US 9,575,560 B2Grant
Radar-based gesture-recognition through a wearable device
Issue Date:2017-02-21
•20 Claims
•15 Drawing Sheets
Abstract
This document describes techniques and devices for radar-based gesture-recognition through a wearable device. The techniques enable an easy-to-use input interface through this wearable radar device, in contrast to small or difficult-to-use input interfaces common to wearable computing devices. Further, these techniques are not limited to interfacing with wearable computing devices, but may aid users in controlling various non-wearable devices, such as to control volume on a stereo, pause a movie playing on a television, or select a webpage on a desktop computer.
Metadata
Assignee
- Google Inc.
Inventors
- Ivan Poupyrev
- Gaetano Roberto Aiello
Application Information
Application Number:US 14/312,486
Filing Date:2014-06-23
Priority Date:2014-06-03
Art Unit:2699
Classifications
IPC:
G06F3/01G01S13/89G01S13/88G06F1/16
Field of Search:
G06F 3/014G06F 3/017G06F 3/0488G06F 3/038G06F 3/04847G06F 3/013G06F 3/011G06F 3/041G06F 3/1462G06F 1/163G06F 3/0426H04W 4/008B60C 11/24B60C 19/00G01S 7/03G01S 7/412G01S 13/887G01S 13/89G01S 13/88H01L 27/14609H01L 27/14649G08B 21/18G06K 19/07G02B 27/017
Patent Drawings (15 sheets)
Description
PRIORITY APPLICATION
[0001] This application claims priority under 35 U.S.C. §119(e) to U.S. Provisional Patent Application No. 62/007,324, entitled “Radar-Based Gesture-Recognition through a Wearable Device” and filed on Jun. 3, 2014, the disclosure of which is incorporated in its entirety by reference herein.
BACKGROUND
[0002] Wearable computing devices continue to increase in popularity, as these devices are small and light, easy to wear and keep track of, and often have substantial computing capabilities. Wearable computing devices, however, generally have small or difficult-to-use input interfaces. A computing ring or bracelet, for example, may use a very small touch screen through which to receive user input. Not only is it difficult for many user to see what to select, physically selecting the desired portion of the small touch screen can also be challenging. Other wearable computing devices, such as computing spectacles, may use small integrated buttons. Small integrated buttons offer few choices and may require users to remember functions associated with the buttons, resulting in a poor user experience.
[0003] To address these input limitations, users may augment their wearable computing devices with relatively large peripheral inputs interfaces, such as touch displays. This solution, however, adds another device, which increases cost, size, weight, and complexity for the user, which in turn defeats many of the reasons for which users desire wearable computing devices.
SUMMARY
[0004] This document describes techniques and devices for radar-based gesture-recognition through a wearable device. The techniques enable an easy-to-use input interface through this wearable radar device, in contrast to small or difficult-to-use input interfaces common to wearable computing devices. Further, these techniques are not limited to interfacing with wearable computing devices, but may aid users in controlling various non-wearable devices, such as to control volume on a stereo, pause a movie playing on a television, or select a webpage on a desktop computer.
[0005] This summary is provided to introduce simplified concepts concerning a radar-based gesture-recognition through a wearable device, 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
[0006] Embodiments of techniques and devices for 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:
[0007] FIG. 1 illustrates an example environment in which radar-based gesture-recognition through a wearable device can be implemented.
[0008] FIG. 2 illustrates an example wearable radar-based gesture-recognition system and wearable computing device.
[0009] FIG. 3 illustrates an example 3D volume radar field emitted by the wearable radar-based gesture-recognition system of FIG. 2 .
[0010] FIG. 4 illustrates an example surface radar field emitted by the wearable radar-based gesture-recognition system of FIG. 2 .
[0011] FIG. 5 illustrates another example surface radar field emitted by the wearable radar-based gesture-recognition system of FIG. 2 .
[0012] FIG. 6 illustrates a third example surface radar field emitted by the wearable radar-based gesture-recognition system of FIG. 2 .
[0013] FIG. 7 illustrates an example planar radar field emitted by the wearable radar-based gesture-recognition system of FIG. 2 .
[0014] FIG. 8 illustrates a first interaction with an example dual-planar radar field emitted by the wearable radar-based gesture-recognition system of FIG. 2 .
[0015] FIG. 9 illustrates a second interaction with the example dual-planar radar field of FIG. 8 .
[0016] FIG. 10 illustrates an example radar field conforming to a shirt-sleeve collar emitted by the wearable radar-based gesture-recognition system of FIG. 2 .
[0017] FIG. 11 illustrates an example remote computing device.
[0018] FIG. 12 illustrates example methods enabling use of a radar-based gesture-recognition through a wearable device.
[0019] FIG. 13 illustrates methods enabling use of a radar-based gesture-recognition through a wearable device, including through particular controls for an application.
[0020] FIG. 14 illustrates an example device embodying, or in which techniques may be implemented that enable use of, a radar-based gesture-recognition through a wearable device.
DETAILED DESCRIPTION
[0021] Overview
[0022] This document describes techniques using, and devices embodying, radar-based gesture-recognition. These techniques and devices can enable a great breadth of gestures and uses for those gestures through a wearable radar system. When the wearable radar system is part of a wearable computing device, for example, radar-based gesture-recognition enables users to provide input through a surface larger than a bracelet or ring, such as to tap the top of the user's left hand with the user's right finger to input a selection. Here the larger surface is the top of the user's left hand on which a localized radar field is overlaid. The wearable radar system may instead be used to control and interact with other computing devices, such as to receive simple or highly complex gestures without a user having to touch a remote touch screen, make large body movements for a game controller, or walk to a sound system receiver to adjust a volume knob or button.
[0023] These are but two examples of how techniques and/or devices enabling use of radar-based gesture-recognition through a wearable device can be performed. This document now turns to an example environment, after which example radar-based gesture-recognition systems, example methods, and an example computing system are described.
Example Environment
[0024] FIG. 1 is an illustration of an example environment 100 in which techniques using, and an apparatus including, a radar-based gesture-recognition system may be embodied. Environment 100 includes a wearable computing device 102, wearable radar-based gesture-recognition systems 104, a network 106, and remote computing devices 108. Environment 100 includes two example devices and manners for using wearable radar-based gesture-recognition system 104, the first is shown at 104-1, in which the wearable radar-based gesture-recognition system is integral with wearable computing device 102, and the second is shown at 104-2, in which the wearable radar-based gesture-recognition system is independent of wearable computing device 102. These wearable radar-based gesture-recognition systems 104-1 and 104-2 are described generally below, after which they are illustrated in detail.
