20160103500 Hussey et al. Apr 2016 A1
20160106328 Mestha et al. Apr 2016 A1
20160131741 Park May 2016 A1
20160140872 Palmer et al. May 2016 A1
20160145776 Roh May 2016 A1
20160146931 Rao et al. May 2016 A1
20160170491 Jung Jun 2016 A1
20160171293 Li et al. Jun 2016 A1
20160186366 McMaster Jun 2016 A1
20160206244 Rogers Jul 2016 A1
20160213331 Gil et al. Jul 2016 A1
20160216825 Forutanpour Jul 2016 A1
20160220152 Meriheina et al. Aug 2016 A1
20160249698 Berzowska et al. Sep 2016 A1
20160252607 Saboo et al. Sep 2016 A1
20160253044 Katz Sep 2016 A1
20160259037 Molchanov et al. Sep 2016 A1
20160262685 Wagner et al. Sep 2016 A1
20160282988 Poupyrev Sep 2016 A1
20160283101 Schwesig et al. Sep 2016 A1
20160284436 Fukuhara et al. Sep 2016 A1
20160287172 Morris et al. Oct 2016 A1
20160299526 Inagaki et al. Oct 2016 A1
20160320852 Poupyrev Nov 2016 A1
20160320853 Lien et al. Nov 2016 A1
20160320854 Lien et al. Nov 2016 A1
20160321428 Rogers Nov 2016 A1
20160338599 DeBusschere et al. Nov 2016 A1
20160345638 Robinson et al. Dec 2016 A1
20160349790 Connor Dec 2016 A1
20160349845 Poupyrev et al. Dec 2016 A1
20160377712 Wu et al. Dec 2016 A1
20170029985 Tajitsu et al. Feb 2017 A1
20170052618 Lee et al. Feb 2017 A1
20170060254 Molchanov et al. Mar 2017 A1
20170060298 Hwang et al. Mar 2017 A1
20170075481 Chou et al. Mar 2017 A1
20170075496 Rosenberg et al. Mar 2017 A1
20170097413 Gillian et al. Apr 2017 A1
20170097684 Lien Apr 2017 A1
20170115777 Poupyrev Apr 2017 A1
20170124407 Micks et al. May 2017 A1
20170125940 Karagozler et al. May 2017 A1
20170196513 Longinotti-Buitoni et al. Jul 2017 A1
20170231089 Van Keymeulen Aug 2017 A1
20170232538 Robinson et al. Aug 2017 A1
20170233903 Jeon Aug 2017 A1
20170249033 Podhajny et al. Aug 2017 A1
20170322633 Shen et al. Nov 2017 A1
20170325337 Karagozler et al. Nov 2017 A1
20170325518 Poupyrev et al. Nov 2017 A1
20170329425 Karagozler et al. Nov 2017 A1
20180000354 Debusschere et al. Jan 2018 A1
20180000355 Debusschere et al. Jan 2018 A1
20180004301 Poupyrev Jan 2018 A1
20180005766 Fairbanks et al. Jan 2018 A1
20180046258 Poupyrev Feb 2018 A1
20180095541 Gribetz et al. Apr 2018 A1
20180106897 Shouldice et al. Apr 2018 A1
20180113032 Dickey et al. Apr 2018 A1
20180157330 Gu et al. Jun 2018 A1
20180160943 Fyfe et al. Jun 2018 A1
20180177464 Debusschere et al. Jun 2018 A1
20180196527 Poupyrev et al. Jul 2018 A1
20180256106 Rogers et al. Sep 2018 A1
20180296163 Debusschere et al. Oct 2018 A1
20180321841 Lapp Nov 2018 A1
20190033981 Poupyrev Jan 2019 A1
20190138109 Poupyrev et al. May 2019 A1
20190155396 Lien et al. May 2019 A1
20190208837 Poupyrev et al. Jul 2019 A1
20190232156 Amihood et al. Aug 2019 A1
20190243464 Lien et al. Aug 2019 A1
20190257939 Schwesig et al. Aug 2019 A1
20190278379 Gribetz et al. Sep 2019 A1
20190321719 Gillian et al. Oct 2019 A1
20190391667 Poupyrev Dec 2019 A1
20190394884 Karagozler et al. Dec 2019 A1
20200064924 Poupyrev et al. Feb 2020 A1
20200089314 Poupyrev et al. Mar 2020 A1
Foreign Referenced Citations (86)
Number Date Country
1462382 Dec 2003 CN
101751126 Jun 2010 CN
102414641 Apr 2012 CN
102782612 Nov 2012 CN
102893327 Jan 2013 CN
202887794 Apr 2013 CN
103076911 May 2013 CN
103502911 Jan 2014 CN
102660988 Mar 2014 CN
104035552 Sep 2014 CN
103355860 Jan 2016 CN
102011075725 Nov 2012 DE
102013201359 Jul 2014 DE
0161895 Nov 1985 EP
1785744 May 2007 EP
1815788 Aug 2007 EP
2417908 Feb 2012 EP
2637081 Sep 2013 EP
3201726 Aug 2017 EP
2443208 Apr 2008 GB
113860 Apr 1999 JP
2003280049 Oct 2003 JP
2006234716 Sep 2006 JP
2007011873 Jan 2007 JP
2007132768 May 2007 JP
2007266772 Oct 2007 JP
2008287714 Nov 2008 JP
2008293501 Dec 2008 JP
2009037434 Feb 2009 JP
2011102457 May 2011 JP
201218583 Sep 2012 JP
2012185833 Sep 2012 JP
2012198916 Oct 2012 JP
2012208714 Oct 2012 JP
2013196047 Sep 2013 JP
2013251913 Dec 2013 JP
1020060102516 Nov 2008 KR
100987650 Oct 2010 KR
100987850 Oct 2010 KR
1020140055985 May 2014 KR
101999712 Jan 2017 KR
101914850 Oct 2018 KR
201425974 Jul 2014 TW
WO-9001895 Mar 1990 WO
WO-0130123 Apr 2001 WO
WO-2001027855 Apr 2001 WO
WO-0175778 Oct 2001 WO
WO-2002082999 Oct 2002 WO
2004004557 Jan 2004 WO
2004053601 Jun 2004 WO
WO-2005033387 Apr 2005 WO
2005103863 Nov 2005 WO
2007125298 Nov 2007 WO
WO-2008061385 May 2008 WO
WO-2009032073 Mar 2009 WO
2009083487 Jul 2009 WO
WO-2010032173 Mar 2010 WO
2010101697 Sep 2010 WO
WO-2012026013 Mar 2012 WO
2012064847 May 2012 WO
WO-2012152476 Nov 2012 WO
WO-2013082806 Jun 2013 WO
WO-2013084108 Jun 2013 WO
2013154864 Oct 2013 WO
WO-2013186696 Dec 2013 WO
WO-2013191657 Dec 2013 WO
WO-2013192166 Dec 2013 WO
WO-2014019085 Feb 2014 WO
2014085369 Jun 2014 WO
WO-2014116968 Jul 2014 WO
WO-2014124520 Aug 2014 WO
WO-2014136027 Sep 2014 WO
WO-2014138280 Sep 2014 WO
WO-2014160893 Oct 2014 WO
WO-2014165476 Oct 2014 WO
WO-2014204323 Dec 2014 WO
WO-2015017931 Feb 2015 WO
WO-2015022671 Feb 2015 WO
2015149049 Oct 2015 WO
2016053624 Apr 2016 WO
2016118534 Jul 2016 WO
2016176471 Nov 2016 WO
2016178797 Nov 2016 WO
2017019299 Feb 2017 WO
20170200949 Nov 2017 WO
2018106306 Jun 2018 WO
Non-Patent Literature Citations (309)
Entry
“Corrected Notice of Allowance”, U.S. Appl. No. 14/930,220, dated Mar. 20, 2017, 2 pages.
“First Action Interview Office Action”, U.S. Appl. No. 14/959,901, dated Apr. 14, 2017, 3 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/060399, dated Jan. 30, 2017, 11 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,038, dated Mar. 22, 2017, 33 pages.
“Pre-Interview Communication”, U.S. Appl. No. 14/715,454, dated Apr. 14, 2017, 3 pages.
“Pre-Interview Communication”, U.S. Appl. No. 14/715,793, dated Mar. 20, 2017, 3 pages.
“Pre-Interview Communication”, U.S. Appl. No. 15/343,067, dated Apr. 19, 2017, 3 pages.
“Textile Wire Brochure”, Retrieved at: http://www.textile-wire.ch/en/home.html, Aug. 7, 2004, 17 pages.
Stoppa,“Wearable Electronics and Smart Textiles: A Critical Review”, In Proceedings of Sensors, vol. 14, Issue 7, Jul. 7, 2014, pp. 11957-11992.
“Combined Search and Examination Report”, GB Application No. 1620891.0, dated May 31, 2017, 9 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 14/930,220, dated May 11, 2017, 2 pages.
“Final Office Action”, U.S. Appl. No. 14/959,799, dated Jul. 19, 2017, 12 pages.
“Final Office Action”, U.S. Appl. No. 14/518,863, dated May 5, 2017, 18 pages.
“First Action Interview Pilot Program Pre-Interview Communication”, U.S. Appl. No. 14/731,195, dated Aug. 1, 2017, 3 pages.
“International Preliminary Report on Patentability”, Application No. PCT/US2015/050903, dated Apr. 13, 2017, 12 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/063874, dated May 11, 2017, 19 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/403,066, dated May 4, 2017, 31 pages.
“Notice of Allowance”, U.S. Appl. No. 15/343,067, dated Jul. 27, 2017, 9 pages.
“Notice of Allowance”, U.S. Appl. No. 14/494,863, dated May 30, 2017, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 14/681,625, dated Jun. 7, 2017, 7 pages.
“Advisory Action”, U.S. Appl. No. 14/504,139, dated Aug. 28, 2017, 3 pages.
“Final Office Action”, U.S. Appl. No. 15/398,147, dated Jun. 30, 2017, 11 pages.
“Final Office Action”, U.S. Appl. No. 14/874,955, dated Jun. 30, 2017, 9 pages.
“Final Office Action”, U.S. Appl. No. 14/504,121, dated Aug. 8, 2017, 16 pages.
“Final Office Action”, U.S. Appl. No. 14/959,901, dated Aug. 25, 2017, 19 pages.
“Final Office Action”, U.S. Appl. No. 14/715,454, dated Sep. 7, 2017, 14 pages.
“Final Office Action”, U.S. Appl. No. 14/715,793, dated Sep. 12, 2017, 7 pages.
“First Action Interview OA”, U.S. Appl. No. 14/715,793, dated Jun. 21, 2017, 3 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/720,632, dated Jun. 14, 2017, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/862,409, dated Jun. 22, 2017, 15 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/959,730, dated Jun. 23, 2017, 14 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/093,533, dated Aug. 24, 2017, 18 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/142,619, dated Aug. 25, 2017, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/959,799, dated Sep. 8, 2017, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/398,147, dated Sep. 8, 2017, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 14/513,875, dated Jun. 28, 2017, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 14/666,155, dated Jul. 10, 2017, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 14/504,038, dated Aug. 7, 2017, 17 pages.
Otto, et al., “System Architecture of a Wireless Body Area Sensor Network for Ubiquitous Health Monitoring”, Journal Mobile Multimedia; vol. 1, No. 4, Jan. 10, 2006, 20 pages.