[0025] Wearable computing device 102 includes wearable radar-based gesture-recognition system 104-1, and in this case these devices work together to improve user interaction with wearable computing device 102. Assume, for example, that wearable computing device 102 includes a small touch screen 110 through which display and user interaction are performed. This small touch screen 110 can present some challenges to users, as the size for selecting inputs, and therefore generally the accuracy needed by users, can make interaction difficult and time-consuming. Consider, however, wearable radar-based gesture-recognition system 104-1, which provides a localized radar field 112 overlaying a top of a user's hand 114. As is readily apparent, an area through which a user may make selections is substantially increased over that of small touch screen 110.
[0026] Wearable radar-based gesture-recognition system 104-2 is shown independent of wearable computing device 102. Assume here that wearable radar-based gesture-recognition system 104-2 interacts with remote computing devices 108 through network 106 and by transmitting input responsive to recognizing gestures, here a thumb-and-middle-finger gesture 116 is shown interacting with localized radar field 118. Gestures can be mapped to various remote computing devices 108 and their applications, thereby enabling control of many devices and applications. Many complex and unique gestures can be recognized by wearable radar-based gesture-recognition systems 104, thereby permitting precise and/or single-gesture control, even for multiple applications. Wearable radar-based gesture-recognition systems 104, whether integrated with a computing device, having computing capabilities, or having few computing abilities, can each be used to interact with remote computing devices 108.
[0027] Network 106 includes one or more of many types of wireless or partly wireless communication networks, such as 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 so forth.
[0028] Remote computing devices 108 are illustrated with various non-limiting example devices: server 108-1, smartphone 108-2, laptop 108-3, computing spectacles 108-4, television 108-5, camera 108-6, tablet 108-7, and desktop 108-8, though other devices may also be used, such as home automation and control systems, sound or entertainment systems, home appliances, security systems, netbooks, and e-readers. Note that remote computing device 108 can be wearable, non-wearable but mobile, or relatively immobile (e.g., desktops and servers).
[0029] In more detail, consider FIG. 2 , which illustrates wearable radar-based gesture-recognition system 104 both as part, and independent, of wearable computing device 102. Note also that wearable radar-based gesture-recognition system 104 can be used with, or embedded within, many different garments, accessories, and computing devices, such as the example remote computing devices 108 noted above, jackets (e.g., with a localized radar field on a sleeve or sleeve collar), hats, books, computing rings, spectacles, and so forth. Further, the localized radar field can be invisible and penetrate some materials, such as textiles, thereby further expanding how the wearable radar-based gesture-recognition system 104 can be used and embodied. While examples shown herein generally show one wearable radar-based gesture-recognition system 104 per device, multiples can be used, thereby increasing a number and complexity of gestures, as well as accuracy and robust recognition. Wearable computing device 102 includes one or more computer processors 202 and computer-readable media 204, which includes 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 gesture manager 206 (described below).
[0030] Computing device 102 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 (e.g., through network 106 of FIG. 1 ). Wearable computing device 102 includes a display 210, which can be touch-sensitive, though this is not required.
[0031] Wearable radar-based gesture-recognition system 104, as noted above, is configured to sense gestures. To enable this, wearable radar-based gesture-recognition system 104 includes a microwave radio element 212, an antenna element 214, and a signal processor 216.
[0032] Generally, microwave radio element 212 is configured to provide a localized radar field. This localized radar field is generally small, such as less than one half of one meter from the microwave radio element. Microwave radio element 212 can be configured to emit 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 within the localized radar field.
[0033] Antenna element 214 is configured to sense interactions in the localized radar field, and signal processor 216 is configured to process the sensed interactions in the localized 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 field is a surface, plane, or volume.
[0034] The field provided by microwave radio element 212 can be a three-dimensional (3D) volume (e.g., hemisphere, cube, or cylinder), a plane, or a surface applied to human tissue or non-human object. In the case of a 3D volume (or some embodiments of a field, plane, or surface), antenna element 214 is configured to sense interactions in the 3D volume of multiple targets (e.g., fingers, one moving finger, or hand elements such as knuckles or a palm), and signal processor 216 is configured to process the sensed interactions in the 3D volume sufficient to provide gesture data usable to determine gestures in three dimensions.
[0035] An example of a 3D volume is illustrated in FIG. 3 , which shows 3D volume radar field 302 emitted by wearable radar-based gesture-recognition system 104-1 of wearable computing device 102. With 3D volume radar field 302, a user may perform complex or simple gestures with a right hand or device (e.g., a stylus) that interrupts the volume. 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 on a web-based radio application, a next song on a compact disk playing on a stereo, or a next page or image in a file or album on a computer display or digital picture frame.
[0036] The localized radar field can also include a surface applied to human tissue or non-human object. In this case, antenna element 214 is configured to sense an interaction in the surface and signal processor 216 is configured to process the sensed interaction in the surface sufficient to provide gesture data usable to determine a gesture.
[0037] Example surfaces are illustrated in FIG. 1 , at localized radar field 112, and in FIGS. 4, 5, and 6 . FIG. 4 illustrates surface radar field 402 emitted by wearable radar-based gesture-recognition system 104-2 of FIG. 1 . With surface radar field 402, a user's hand (right hand 404) may interact to perform gestures, such as to tap on the user's other hand (left hand 406), thereby interrupting surface radar field 402. Example gestures include single and multi-finger swipe, spread, squeeze, non-linear movements, and so forth. Similarly, FIGS. 5 and 6 illustrates surface radar fields 502 and 602, respectively, emitted by wearable radar-based gesture-recognition system 104-1 of FIG. 1 (obscured by right hand 504 or left hand 604) in conjunction with wearable computing device 102. With surface radar field 502 or 602, a same hand as a hand on which wearable radar-based gesture-recognition system 104-1 resides (right hand 504 or left hand 604) may interact with to perform gestures on curved object 506 (here a can) or a flat object (on which surface radar field 602 of FIG. 6 is applied, such as a table surface, a wall, etc.), thereby interrupting surface radar field 502 or 602.
[0038] The localized radar field can also include one or more planes through which a user may interact. In this case, antenna element 214 is configured to sense an interaction in the planes and signal processor 216 is configured to process the sensed interaction in the surface sufficient to provide gesture data usable to determine a gesture.