“Cardiio”, Retrieved From: <http://www.cardiio.com/> Apr. 15, 2015 App Information Retrieved From: <https://itunes.apple.com/us/app/cardiio-touchless-camera-pulse/id542891434?Is=1&mt=8> Apr. 15, 2015, Feb. 24, 2015, 6 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 14/312,486, dated Jan. 23, 2017, 4 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 14/312,486, dated Oct. 28, 2016, 4 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 14/504,061, dated Dec. 27, 2016, 2 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 14/582,896, dated Feb. 6, 2017, 2 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 14/582,896, dated Feb. 23, 2017, 2 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 14/582,896, dated Dec. 19, 2016, 2 pages.
“Extended European Search Report”, EP Application No. 15170577.9, dated Nov. 5, 2015, 12 pages.
“Final Office Action”, U.S. Appl. No. 14/312,486, dated Jun. 3, 2016, 32 pages.
“Final Office Action”, U.S. Appl. No. 14/504,038, dated Sep. 27, 2016, 23 pages.
“Final Office Action”, U.S. Appl. No. 14/504,061, dated Mar. 9, 2016, 10 pages.
“Final Office Action”, U.S. Appl. No. 14/599,954, dated Aug. 10, 2016, 23 pages.
“Final Office Action”, U.S. Appl. No. 14/681,625, dated Dec. 7, 2016, 10 pages.
“Frogpad Introduces Wearable Fabric Keyboard with Bluetooth Technology”, Retrieved From: <http://www.geekzone.co.nz/content.asp?contentid=3898> Mar. 16, 2015, Jan. 7, 2005, 2 pages.
“International Preliminary Report on Patentability”, Application No. PCT/US2015/043963, dated Feb. 16, 2017, 12 pages.
“International Preliminary Report on Patentability”, Application No. PCT/US2015/030388, dated Dec. 15, 2016, 12 pages.
“International Preliminary Report on Patentability”, Application No. PCT/US2015/043949, dated Feb. 16, 2017, 13 pages.
“International Preliminary Report on Patentability”, Application No. PCT/US2015/044774, dated Mar. 2, 2017, 8 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/062082, dated Feb. 23, 2017, 12 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/042013, dated Oct. 26, 2016, 12 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2015/044774, dated Nov. 3, 2015, 12 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/024267, dated Jun. 20, 2016, 13 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/024273, dated Jun. 20, 2016, 13 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/032307, dated Aug. 25, 2016, 13 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/034366, dated Nov. 17, 2016, 13 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/029820, dated Jul. 15, 2016, 14 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/055671, dated Dec. 1, 2016, 14 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/030177, dated Aug. 2, 2016, 15 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2015/043963, dated Nov. 24, 2015, 16 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/024289, dated Aug. 25, 2016, 17 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2015/050903, dated Feb. 19, 2016, 18 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/030115, dated Aug. 8, 2016, 18 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2015/043949, dated Dec. 1, 2015, 18 pages.
“International Search Report and Written Opinion”, Application No. PCT/US2016/033342, dated Oct. 27, 2016, 20 pages.
“Life:X Lifestyle eXplorer”, Retrieved from <https://web.archive.org/web/20150318093841/http://research.microsoft.com/en-us/projects/lifex >, Feb. 3, 2017, 2 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/312,486, dated Oct. 23, 2015, 25 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,038, dated Feb. 26, 2016, 22 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,061, dated Nov. 4, 2015, 8 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,121, dated Jan. 9, 2017, 13 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,139, dated Jan. 27, 2017, 10 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/513,875, dated Feb. 21, 2017, 9 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/518,863, dated Oct. 14, 2016, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/582,896, dated Jun. 29, 2016, 9 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/599,954, dated Jan. 26, 2017, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/599,954, dated Feb. 2, 2016, 17 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/666,155, dated Feb. 3, 2017, 12 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/666,155, dated Aug. 24, 2016, 9 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/681,625, dated Mar. 6, 2017, 7 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/681,625, dated Aug. 12, 2016, 9 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/874,955, dated Feb. 27, 2017, 8 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/930,220, dated Sep. 14, 2016, 15 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/959,799, dated Jan. 27, 2017, 10 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/398,147, dated Mar. 9, 2017, 10 pages.
“Notice of Allowance”, U.S. Appl. No. 14/312,486, dated Oct. 7, 2016, 15 pages.
“Notice of Allowance”, U.S. Appl. No. 14/504,061, dated Sep. 12, 2016, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 14/582,896, dated Nov. 7, 2016, 5 pages.
“Notice of Allowance”, U.S. Appl. No. 14/930,220, dated Feb. 2, 2017, 8 pages.
“Philips Vital Signs Camera”, Retrieved From: <http://www.vitalsignscamera.com/> Apr. 15, 2015, Jul. 17, 2013, 2 pages.
“Pre-Interview Communication”, U.S. Appl. No. 14/494,863, dated Jan. 27, 2017, 5 pages.
“Pre-Interview Communication”, U.S. Appl. No. 14/513,875, dated Oct. 21, 2016, 3 pages.
“Pre-Interview Communication”, U.S. Appl. No. 14/959,730, dated Feb. 15, 2017, 3 pages.
“Pre-Interview Communication”, U.S. Appl. No. 14/959,901, dated Feb. 10, 2017, 3 pages.
“Restriction Requirement”, U.S. Appl. No. 14/666,155, dated Jul. 22, 2016, 5 pages.
“The Dash smart earbuds play back music, and monitor your workout”, Retrieved from <http://newatlas.com/bragi-dash-tracking-earbuds/30808/>, Feb. 13, 2014, 3 pages.
“The Instant Blood Pressure app estimates blood pressure with your smartphone and our algorithm”, Retrieved at: http://www.instantbloodpressure.com/—on Jun. 23, 2016, 6 pages.
Arbabian,“A 94GHz mm-Wave to Baseband Pulsed-Radar for Imaging and Gesture Recognition”, 2012 IEEE, 2012 Symposium on VLSI Circuits Digest of Technical Papers, 2012, 2 pages.
Balakrishnan,“Detecting Pulse from Head Motions in Video”, In Proceedings: CVPR '13 Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition Available at: <http://people.csail.mit.edu/mrub/vidmag/papers/Balakrishnan_Detecting_Pulse_from_2013_CVPR_paper.pdf>, Jun. 23, 2013, 8 pages.
Cheng,“Smart Textiles: From Niche to Mainstream”, IEEE Pervasive Computing, Jul. 2013, pp. 81-84.
Couderc,“Detection of Atrial Fibrillation using Contactless Facial Video Monitoring”, In Proceedings: Heart Rhythm Society, vol. 12, Issue 1 Available at: <http://www.heartrhythmjournal.com/article/S1547-5271(14)00924-2/pdf>, Jan. 2015, 7 pages.
Espina,“Wireless Body Sensor Network for Continuous Cuff-less Blood Pressure Monitoring”, International Summer School on Medical Devices and Biosensors, 2006, Sep. 2006, 5 pages.
Farringdon,“Wearable Sensor Badge & Sensor Jacket for Context Awareness”, Third International Symposium on Wearable Computers, Oct. 1999, 7 pages.
Godana,“Human Movement Characterization in Indoor Environment using GNU Radio Based Radar”, Retrieved at: http://repository.tudelft.nl/islandora/object/uuid:414e1868-dd00-4113-9989-4c213f1f7094?collection=education, Nov. 30, 2009, 100 pages.
He,“A Continuous, Wearable, and Wireless Heart Monitor Using Head Ballistocardiogram (BCG) and Head Electrocardiogram (ECG) with a Nanowatt ECG Heartbeat Detection Circuit”, In Proceedings: Thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology Available at: <http://dspace.mit.edu/handle/1721.1/79221>, Feb. 2013, 137 pages.
Holleis,“Evaluating Capacitive Touch Input on Clothes”, Proceedings of the 10th International Conference on Human Computer Interaction, Jan. 1, 2008, 10 pages.
Klabunde,“Ventricular Pressure-Volume Loop Changes in Valve Disease”, Retrieved From <https://web.archive.org/web/20101201185256/http://cvphysiology.com/Heart%20Disease/HD009.htm>, Dec. 1, 2010, 8 pages.
Matthews,“Venous Pulse”, Retrieved at: http://www.rjmatthewsmd.com/Definitions/venous_pulse.htm—on Nov. 30, 2016, Apr. 13, 2013, 7 pages.
Nakajima,“Development of Real-Time Image Sequence Analysis for Evaluating Posture Change and Respiratory Rate of a Subject in Bed”, In Proceedings: Physiological Measurement, vol. 22, No. 3 Retrieved From: <http://iopscience.iop.org/0967-3334/22/3/401/pdf/0967-3334_22_3_401.pdf> Feb. 27, 2015, Aug. 2001, 8 pages.
Palese,“The Effects of Earphones and Music on the Temperature Measured by Infrared Tympanic Thermometer: Preliminary Results”, ORL—head and neck nursing: official journal of the Society of Otorhinolaryngology and Head-Neck Nurses 32.2, 2013, pp. 8-12.
Patel,“Applications of Electrically Conductive Yarns in Technical Textiles”, International Conference on Power System Technology (POWECON), Oct. 30, 2012, 6 pages.
Poh,“A Medical Mirror for Non-contact Health Monitoring”, In Proceedings: ACM SIGGRAPH Emerging Technologies Available at: <http://affect.media.mit.edu/pdfs/11.Poh-etal-SIGGRAPH.pdf>, 2011, 1 page.
Poh,“Non-contact, Automated Cardiac Pulse Measurements Using Video Imaging and Blind Source Separation.”, In Proceedings: Optics Express, vol. 18, No. 10 Available at: <http://www.opticsinfobase.org/view_article.cfm?gotourl=http%3A%2F%2Fwww%2Eopticsinfobase%2Eorg%2FDirectPDFAccess%2F77B04D55%2DBC95%2D6937%2D5BAC49A426378CO2%5F199381%2Foe%2D18%2D10%2D10762%2Ep, May 7, 2010, 13 pages.
Pu,“Gesture Recognition Using Wireless Signals”, Oct. 2014, pp. 15-18.
Pu,“Whole-Home Gesture Recognition Using Wireless Signals”, MobiCom '13 Proceedings of the 19th annual international conference on Mobile computing & networking, Aug. 27, 2013, 12 pages.
Schneegass,“Towards a Garment OS: Supporting Application Development for Smart Garments”, Wearable Computers, ACM, Sep. 2014, 6 pages.
Wang,“Exploiting Spatial Redundancy of Image Sensor for Motion Robust rPPG”, In Proceedings: IEEE Transactions on Biomedical Engineering, vol. 62, Issue 2, Jan. 19, 2015, 11 pages.
Wang,“Micro-Doppler Signatures for Intelligent Human Gait Recognition Using a UWB Impulse Radar”, 2011 IEEE International Symposium on Antennas and Propagation (APSURSI), Jul. 3, 2011, pp. 2103-2106.
Wijesiriwardana,“Capacitive Fibre-Meshed Transducer for Touch & Proximity Sensing Applications”, IEEE Sensors Journal, IEEE Service Center, Oct. 1, 2005, 5 pages.
Zhadobov,“Millimeter-wave Interactions with the Human Body: State of Knowledge and Recent Advances”, International Journal of Microwave and Wireless Technologies, Mar. 1, 2011, 11 pages.
Zhang,“Study of the Structural Design and Capacitance Characteristics of Fabric Sensor”, Advanced Materials Research (vols. 194-196), Feb. 21, 2011, 8 pages.
“Extended European Search Report”, European Application No. 19164113.3, dated Jun. 13, 2019, 11 pages.
“Final Office Action”, U.S. Appl. No. 14/959,901, dated May 30, 2019, 18 pages.
“Final Office Action”, U.S. Appl. No. 16/238,464, dated Jul. 25, 2019, 15 pages.