[0039] Example planes are illustrated in FIG. 1 , at localized radar field 118, and in FIGS. 7, 8, and 9 . FIG. 7 illustrates planar radar field 702 emitted by wearable radar-based gesture-recognition system 104-2 of FIG. 1 . With planar radar field 702, a user's hand (left hand 704) may interact with the plane by performing gestures, such as to tap through the plane, thereby interrupting planar radar field 702, or through many of the other gestures contemplated herein, such as an up-and-down first movement to mean “Yes”. Other highly complex and simple gestures can used, including those common to touch-sensitive displays, but also many more because a gesture can continue through the plane, which is not permitted with touch-sensitive displays. For example, a gesture where two fingers are placed in the plane and the clutched back like a squeezing movement, can be interpreted as a new gesture relative to a two-finger tap or swipe.
[0040] FIGS. 8 and 9 illustrate interactions with example dual-planar radar fields 802 and 804, both emitted by one or more of wearable radar-based gesture-recognition system 104-1 (obscured in FIG. 8 ) or 104-2 (obscured in FIG. 9 ) of FIG. 1 . FIG. 8 illustrates a user's right hand 806 interacting with one of the dual-planar radar fields, here field 802, through which the user may perform various gestures. FIG. 9 illustrates another interaction, here with both of dual-planar radar fields 802 and 804, with squeezing-and-moving action 902 performed by right hand 904. This is but one of many of the contemplated, complex gestures that are not permitted with a touch-sensitive display.
[0041] By way of a last illustrated example of localized radar fields, consider FIG. 10 , which illustrates an example radar field 1002 conforming to a shirt-sleeve collar 1004 emitted by wearable radar-based gesture-recognition system 104 (obscured) of FIG. 1 . As noted herein, the localized radar field can be emitted or sensed to be preferentially tailored to fabric or human tissue. In this case, shirt-sleeve collar 1004 can be a material affecting radar field 1002 or simply be any normal clothing material. Thus, shirt-sleeve collar 1004 can be similar to curved object 506 of FIG. 5 (affecting the radar field) or of localized radar fields shown in FIG. 3 (volume) or FIG. 4, 7, 8 , or 9 (less or not affecting the radar field).
[0042] In addition to these example localized radar fields, other are also contemplated, such as volumetric fan visually similar to plane 702 of FIG. 7 , or multiple planes or surfaces to better enable multi-hand gestures. Thus, two or more planes provided by microwave radio element 212 or two or more surfaces (e.g., to both user's hands, even from a single wearable radar-based gesture-recognition system 104), thereby allowing highly complex multi-hand gestures. These multi-hand gestures number in the many hundreds or even thousands for even one of the many sign languages currently in use.
[0043] Returning to FIG. 2 , wearable radar-based gesture-recognition system 104 also includes a transmitting device configured to transmit gesture data to a remote device, though this may not be used when wearable radar-based gesture-recognition system 104 is integrated with wearable computing device 102. When included, gesture data can be provided in a format usable by remote computing device 108 sufficient for remote computing device 108 to determine the gesture in those cases where the gesture is not determined by wearable radar-based gesture-recognition system 104 or wearable computing device 102.
[0044] 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 a 3 GHz to 100 GHz range, to provide the localized 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 wearable radar-based gesture-recognition system 104, to have a relatively fast update rate, which can aid in resolution of the interactions.
[0045] By selecting particular frequencies, wearable radar-based gesture-recognition system 104 can operate to substantially penetrate clothing while not substantially penetrating human tissue. Further, antenna element 214 or signal processor 216 can be configured to differentiate between interactions in the localized radar field caused by clothing from those interactions in the localized radar field caused by human tissue. Thus, a wearer of wearable radar-based gesture-recognition system 104 may have a jacket or shirt covering microwave radio element 212 (or even embodying microwave radio element 212) and a glove covering one or more hands (e.g., right hand 404 making a gesture and left hand 406 over which the field is overlaid) but wearable radar-based gesture-recognition system 104 remains functional.
[0046] Wearable radar-based gesture-recognition system 104 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 remote device 108, and causing transceiver 218 to transmit the control input to the remote device effective to enable control of the application. This is but one of the ways in which the above-mentioned control through wearable radar-based gesture-recognition system 104 can be enabled. Operations of system manager 224 are provided in greater detail as part of methods 1200 and 1300 below.
[0047] Returning to FIG. 1 , consider remote computing device 108, which is illustrated in detail in FIG. 11 . Remote computing device 108 includes one or more computer processors 1102 and computer-readable storage media (storage media) 1104. Storage media 1104 includes applications 1106 and/or an operating system (not shown) embodied as computer-readable instructions executable by computer processors 1102 to provide, in some cases, functionalities described herein. Storage media 1104 also includes remote gesture manager 1108 (described below).
[0048] Remote computing device 108 may also include a display 1110 and network interfaces 1112 for communicating data over wired, wireless, or optical networks. By way of example and not limitation, network interface 1112 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.
[0049] Remote gesture manager 1108 is capable of interacting with applications 1106 and wearable radar-based gesture-recognition system 104 effective to aid, in some cases, control of applications 1106 through gestures received by wearable radar-based gesture-recognition system 104.
[0050] These and other capabilities and configurations, as well as ways in which entities of FIGS. 1-11 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. 2-10 illustrate some of many possible environments and devices capable of employing the described techniques.
Example Methods
[0051] FIGS. 12 and 13 depict methods enabling radar-based gesture-recognition through a wearable device. These methods and other methods herein are shown as sets of blocks that specify operations performed but are not necessarily limited to the order or combinations shown for performing the operations by the respective blocks. In portions of the following discussion reference may be made to environment 100 of FIG. 1 and entities detailed in FIGS. 2-11 , 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.
[0052] At 1202 a localized radar field is presented. This presentation of the localized radar field can be caused by one or more of gesture manager 206, system manager 224, signal processor 216, or remote gesture manager 1108. Thus, system manager 224 may cause microwave radio element 212 of wearable radar-based gesture-recognition system 104 to present (e.g., project or emit) one of the described localized radar fields noted above.
[0053] Methods 1200 may present, at 1204, an interface showing selectable control regions of the localized radar field or particular gestures, such as on display 210 or 1110 for wearable computing device 102 or remote computing device 108, respectively. A user may look at a display and see regions at which various regions select various inputs. Remote gesture manager 1108 may cause television 108-5, for example, to show particular gestures that, independent of particular regions, represent various selections, such as quick fan-out of thumb and fingers to mute the volume, or the noted localized radar field and in which regions of the field, such as to tap one region to pause the television and another to fast-forward the media being played.
[0054] At 1206, an interaction in the localized radar field is sensed. These interaction include the many noted above, such as a up-and-down first to represent a “Yes” selection, a two-finger tap gesture, or a two-handed gesture, such as tapping opposing index, middle, and thumbs against each other through a plane or volume to represent an “eat” entry, as is the meaning in some sign languages.
[0055] Responsive to the sensed interaction, the techniques may, at 1208, present a visual approximation of a location and/or real-time movement corresponding to the sensed interaction. This can aid a user by providing a visual feedback, such as on display 110 of FIG. 1 to show an interaction with localized radar field 112.
[0056] At 1210, a gesture is determined based on the sensed interaction in the localized radar field. The sensed interaction can be processed by signal processor 216, which may provide gesture data for later determination as to the gesture intended, such as by system manager 224, gesture manager 206, or remote gesture manager 1108, as noted herein.
[0057] At 1212, the determined gesture is passed to an application or operating system effective to cause an application or operating system to receive an input corresponding to the determined gesture. Thus, a user may make a gesture to pause playback of media on a remote device and, at 1212, the gesture is passed effective to pause the playback. In some embodiments, therefore, wearable radar-based gesture-recognition system 104 and these techniques a universal controller for televisions, computers, appliances, and so forth.
[0058] In some cases, the techniques, when applying methods 1200 to a wearable computing device having the wearable radar-based gesture-recognition system, may also aid the user by showing an object on which the localized radar field overlays, such as a user's left hand or top surface of the user's left hand. The techniques may then present a visual approximation for the object on the display. Following this, and responsive to sensing an interaction in the localized radar field, the techniques present the sensed interaction at a location in the visual approximation for the object corresponding to the sensed interaction's location at the object's surface, similar to operation 1208.
[0059] FIG. 13 depicts methods 1300 enabling radar-based gesture-recognition through a wearable device, including through particular controls for an application.
[0060] At 1302, a set of controls through which the application can be controlled is determined. Gesture manager 206 or system manager 224, for example, can interact with applications on wearable computing device 102 or remote computing devices 108 to determine controls through which a user may interaction with an application. Doing so may involve determining user interfaces through which an application is controlled, such as through inspection of the interface (e.g., visual controls), published APIs, and the like.
[0061] At 1304, the set or a subset of the controls selectable through a localized radar field are indicated. This can be through the application and the device on which the application is stored, e.g., on a laptop for a web browser, or on wearable computing device 102, such as to show a gesture usable to turn off the lights in a room.
[0062] At 1306, the localized radar field is provided. Thus, system manager 224 may cause microwave radio element 212 to present one of the various localized radar fields described herein.
[0063] At 1308, an interaction in the localized radar field is sensed, such as by antenna element 214. This is described in detail elsewhere herein.
[0064] At 1310, a control of the set or subset of the controls selected through the sensed interaction in the localized radar field is determined. This can be performed by signal processor 216 passing gesture data to various managers as noted herein.
[0065] At 1312, the determined control is passed to the application. Methods 1300 can be performed on a device remote from the radar-based gesture-recognition system, such as by remote gesture manager 1108. In this case remote gesture manager 1108 determines the set at 1302, indicates the controls on a remote display or causes the indication on display 110 or 210 of wearable computing device 102 and causes, at 1306, the localized radar field to be provided by communicating with wearable radar-based gesture-recognition system 104's transceiver 218. Remote gesture manager 1108 then receives gesture data for the interaction (which may be processed by signal processor 216), and, at 1310, determines based on the gesture data which control was selected before passing to the relevant application.
[0066] Operations of methods 1300 can be repeated, such as by determining for multiple other applications and other controls through which the multiple other applications can be controlled. Methods 1300 may then indicate various different controls to control various applications. In some cases, the techniques determine or assign unique and/or complex and three-dimensional controls to the different applications, thereby allowing a user to control numerous applications without having to select to switch control between them.
[0067] The preceding discussion describes methods relating to radar-based gesture-recognition through a wearable devices. 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. 1-11 and 14 (computing system 1400 is described in FIG. 14 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
[0068] FIG. 14 illustrates various components of example computing system 1400 that can be implemented as any type of client, server, and/or computing device as described with reference to the previous FIGS. 1-9 to implement a radar-based gesture-recognition through a wearable device. In embodiments, computing system 1400 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 1400 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.
[0069] Computing system 1400 includes communication devices 1402 that enable wired and/or wireless communication of device data 1404 (e.g., received data, data that is being received, data scheduled for broadcast, data packets of the data, etc.). Device data 1404 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 1400 can include any type of audio, video, and/or image data. Computing system 1400 includes one or more data inputs 1406 via which any type of data, media content, and/or inputs can be received, such as human utterances, interactions with a localized 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.
[0070] Computing system 1400 also includes communication interfaces 1408, 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 1408 provide a connection and/or communication links between computing system 1400 and a communication network by which other electronic, computing, and communication devices communicate data with computing system 1400.
[0071] Computing system 1400 includes one or more processors 1410 (e.g., any of microprocessors, controllers, and the like), which process various computer-executable instructions to control the operation of computing system 1400 and to enable techniques for, or in which can be embodied, a radar-based gesture-recognition through a wearable device. Alternatively or in addition, computing system 1400 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 1412. Although not shown, computing system 1400 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.
[0072] Computing system 1400 also includes computer-readable media 1414, 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 1400 can also include a mass storage media device 1416.
[0073] Computer-readable media 1414 provides data storage mechanisms to store device data 1404, as well as various device applications 1418 and any other types of information and/or data related to operational aspects of computing system 1400. For example, an operating system 1420 can be maintained as a computer application with computer-readable media 1414 and executed on processors 1410. Device applications 1418 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.
[0074] Device applications 1418 also include any system components, engines, or managers to implement radar-based gesture-recognition through a wearable device. In this example, device applications 1418 include gesture manager 206 and system manager 224.
CONCLUSION
[0075] Although embodiments of techniques using, and apparatuses including, radar-based gesture-recognition through a wearable device 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 of radar-based gesture-recognition through a wearable device.
Claims
Certificate of Correction present
The claims shown below may not include correction changes. Use the corrected PDF for authoritative text.
What is claimed is:
1. A radar-based gesture-recognition system comprising:
a microwave radio element in a wearable device configured to provide a planar localized radar field adjacent a user appendage on which the wearable device resides, the planar localized radar field corresponding to a planar surface through which a gesture interaction is sensed;
an antenna element configured to sense the gesture interaction through the planar localized radar field, the gesture interaction having multiple targets on the planar surface in the planar localized radar field, the gesture interaction passing through the planar localized radar field; and
a signal processor configured to process the sensed gesture interaction having the multiple targets in the planar localized radar field sufficient to provide gesture data usable to determine a two-dimensional gesture or a three-dimensional gesture from the sensed gesture interaction having the multiple targets.