“First Action Interview Office Action”, U.S. Appl. No. 15/917,238, dated Jun. 6, 2019, 6 pages.
“Foreign Office Action”, Japanese Application No. 2018156138, dated May 22, 2019, 3 pages.
“International Preliminary Report on Patentability”, PCT Application No. PCT/US2017/051663, dated Jun. 20, 2019, 10 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/424,263, dated May 23, 2019, 12 pages.
“Notice of Allowance”, U.S. Appl. No. 15/287,308, dated Jul. 17, 2019, 17 Pages.
“Notice of Allowance”, U.S. Appl. No. 15/917,238, dated Aug. 21, 2019, 13 pages.
“Notice of Allowance”, U.S. Appl. No. 16/389,402, dated Aug. 21, 2019, 7 Pages.
“Notice of Allowance”, U.S. Appl. No. 15/352,194, dated Jun. 26, 2019, 8 pages.
“Notice of Allowance”, U.S. Appl. No. 15/287,155, dated Jul. 25, 2019, 7 pages.
“EP Appeal Decision”, European Application No. 10194359.5, dated May 28, 2019, 20 pages.
“Final Office Action”, U.S. Appl. No. 15/287,394, dated Sep. 30, 2019, 38 Pages.
“Foreign Office Action”, Korean Application No. 1020197019768.
“Foreign Office Action”, Korean Application No. 1020197004803, dated Oct. 14, 2019, 2 pages.
“Foreign Office Action”, Japanese Application No. 2018156138, dated Sep. 30, 2019, 3 pages.
“Galaxy S4 Air Gesture”, Galaxy S4 Guides, https://allaboutgalaxys4.com/galaxy-s4-features-explained/air-gesture/, 4 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/286,537, dated Sep. 3, 2019, 28 Pages.
“Non-Final Office Action”, U.S. Appl. No. 15/791,044, dated Sep. 30, 2019, 22 Pages.
“Non-Final Office Action”, U.S. Appl. No. 16/153,395, dated Oct. 22, 2019, 10 Pages.
“Notice of Allowance”, U.S. Appl. No. 15/287,253, dated Aug. 26, 2019, 13 Pages.
“Notice of Allowance”, U.S. Appl. No. 16/356,748, dated Oct. 17, 2019, 9 Pages.
“Notice of Allowance”, U.S. Appl. No. 16/238,464, dated Nov. 4, 2019, 10 Pages.
“Samsung Galaxy S4 Air Gestures”, Video from https://www.youtube.com/watch?v=375Hb87yGcg, May 7, 2013.
Amihood, et al., “Closed-Loop Manufacturing System Using Radar”, Technical Disclosure Commons; Retrieved from http://www.tdcommons.org/dpubs_series/464, Apr. 17, 2017, 8 pages.
Karagozler, et al., “Embedding Radars in Robots to Accurately Measure Motion”, Technical Disclosure Commons; Retrieved from http://www.tdcommons.org/dpubs_series/454, Mar. 30, 2017, 8 pages.
Lien, et al., “Embedding Radars in Robots for Safety and Obstacle Detection”, Technical Disclosure Commons; Retrieved from http://www.tdcommons.org/dpubs_series/455, Apr. 2, 2017, 10 pages.
Pu, et al., “Whole-Home Gesture Recognition Using Wireless Signals”, MobiCom'13, Sep. 30-Oct. 4, Miami, FL, USA, Sep. 2013, 12 pages.
“Final Office Action”, U.S. Appl. No. 15/403,066, dated Oct. 5, 2017, 31 pages.
“Foreign Office Action”, KR Application No. 10-2016-7035397, dated Sep. 20, 2017, 5 pages.
“Foreign Office Action”, JP Application No. 2016567813, dated Sep. 22, 2017, 8 pages.
“International Preliminary Report on Patentability”, PCT Application No. PCT/US2016/026756, dated Oct. 19, 2017, 8 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/518,863, dated Sep. 29, 2017, 20 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/142,689, dated Oct. 4, 2017, 18 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,139, dated Oct. 18, 2017, 12 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/699,181, dated Oct. 18, 2017, 33 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/595,649, dated Oct. 31, 2017, 16 pages.
“Notice of Allowance”, U.S. Appl. No. 14/874,955, dated Oct. 20, 2017, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 14/681,625, dated Oct. 23, 2017, 8 pages.
“Notice of Allowance”, U.S. Appl. No. 15/398,147, dated Nov. 15, 2017, 8 pages.
“Written Opinion”, PCT Application No. PCT/US2017/032733, dated Jul. 26, 2017, 5 pages.
“Apple Watch Used Four Sensors to Detect your Pulse”, retrieved from http://www.theverge.com/2014/9/9/6126991 / apple-watch-four-back-sensors-detect-activity on Sep. 23, 2017 as cited in PCT search report for PCT Application No. PCT/US2016/026756 dated Nov. 10, 2017; The Verge, paragraph 1, Sep. 9, 2014, 4 pages.
“Non-Invasive Quantification of Peripheral Arterial Volume Distensibility and its Non-Lineaer Relationship with Arterial Pressure”, Journal of Biomechanics, Pergamon Press, vol. 42, No. 8; as cited in the search report for PCT/US2016/013968 citing the whole document, but in particular the abstract, May 29, 2009, 2 pages.
“Pre-Interview Office Action”, U.S. Appl. No. 14/862,409, dated Sep. 15, 2017, 16 pages.
“Pressure-Volume Loop Analysis in Cardiology”, retrieved from https://en.wikipedia.org/w/index.php?t itle=Pressure-volume loop analysis in card iology&oldid=636928657 on Sep. 23, 2017; Obtained per link provided in search report from PCT/US2016/01398 on Jul. 28, 2016, Dec. 6, 2014, 10 pages.
“Written Opinion”, PCT Application No. PCT/US2016/042013, dated Feb. 2, 2017, 6 pages.