2. The radar-based gesture-recognition system as recited in claim 1, wherein the microwave radio element is configured to emit microwave radiation in a 3 GHz to 300 GHz range and the antenna element is configured to sense the gesture interaction of the emitted microwave radiation to track locations of two or more of the multiple targets to a resolution of approximately two to 25 millimeters, the resolution of the locations based on the 3 GHz to 300 GHz range of the emitted microwave radiation.
3. The radar-based gesture-recognition system as recited in claim 1, wherein the microwave radio element is configured to emit microwave radiation capable of substantially penetrating clothing and not substantially penetrating human tissue, and the antenna element or signal processor is configured to differentiate between gesture interactions in the planar localized radar field caused by clothing from gesture interactions in the planar localized radar field caused by human tissue.
4. The radar-based gesture-recognition system as recited in claim 1, wherein the microwave radio element is configured to emit continuously modulated radiation, ultra-wideband radiation, or sub-millimeter-frequency radiation.
5. The radar-based gesture-recognition system as recited in claim 1, wherein the microwave radio element is configured to form emitted radiation in beams, the beams enabling the antenna element and the signal processor to determine which of the beams are interrupted.
6. The radar-based gesture-recognition system as recited in claim 1, wherein the gesture interaction interrupts the planar localized radar field at locations corresponding to the multiple targets.
7. The radar-based gesture-recognition system as recited in claim 1, wherein the planar localized radar field comprises a radar plane above, below, or multiple planes above or below an object.
8. The radar-based gesture-recognition system as recited in claim 7, wherein the object comprises a human hand or clothing.
9. The radar-based gesture-recognition system as recited in claim 1, further comprising:
one or more computer processors; and
one or more computer-readable storage media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising:
determining, based on the provided gesture data from the signal processor, the two-dimensional gesture or the three-dimensional gesture;
mapping the determined two-dimensional gesture or the determined three-dimensional gesture to a pre-configured control gesture associated with a control input for an application associated with a remote device; and
causing the transmitting device to transmit the control input to the remote device effective to enable control of the application.
10. The radar-based gesture-recognition system as recited in claim 9, wherein the pre-configured control gesture is one of multiple complex or single-handed gestures.
11. A computer-implemented method comprising:
determining, for an application on a wearable computing device, a set of controls through which the application can be controlled;
indicating the set or a subset of the controls selectable through a planar localized radar field;
causing a radar-based gesture-recognition system to present the planar localized radar field adjacent a user appendage on which the radar-based gesture recognition system resides, the planar localized radar field corresponding to a planar surface through which a two-dimensional or three-dimensional gesture interaction is sensed;
causing the radar-based gesture-recognition system to sense the gesture interaction through the planar localized radar field, the gesture interaction having multiple targets on the planar surface in the planar localized radar field, the gesture interaction passing through the planar localized radar field;
determining a control of the set or subset of the controls selected through the sensed gesture interaction in the planar localized radar field; and
passing the determined control to the application.
12. The computer-implemented method as described in claim 11, wherein the computer-implemented method is performed on the wearable computing device, the wearable computing device being separate from the radar-based gesture-recognition system, the indicating the set or the subset of the controls is performed on a display associated with the wearable computing device, and the method further comprises, prior to determining the selected control, receiving gesture data from the radar-based gesture-recognition system.
13. A wearable computing device comprising:
a radar-based gesture-recognition system configured to sense gestures;
one or more computer processors; and
one or more computer-readable storage media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising:
causing the radar-based gesture-recognition system to provide a planar localized radar field adjacent a user appendage on which the wearable computing device resides, the planar localized radar field corresponding to a planar surface through which an interaction is sensed;
causing the radar-based gesture-recognition system to sense the interaction through the planar localized radar field, the interaction having multiple targets on the planar surface in the planar localized radar field, the interaction passing through the planar localized radar field;
determining a two-dimensional gesture or a three-dimensional gesture based on the sensed interaction through the planar localized radar field; and
passing the determined gesture to an application or operating system of the wearable computing device effective to cause the application or operating system to receive an input corresponding to the determined gesture.
14. The wearable computing device as recited in claim 13, wherein the wearable computing device further comprises a display and the operations further comprise causing the display to present a visual approximation, in real time, of a movement and locations corresponding to the sensed interaction.
15. The wearable computing device as recited in claim 13, wherein the wearable computing device further comprises a display and the operations further comprise:
overlaying the planar localized radar field on an object;
determining the object on which the planar localized radar field overlays;
presenting a visual approximation of the object on the display; and
responsive to sensing the interaction in the planar localized radar field, presenting the sensed interaction at a location in the visual approximation for the object corresponding to the sensed interaction's location at the object.
16. The wearable computing device as recited in claim 13, wherein the wearable computing device further comprises a display and the operations further comprise causing the display to present a visual approximation of a location corresponding to the sensed interaction.
17. The wearable computing device as recited in claim 16, wherein the display presents an interface showing selectable control regions of the planar localized radar field and the visual approximation of the location corresponding to the sensed interaction indicates selection of a selectable control region responsive to sensing the interaction in the planar localized radar field.
18. The wearable computing device as recited in claim 13, wherein the operations further comprise:
determining, based on a user interface associated with the application, a set of controls for the user interface through which the user interface is capable of receiving input;
indicating, to the user interface, the set of controls or a subset of the set of controls for selection through the radar-based gesture-recognition system effective to enable the user interface to highlight or indicate the set of controls or the subset of the set of controls for selection through the radar-based gesture-recognition system; and
responsive to the sensed interaction selecting one of the set or subset of controls, causing the user interface associated with the application to indicate selection of the selected control.
19. The wearable computing device as recited in claim 18, wherein the user interface is displayed on a remote device, the remote device being remote from the wearable computing device.
20. The wearable computing device as recited in claim 18, wherein the user interface is displayed on a display associated with the wearable computing device.