“Written Opinion”, PCT Application PCT/US2016/013968, dated Jul. 28, 2016, 9 pages.
“Written Opinion”, PCT Application No. PCT/US2016/026756, dated Nov. 10, 2016, 7 pages.
Ishijima, “Unobtrusive Approaches to Monitoring Vital Signs at Home”, Medical & Biological Engineering and Computing, Springer, Berlin, DE, vol. 45, No. 11 as cited in search report for PCT/US2016/013968 dated Jul. 28, 2016, Sep. 26, 2007, 3 pages.
“Final Office Action”, U.S. Appl. No. 15/595,649, dated May 23, 2018, 13 pages.
“Final Office Action”, U.S. Appl. No. 15/142,689, dated Jun. 1, 2018, 16 pages.
“Final Office Action”, U.S. Appl. No. 14/874,955, dated Jun. 11, 2018, 9 pages.
“Final Office Action”, U.S. Appl. No. 14/959,901, dated Jun. 15, 2018, 21 pages.
“Final Office Action”, U.S. Appl. No. 15/286,152, dated Jun. 26, 2018, 25 pages.
“Final Office Action”, U.S. Appl. No. 15/267,181, dated Jun. 7, 2018, 31 pages.
“Final Office Action”, U.S. Appl. No. 14/504,121, dated Jul. 9, 2018, 23 pages.
“First Action Interview Office Action”, U.S. Appl. No. 14/731,195, dated Jun. 21, 2018, 4 pages.
“Foreign Office Action”, Korean Application No. 1020187012629, dated May 24, 2018, 6 pages.
“Foreign Office Action”, Chinese Application No. 201721290290.3, dated Jun. 6, 2018, 3 pages.
“Foreign Office Action”, Chinese Application No. 201580036075.8, dated Jul. 4, 2018, 14 page.
“Foreign Office Action”, CN Application No. 201580034908.7, dated Jul. 3, 2018, 12 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/720,632, dated May 18, 2018, 20 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/809,901, dated May 24, 2018, 13 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/586,174, dated Jun. 18, 2018, 7 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/286,512, dated Jul. 19, 2018, 15 pages.
“Notice of Allowance”, U.S. Appl. No. 14/715,793, dated Jul. 6, 2018, 5 pages.
“Notice of Allowance”, U.S. Appl. No. 15/362,359, dated Aug. 3, 2018, 8 pages.
“Notice of Allowance”, U.S. Appl. No. 14/862,409, dated Jun. 6, 2018, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 15/142,619, dated Aug. 13, 2018, 9 pages.
“Pre-Interview Communication”, U.S. Appl. No. 15/287,359, filed Jul. 24, 2018, 2 pages.
Zhadobov, et al., “Millimeter-Wave Interactions with the Human Body: State of Knowledge and Recent Advances”, International Journal of Microwave and Wireless Technologies, p. 1 of 11. # Cambridge University Press and the European Microwave Association, doi:10.1017/S1759078711000122, 2011.
“Final Office Action”, U.S. Appl. No. 15/093,533, dated Mar. 21, 2018, 19 pages.
“Final Office Action”, U.S. Appl. No. 14/715,454, dated Apr. 17, 2018, 19 pages.
“Final Office Action”, U.S. Appl. No. 14/518,863, dated Apr. 5, 2018, 21 pages.
“Final Office Action”, U.S. Appl. No. 14/504,139, dated May 1, 2018, 14 pages.
“Final Office Action”, U.S. Appl. No. 14/699,181, dated May 4, 2018, 41 pages.
“First Action Interview Office Action”, U.S. Appl. No. 15/286,152, dated Mar. 1, 2018, 5 pages.
“First Action Interview Office Action”, U.S. Appl. No. 15/166,198, dated Apr. 25, 2018, 8 pages.
“Foreign Office Action”, Chinese Application No. 201721290290.3, dated Mar. 9, 2018, 2 pages.
“Foreign Office Action”, EP Application No. 15754323.2, dated Mar. 9, 2018, 8 pages.
“Foreign Office Action”, Japanese Application No. 2016-567839, dated Apr. 3, 2018, 3 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/287,253, dated Apr. 5, 2018, 17 pages.
“Notice of Allowance”, U.S. Appl. No. 14/666,155, dated Feb. 20, 2018, 5 pages.
“Notice of Allowance”, U.S. Appl. No. 14/959,730, dated Feb. 22, 2018, 8 pages.
“Pre-Interview Communication”, U.S. Appl. No. 15/166,198, dated Mar. 8, 2018, 8 pages.
“Pre-Interview Communication”, U.S. Appl. No. 15/362,359, dated May 17, 2018, 4 pages.
“Thermofocus No Touch Forehead Thermometer”, Technimed, Internet Archive. Dec. 24, 2014. https://web.archive.org/web/20141224070848/http://www.tecnimed.it:80/thermofocus-forehead-thermometer-H1N1-swine-flu.html, Dec. 24, 2018, 4 pages.
“Written Opinion”, PCT Application No. PCT/US2017/032733, dated Jul. 24, 2017, 5 pages.
“Corrected Notice of Allowance”, U.S. Appl. No. 15/362,359, dated Sep. 17, 2018, 10 pages.
“Final Office Action”, U.S. Appl. No. 14/731,195, dated Oct. 11, 2018, 12 pages.
“Final Office Action”, U.S. Appl. No. 15/166,198, dated Sep. 27, 2018, 33 pages.
“Foreign Office Action”, Korean Application No. 10-2016-7036015, dated Oct. 15, 2018, 3 pages.
“Foreign Office Action”, Chinese Application No. 201580034536.8, dated Oct. 9, 2018.
“Non-Final Office Action”, U.S. Appl. No. 15/287,253, dated Sep. 7, 2018, 20 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/959,901, dated Oct. 11, 2018, 22 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/287,308, dated Oct. 15, 2018, 18 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/286,152, dated Oct. 19, 2018, 27 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/286,837, dated Oct. 26, 2018, 10 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,139, dated Oct. 5, 2018, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/142,829, dated Aug. 16, 2018, 15 pages.
“Notice of Allowance”, U.S. Appl. No. 15/142,689, dated Oct. 30, 2018, 9 pages.
“Notice of Allowance”, U.S. Appl. No. 14/874,955, dated Oct. 4, 2018, 8 pages.
“Notice of Allowance”, U.S. Appl. No. 15/287,200, dated Nov. 6, 2018, 19 pages.
“Notice of Allowance”, U.S. Appl. No. 15/595,649, dated Sep. 14, 2018, 8 pages.
“Notice of Allowance”, U.S. Appl. No. 15/586,174, dated Sep. 24, 2018, 5 pages.
“Pre-Interview Communication”, U.S. Appl. No. 15/286,495, dated Sep. 10, 2018, 4 pages.
“Restriction Requirement”, U.S. Appl. No. 15/286,537, dated Aug. 27, 2018, 8 pages.
“Written Opinion”, PCT Application No. PCT/US2017/051663, dated Oct. 12, 2018, 8 pages.
Gürbüz, et al., “Detection and Identification of Human Targets in Radar Data”, Proc. SPIE 6567, Signal Processing, Sensor Fusion, and Target Recognition XVI, 656701, May 7, 2007, 12 pages.
Pu, et al., “Whole-Home Gesture Recognition Using Wireless Signals”, MobiCom'13, Sep. 30-Oct. 4, Miami, FL, USA, 2013, 12 pages.
“Final Office Action”, U.S. Appl. No. 14/809,901, dated Dec. 13, 2018, 7 pages.
“Final Office Action”, U.S. Appl. No. 15/286,512, dated Dec. 26, 2018, 15 pages.
“Final Office Action”, U.S. Appl. No. 15/287,308, dated Feb. 8, 2019, 23 pages.
“Foreign Office Action”, Japanese Application No. 2018021296, dated Dec. 25, 2018, 8 pages.
“International Preliminary Report on Patentability”, PCT Application No. PCT/US2017/032733, dated Nov. 29, 2018, 7 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/286,537, dated Nov. 19, 2018, 18 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/287,155, dated Dec. 10, 2018, 12 pages.
“Notice of Allowance”, U.S. Appl. No. 15/286,495, dated Jan. 17, 2019, 5 pages.
“Notice of Allowance”, U.S. Appl. No. 15/595,649, dated Jan. 3, 2019, 5 pages.
“Notice of Allowance”, U.S. Appl. No. 15/142,829, dated Feb. 6, 2019, 8 pages.
“Notice of Allowance”, U.S. Appl. No. 14/504,137, dated Feb. 6, 2019, 9 pages.
“Pre-Interview Communication”, U.S. Appl. No. 15/703,511, dated Feb. 11, 2019, 5 pages.
“Restriction Requirement”, U.S. Appl. No. 15/352,194, dated Feb. 6, 2019, 8 pages.
Garmatyuk, et al., “Ultra-Wideband Continuous-Wave Random Noise Arc-SAR”, IEEE Transaction on Geoscience and Remote Sensing, vol. 40, No. 12, Dec. 2002, Dec. 2002, 10 pages.
Geisheimer, et al., “A Continuous-Wave (CW) Radar for Gait Analysis”, IEEE 2001, 2001, 5 pages.
Kubota, et al., “A Gesture Recognition Approach by using Microwave Doppler Sensors”, IPSJ SIG Technical Report, 2009 (6), Information Processing Society of Japan, Apr. 15, 2010, pp. 1-8, Apr. 15, 2010, 13 pages.
Pu, et al., “Whole-Home Gesture Recognition Using Wireless Signals”, Proceedings of the 19th annual international conference on Mobile computing & networking (MobiCom'13), US, ACM, Sep. 30, 2013, pp. 27-38, Sep. 30, 2013, 12 pages.
“Final Office Action”, U.S. Appl. No. 15/287,155, dated Apr. 10, 2019, 11 pages.
“Final Office Action”, U.S. Appl. No. 15/286,537, dated Apr. 19, 2019, 21 pages.
“Final Office Action”, U.S. Appl. No. 15/287,253, dated Apr. 2, 2019, 10 pages.
“Foreign Office Action”, Chinese Application No. 201580034908.7, dated Feb. 19, 2019, 10 pages.
“Foreign Office Action”, Chinese Application No. 201580036075.8, dated Feb. 19, 2019, 5 pages.
“Foreign Office Action”, Korean Application No. 1020197004803, dated Apr. 26, 2019, 6 pages.
“Foreign Office Action”, Japanese Application No. 2018-021296, dated Apr. 9, 2019, 3 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/166,198, dated Feb. 21, 2019, 48 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/287,394, dated Mar. 22, 2019, 39 pages.
“Non-Final Office Action”, U.S. Appl. No. 16/238,464, dated Mar. 7, 2019, 15 pages.
“Notice of Allowance”, U.S. Appl. No. 15/286,152, dated Mar. 5, 2019, 23 pages.
“Notice of Allowance”, U.S. Appl. No. 15/286,837, dated Mar. 6, 2019, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 15/703,511, dated Apr. 16, 2019, 5 pages.
“Notice of Allowance”, U.S. Appl. No. 14/731,195, dated Apr. 24, 2019, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 15/286,512, dated Apr. 9, 2019, 14 pages.
“Pre-Interview Communication”, U.S. Appl. No. 15/917,238, dated May 1, 2019, 6 pages.
“Final Office Action”, U.S. Appl. No. 14/959,730, dated Nov. 22, 2017, 16 pages.
“Final Office Action”, U.S. Appl. No. 15/142,819, dated Feb. 8, 2018, 15 pages.