Patent Citations (190)
| Patent | Date | Inventor | Cited By |
|---|---|---|---|
| US3610874(A) | 1971-10-01 | Gagliano | Applicant |
| US3953706(A) | 1976-04-01 | Harris et al. | Applicant |
| US4700044(A) | 1987-10-01 | Hokanson et al. | Applicant |
| US5298715(A) | 1994-03-01 | Chalco et al. | Applicant |
| US5341979(A) | 1994-08-01 | Gupta | Applicant |
| US5798798(A) | 1998-08-01 | Rector et al. | Applicant |
| US6032450(A) | 2000-03-01 | Blum | Applicant |
| US6080690(A) | 2000-06-01 | Lebby et al. | Applicant |
| US6210771(B1) | 2001-04-01 | Post et al. | Applicant |
| US6313825(B1) | 2001-11-01 | Gilbert | Applicant |
| US6340979(B1) | 2002-01-01 | Beaton et al. | Applicant |
| US6386757(B1) | 2002-05-01 | Konno | Applicant |
| US6492980(B2) | 2002-12-01 | Sandbach | Applicant |
| US6493933(B1) | 2002-12-01 | Post et al. | Applicant |
| US6513970(B1) | 2003-02-01 | Tabata et al. | Applicant |
| US6543668(B1) | 2003-04-01 | Fujii et al. | Applicant |
| US7299964(B2) | 2007-11-01 | Jayaraman et al. | Applicant |
| US7317416(B2) | 2008-01-01 | Flom et al. | Applicant |
| US7365031(B2) | 2008-04-01 | Swallow et al. | Applicant |
| US7421061(B2) | 2008-09-01 | Boese et al. | Applicant |
| US7578195(B2) | 2009-08-01 | DeAngelis et al. | Applicant |
| US7677729(B2) | 2010-03-01 | Vilser et al. | Applicant |
| US7691067(B2) | 2010-04-01 | Westbrook et al. | Applicant |
| US7698154(B2) | 2010-04-01 | Marchosky | Applicant |
| US8062220(B2) | 2011-11-01 | Kurtz et al. | Applicant |
| US8169404(B1) | 2012-05-01 | Boillot | Examiner |
| US8289185(B2) | 2012-10-01 | Alonso | Applicant |
| US8301232(B2) | 2012-10-01 | Albert et al. | Applicant |
| US8334226(B2) | 2012-12-01 | Nhan et al. | Applicant |
| US8475367(B1) | 2013-07-01 | Yuen et al. | Applicant |
| US8560972(B2) | 2013-10-01 | Wilson | Applicant |
| US8700137(B2) | 2014-04-01 | Albert | Applicant |
| US8758020(B2) | 2014-06-01 | Burdea et al. | Applicant |
| US8759713(B2) | 2014-06-01 | Sheats | Applicant |
| US8764651(B2) | 2014-07-01 | Tran | Applicant |
| US8790257(B2) | 2014-07-01 | Libbus et al. | Applicant |
| US9125456(B2) | 2015-09-01 | Chow | Applicant |
| US9141194(B1) | 2015-09-01 | Keyes et al. | Applicant |
| US2002/0170897(A1) | 2002-11-01 | Hall | Applicant |
| US2003/0100228(A1) | 2003-05-01 | Bungo et al. | Applicant |
| US2003/0119391(A1) | 2003-06-01 | Swallow et al. | Applicant |
| US2004/0009729(A1) | 2004-01-01 | Hill et al. | Applicant |
| US2005/0069695(A1) | 2005-03-01 | Jung et al. | Applicant |
| US2006/0035554(A1) | 2006-02-01 | Glaser et al. | Applicant |
| US2006/0040739(A1) | 2006-02-01 | Wells | Applicant |
| US2006/0166620(A1) | 2006-07-01 | Sorensen | Applicant |
| US2006/0258205(A1) | 2006-11-01 | Locher et al. | Applicant |
| US2007/0118043(A1) | 2007-05-01 | Oliver et al. | Applicant |
| US2007/0161921(A1) | 2007-07-01 | Rausch | Applicant |
| US2007/0176821(A1) | 2007-08-01 | Flom | Examiner |
| US2007/0197878(A1) | 2007-08-01 | Shklarski | Applicant |
| US2007/0210074(A1) | 2007-09-01 | Maurer et al. | Applicant |
| US2008/0065291(A1) | 2008-03-01 | Breed | Applicant |
| US2008/0136775(A1) | 2008-06-01 | Conant | Examiner |
| US2008/0233822(A1) | 2008-09-01 | Swallow et al. | Applicant |
| US2008/0282665(A1) | 2008-11-01 | Speleers | Applicant |
| US2008/0291158(A1) | 2008-11-01 | Park | Examiner |
| US2009/0033585(A1) | 2009-02-01 | Lang | Applicant |
| US2009/0053950(A1) | 2009-02-01 | Surve | Applicant |
| US2009/0056300(A1) | 2009-03-01 | Chung et al. | Applicant |
| US2009/0115617(A1) | 2009-05-01 | Sano et al. | Applicant |
| US2009/0270690(A1) | 2009-10-01 | Roos et al. | Applicant |
| US2009/0288762(A1) | 2009-11-01 | Wolfel | Applicant |
| US2010/0065320(A1) | 2010-03-01 | Urano | Applicant |
| US2010/0071205(A1) | 2010-03-01 | Graumann et al. | Applicant |
| US2010/0094141(A1) | 2010-04-01 | Puswella | Applicant |
| US2010/0201586(A1) | 2010-08-01 | Michalk | Applicant |
| US2010/0205667(A1) | 2010-08-01 | Anderson et al. | Applicant |
| US2010/0208035(A1) | 2010-08-01 | Pinault et al. | Applicant |
| US2010/0225562(A1) | 2010-09-01 | Smith | Examiner |
| US2010/0281438(A1) | 2010-11-01 | Latta et al. | Applicant |
| US2010/0313414(A1) | 2010-12-01 | Sheats | Applicant |
| US2010/0325770(A1) | 2010-12-01 | Chung et al. | Applicant |
| US2011/0003664(A1) | 2011-01-01 | Richard | Applicant |
| US2011/0073353(A1) | 2011-03-01 | Lee et al. | Applicant |
| US2011/0093820(A1) | 2011-04-01 | Zhang et al. | Applicant |
| US2011/0181509(A1) | 2011-07-01 | Rautiainen et al. | Applicant |
| US2011/0181510(A1) | 2011-07-01 | Hakala | Examiner |
| US2011/0213218(A1) | 2011-09-01 | Weiner et al. | Applicant |
| US2011/0221666(A1) | 2011-09-01 | Newton et al. | Applicant |
| US2011/0234492(A1) | 2011-09-01 | Ajmera et al. | Applicant |
| US2011/0303341(A1) | 2011-12-01 | Meiss et al. | Applicant |
| US2011/0318985(A1) | 2011-12-01 | McDermid | Applicant |
| US2012/0047468(A1) | 2012-02-01 | Santos et al. | Applicant |
| US2012/0068876(A1) | 2012-03-01 | Bangera et al. | Applicant |
| US2012/0092284(A1) | 2012-04-01 | Rofougaran | Examiner |
| US2012/0123232(A1) | 2012-05-01 | Najarian et al. | Applicant |
| US2012/0127082(A1) | 2012-05-01 | Kushler | Examiner |
| US2012/0144934(A1) | 2012-06-01 | Russell et al. | Applicant |
| US2012/0174736(A1) | 2012-07-01 | Wang et al. | Applicant |
| US2012/0193801(A1) | 2012-08-01 | Gross et al. | Applicant |
| US2012/0248093(A1) | 2012-10-01 | Ulrich et al. | Applicant |
| US2012/0268416(A1) | 2012-10-01 | Pirogov et al. | Applicant |
| US2012/0280900(A1) | 2012-11-01 | Wang et al. | Applicant |
| US2012/0310665(A1) | 2012-12-01 | Xu et al. | Applicant |
| US2013/0016070(A1) | 2013-01-01 | Starner | Examiner |
| US2013/0053653(A1) | 2013-02-01 | Cuddihy et al. | Applicant |
| US2013/0102217(A1) | 2013-04-01 | Jeon | Applicant |
| US2013/0132931(A1) | 2013-05-01 | Bruns et al. | Applicant |
| US2013/0150735(A1) | 2013-06-01 | Cheng | Applicant |
| US2013/0194173(A1) | 2013-08-01 | Zhu | Examiner |
| US2013/0196716(A1) | 2013-08-01 | Muhammad | Applicant |
| US2013/0278499(A1) | 2013-10-01 | Anderson | Applicant |
| US2013/0345569(A1) | 2013-12-01 | Mestha et al. | Applicant |
| US2014/0005809(A1) | 2014-01-01 | Frei et al. | Applicant |
| US2014/0073969(A1) | 2014-03-01 | Zou et al. | Applicant |
| US2014/0081100(A1) | 2014-03-01 | Muhsin et al. | Applicant |
| US2014/0121540(A1) | 2014-05-01 | Raskin | Applicant |
| US2014/0139616(A1) | 2014-05-01 | Pinter et al. | Applicant |
| US2014/0143678(A1) | 2014-05-01 | Mistry et al. | Applicant |
| US2014/0184496(A1) | 2014-07-01 | Gribetz | Examiner |
| US2014/0191939(A1) | 2014-07-01 | Penn et al. | Applicant |
| US2014/0200416(A1) | 2014-07-01 | Kashef et al. | Applicant |
| US2014/0239065(A1) | 2014-08-01 | Zhou | Examiner |
| US2014/0244277(A1) | 2014-08-01 | Krishna Rao et al. | Applicant |
| US2014/0246415(A1) | 2014-09-01 | Wittkowski | Applicant |
| US2014/0253709(A1) | 2014-09-01 | Bresch et al. | Applicant |
| US2014/0297006(A1) | 2014-10-01 | Sadhu | Applicant |
| US2014/0306936(A1) | 2014-10-01 | Dahl et al. | Applicant |
| US2014/0316261(A1) | 2014-10-01 | Lux et al. | Applicant |
| US2014/0324888(A1) | 2014-10-01 | Xie et al. | Applicant |
| US2014/0347295(A1) | 2014-11-01 | Kim | Examiner |
| US2014/0357369(A1) | 2014-12-01 | Callens et al. | Applicant |
| US2015/0002391(A1) | 2015-01-01 | Chen | Examiner |
| US2015/0009096(A1) | 2015-01-01 | Lee | Examiner |
| US2015/0029050(A1) | 2015-01-01 | Driscoll et al. | Applicant |
| US2015/0068069(A1) | 2015-03-01 | Tran | Examiner |
| US2015/0077282(A1) | 2015-03-01 | Mohamadi | Applicant |
| US2015/0085060(A1) | 2015-03-01 | Fish et al. | Applicant |
| US2015/0091858(A1) | 2015-04-01 | Rosenberg et al. | Applicant |
| US2015/0112606(A1) | 2015-04-01 | He et al. | Applicant |
| US2015/0133017(A1) | 2015-05-01 | Liao et al. | Applicant |
| US2015/0145805(A1) | 2015-05-01 | Liu | Examiner |
| US2015/0162729(A1) | 2015-06-01 | Reversat et al. | Applicant |
| US2015/0199045(A1) | 2015-07-01 | Robucci et al. | Applicant |
| US2015/0261320(A1) | 2015-09-01 | Leto | Applicant |
| US2015/0268027(A1) | 2015-09-01 | Gerdes | Examiner |
| US2015/0277569(A1) | 2015-10-01 | Sprenger et al. | Applicant |
| US2015/0332075(A1) | 2015-11-01 | Burch | Examiner |
| US2015/0375339(A1) | 2015-12-01 | Sterling et al. | Applicant |
| US2016/0018948(A1) | 2016-01-01 | Parvarandeh et al. | Applicant |
| US2016/0041617(A1) | 2016-02-01 | Poupyrev | Applicant |
| US2016/0041618(A1) | 2016-02-01 | Poupyrev | Applicant |
| US2016/0048235(A1) | 2016-02-01 | Poupyrev | Applicant |
| US2016/0048236(A1) | 2016-02-01 | Poupyrev | Applicant |
| US2016/0054792(A1) | 2016-02-01 | Poupyrev | Applicant |
| US2016/0054803(A1) | 2016-02-01 | Poupyrev | Applicant |
| US2016/0054804(A1) | 2016-02-01 | Gollakata et al. | Applicant |
| US2016/0055201(A1) | 2016-02-01 | Poupyrev et al. | Applicant |
| US2016/0098089(A1) | 2016-04-01 | Poupyrev | Applicant |
| US2016/0103500(A1) | 2016-04-01 | Hussey | Examiner |
| US2016/0106328(A1) | 2016-04-01 | Mestha et al. | Applicant |
| US2016/0145776(A1) | 2016-05-01 | Roh | Applicant |
| US2016/0249698(A1) | 2016-09-01 | Berzowska et al. | Applicant |
| US2016/0282988(A1) | 2016-09-01 | Poupyrev | Applicant |
| US2016/0283101(A1) | 2016-09-01 | Schwesig et al. | Applicant |
| US2016/0284436(A1) | 2016-09-01 | Fukuhara et al. | Applicant |
| US2016/0320852(A1) | 2016-11-01 | Poupyrev | Applicant |
| US2016/0320853(A1) | 2016-11-01 | Lien et al. | Applicant |
| US2016/0320854(A1) | 2016-11-01 | Lien et al. | Applicant |
| US2016/0345638(A1) | 2016-12-01 | Robinson et al. | Applicant |
| US2016/0349845(A1) | 2016-12-01 | Poupyrev et al. | Applicant |
| CN202887794 | 2013-04-01 | Applicant | |
| CN103355860 | 2016-01-01 | Applicant | |
| DE102011075725 | 2012-11-01 | Applicant | |
| DE102013201359 | 2014-07-01 | Applicant | |
| EP161895 | 1985-11-01 | Applicant | |
| GB2443208 | 2008-04-01 | Applicant | |
| JP2006234716 | 2006-09-01 | Applicant | |
| JP2011102457 | 2011-05-01 | Applicant | |
| WO-0127855 | 2001-04-01 | Applicant | |
| WO-0175778 | 2001-10-01 | Applicant | |
| WO-02082999 | 2002-10-01 | Applicant | |
| WO-2005033387 | 2005-04-01 | Applicant | |
| WO-2008061385 | 2008-05-01 | Applicant | |