“Foreign Office Action”, JP App. No. 2016-567813, dated Jan. 16, 2018, 3 pages.
“Foreign Office Action”, Korean Application No. 10-2016-7038396, dated Jan. 3, 2018, 7 pages.
“International Search Report and Written Opinion”, PCT/US2017/047691, dated Nov. 16, 2017, 13 pages.
“International Search Report and Written Opinion”, PCT Application No. PCT/US2017/051663, dated Nov. 29, 2017, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/715,454, dated Jan. 11, 2018, 16 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/504,121, dated Jan. 2, 2018, 19 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/959,901, dated Jan. 8, 2018, 21 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/862,409, dated Dec. 14, 2017, 17 pages.
“Non-Final Office Action”, U.S. Appl. No. 15/267,181, dated Feb. 8, 2018, 29 pages.
“Non-Final Office Action”, U.S. Appl. No. 14/074,955, dated Feb. 8, 2018, 7 pages.
“Notice of Allowance”, U.S. Appl. No. 15/403,056, dated Jan. 8, 2018, 18 pages.
“Notice of Allowance”, U.S. Appl. No. 14/715,793, dated Dec. 18, 2017, 5 pages.
“Pre-Interview First Office Action”, U.S. Appl. No. 15/288,152, dated Feb. 8, 2018, 4 pages.
“Pre-Interview Office Action”, U.S. Appl. No. 14/731,195, dated Dec. 20, 2017, 4 pages.
“Preliminary Report on Patentability”, PCT Application No. PCT/US2018/042013, dated Jan. 30, 2018, 7 pages.
“Preliminary Report on Patentability”, PCT Application No. PCT/US2018/032307, dated Dec. 7, 2017, 9 pages.
“Restriction Requirement”, U.S. Appl. No. 15/362,359, dated Jan. 8, 2018, 5 pages.
Bondade, et al., “A linear-assisted DC-DC hybrid power converter for envelope tracking RF power amplifiers”, 2014 IEEE Energy Conversion Congress and Exposition (ECCE), IEEE, Sep. 14, 2014, pp. 5789-5773, XP032880873, DOI: 10.1109/ECCE.2014.6954193, Sep. 14, 2014, 5 pages.
Fan, et al., “Wreless Hand Gesture Recognition Based on Continuous-Wave Doppler Radar Sensors”, IEEE Transactions on Microwave Theory and Techniques, Plenum, USA, vol. 84, No. 11, Nov. 1, 2016 (Nov. 1, 2016). pp. 4012-4012. XP011633246, ISSN: 0018-9480, DOI: 10,1109/TMTT.2016.2610427, Nov. 1, 2019, 9 pages.
Lien, et al., “Soli: Ubiquitous Gesture Sensing with Millimeter Wave Radar”, ACM Transactions on Graphics (TOG), ACM, US, vol. 35, No. 4, Jul. 11, 2018 (Jul. 11, 2018), pp. 1-19, XP058275791, ISSN: 0730-0301, DOI: 10.1145/2897824.2925953, Jul. 11, 2016, 19 pages.
Martinez-Garcia, et al., “Four-quadrant linear-assisted DC/DC voltage regulator”, Analog Integrated Circuits and Signal Processing, Springer New York LLC, US, vol. 88, No. 1, Apr. 23, 2016 (Apr. 23, 2016) , pp. 151-160, XP035898949, ISSN: 0925-1030, DOI: 10.1007/S10470-016-0747-8, Apr. 23, 2016, 10 pages.
Skolnik, “CW and Frequency-Modulated Radar”, In: “Introduction to Radar Systems”, Jan. 1, 1981 (Jan. 1, 1981), McGraw Hill, XP055047645, ISBN: 978-0-07-057909-5 pp. 68-100, p. 95-p. 97, Jan. 1, 1981, 18 pages.
Zheng, et al., “Doppler Bio-Signal Detection Based Time-Domain Hand Gesture Recognition”, 2013 IEEE MTT-S International Microwave Workshop Series on RF and Wireless Technologies for Biomedical and Healthcare Applications (IMWS-BIO), IEEE, Dec. 9, 2013 (Dec. 9, 2013), p. 3, XP032574214, DOI: 10.11-09/IMWS-BIO.2013.6756200, Dec. 9, 2013, 3 Pages.
“Final Office Action”, U.S. Appl. No. 14/959,799, dated Jan. 4, 2018, 17 pages.
“Final Office Action”, U.S. Appl. No. 14/720,832, dated Jan. 9, 2018, 18 pages.
“Final Office Action”, U.S. Appl. No. 14/959,730, dated Nov. 22, 2017, 18 pages.
“Final Office Action”, U.S. Appl. No. 15/142,619, dated Feb. 8, 2018, 15 pages.
“Notice of Allowance”, U.S. Appl. No. 15/287,394, dated Mar. 4, 2020, 11 Pages.
“Pre-Interview Communication”, U.S. Appl. No. 16/401,611, 4 Pages.
“Final Office Action”, U.S. Appl. No. 15/287,359, dated Feb. 19, 2020, 16 Pages.
“Foreign Office Action”, Korean Application No. 1020197004803, dated Dec. 6, 2019, 2 pages.
“Non-Final Office Action”, U.S. Appl. No. 16/252,477, dated Jan. 10, 2020, 13 Pages.
“Notice of Allowance”, U.S. Appl. No. 16/356,748, dated Feb. 11, 2020, 5 Pages.
“Notice of Allowance”, U.S. Appl. No. 15/791,044, dated Feb. 12, 2020, 8 Pages.
“Notice of Allowance”, U.S. Appl. No. 16/153,395, dated Feb. 20, 2020, 13 Pages.
Related Publications (1)
Number Date Country
20170192523 A1 Jul 2017 US
Provisional Applications (1)
Number Date Country
62059099 Oct 2014 US
Continuations (1)
Number Date Country
Parent 14582896 Dec 2014 US
Child 15462957 US