| WO-2009032073 | 2009-03-01 | Applicant | |
| WO-2010032173 | 2010-03-01 | Applicant | |
| WO-2012026013 | 2012-03-01 | Applicant | |
| WO-2012152476 | 2012-11-01 | Applicant | |
| WO-2013082806 | 2013-06-01 | Applicant | |
| WO-2013186696 | 2013-12-01 | Applicant | |
| WO-2013191657 | 2013-12-01 | Applicant | |
| WO-2014019085 | 2014-02-01 | Applicant | |
| WO-2014116968 | 2014-07-01 | Applicant | |
| WO-2014136027 | 2014-09-01 | Applicant | |
| WO-2014138280 | 2014-09-01 | Applicant | |
| WO-2014160893 | 2014-10-01 | Applicant | |
| WO-2014165476 | 2014-10-01 | Applicant | |
| WO-2014204323 | 2014-12-01 | Applicant | |
| WO-2015022671 | 2015-02-01 | Applicant |
Non-Patent Literature (48)
- Arbabian, et al.,' “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.Applicant
- “Extended European Search Report”, EP Application No. 15170577.9, Nov. 5, 2015, 12 pages.Applicant
- 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.Applicant
- “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?ls=1&mt=8> Apr. 15, 2015, Feb. 24, 2015, 6 pages.Applicant
- “Final Office Action”, U.S. Appl. No. 14/504,038, filed Sep. 27, 2016, 23 pages.Applicant
- “Final Office Action”, U.S. Appl. No. 14/504,061, filed Mar. 9, 2016, 10 pages.Applicant
- “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.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2015/044774, Nov. 3, 2015, 12 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2016/024267, Jun. 20, 2016, 13 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2016/024273, Jun. 20, 2016, 13 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2016/032307, Aug. 25, 2016, 13 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2016/029820, Jul. 15, 2016, 14 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2016/030177, Aug. 2, 2016, 15 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2015/043963, Nov. 24, 2015, 16 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2015/050903, Feb. 19, 2016, 18 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2016/030115, Aug. 8, 2016, 18 pages.Applicant
- “International Search Report and Written Opinion”, Application No. PCT/US2015/043949, Dec. 1, 2015, 18 pages.Applicant
- “Non-Final Office Action”, U.S. Appl. No. 14/504,038, Feb. 26, 2016, 22 pages.Applicant
- “Non-Final Office Action”, U.S. Appl. No. 14/504,061, Nov. 4, 2015, 8 pages.Applicant
- “Non-Final Office Action”, U.S. Appl. No. 14/582,896, Jun. 29, 2016, 9 pages.Applicant
- “Non-Final Office Action”, U.S. Appl. No. 14/666,155, Aug. 24, 2016, 9 pages.Applicant
- “Non-Final Office Action”, U.S. Appl. No. 14/681,625, Aug. 12, 2016, 9 pages.Applicant
- “Non-Final Office Action”, U.S. Appl. No. 14/930,220, Sep. 14, 2016, 15 pages.Applicant
- “Notice of Allowance”, U.S. Appl. No. 14/504,061, Sep. 12, 2016, 7 pages.Applicant
- “Philips Vital Signs Camera”, Retrieved From: <http://www.vitalsignscamera.com/> Apr. 15, 2015, Jul. 17, 2013, 2 pages.Applicant
- “Restriction Requirement”, U.S. Appl. No. 14/666,155, Jul. 22, 2016, 5 pages.Applicant
- “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.Applicant
- 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.Applicant
- 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.Applicant
- 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.Applicant
- 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.Applicant
- 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.Applicant
- Holleis,“Evaluating Capacitive Touch Input on Clothes”, Proceedings of the 10th International Conference on Human Computer Interaction, Jan. 1, 2008, 10 pages.Applicant
- 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.Applicant
- Patel,“Applications of Electrically Conductive Yarns in Technical Textiles”, International Conference on Power System Technology (POWECON), Oct. 30, 2012, 6 pages.Applicant
- 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, Aug. 2011.Applicant
- 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%2D5BAC49A426378C02%5F199381%2Foe%2D18%2D10%2D10762%2Ep, May 7, 2010, 13 pages.Applicant
- 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.Applicant
- 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.Applicant
- Wijesiriwardana,“Capacitive Fibre-Meshed Transducer for Touch & Proximity Sensing Applications”, IEEE Sensors Journal, IEEE Service Center, Oct. 1, 2005, 5 pages.Applicant
- 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.Applicant
- Zhang,“Study of the Structural Design and Capacitance Characteristics of Fabric Sensor”, Advanced Materials Research (vols. 194-196), Feb. 21, 2011, 8 pages.Applicant
- “Corrected Notice of Allowance”, U.S. Appl. No. 14/504,061, Dec. 27, 2016, 2 pages.Applicant
- “Corrected Notice of Allowance”, U.S. Appl. No. 14/582,896, Dec. 19, 2016, 2 pages.Applicant
- “Non-Final Office Action”, U.S. Appl. No. 14/518,863, Oct. 14, 2016, 16 pages.Applicant
- “Notice of Allowance”, U.S. Appl. No. 14/582,896, Nov. 7, 2016, 5 pages.Applicant
- “Pre-Interview Communication”, U.S. Appl. No. 14/513,875, Oct. 21, 2016, 3 pages.Applicant
- Pu,“Gesture Recognition Using Wireless Signals”, Oct. 2014, pp. 15-18.Applicant