University of Washington

Belkin International, Inc.

Google Inc.

Georgia Tech Research Corporation

Phyn LLC

Microsoft Technology Licensing, LLC

Transform Sr Brands LLC

Disney Enterprises, Inc.

Sears Brands, LLC

Other

Microsoft Technology Licnesing, LLC

Shwetak N Patel

Matthew Stephen Reynolds

Sidhant Gupta

Gregory D Abowd

Eric C Larson

Thomas M Robertson

Dongeek Shin

Karthik Yogeeswaran

Salil P Banerjee

Gabriel Adam Cohn

Desney S Tan

Nicolas Villar

T Scott Saponas

Daniel Morris

James Anthony Fogarty

Miroslav Enev

Jon E Froehlich

Erich Peter Stuntebeck

Ivan Poupyrev

Yael Gregory Maguire

Michael D Dixon

Shahram Izadi

Aanand Esterberg

Dan Morris

Greg R Smith

Mayank Goel

Raul I Ramos-Garcia

Yoky Matsuoka

Gregory Ray Smith

Brandon Charles Barbello

Sofien Bouaziz

Alanson P Sample

Francis Michael Kelly

Scott E Hudson

Randall Bly

Josh Fromm

Patrick William Vilbrandt

Sailaja Malladi

Ronald E Paulsen

Hanchuan Li

Anupam Pathak

Anthony Law

Eric Brockmeyer

Lynn B McGrath

Alex T Mariakakis

Jacob Baudin

Orestis Vardoulis

Elizabeth Carter

Timothy B Campbell

Ryan Yong Kim

William James Biederman

Todd Whitehurst

Sumit Basu

Shyamnath Gollakota

Frank Kelly

Rizwan Ahmed Chaudhry

Jonathan Bernard Lester

Steven L Goldberg

Steven Benjamin Goldberg

David Kim

Chetan Pitambar Bhole

Edward Wang

William Greene

David Charles Kale

Ke-Yu Chen

Lilian De Greef

Charles Gillen-O'Neel

Ameet V Joshi

Khai N Truong

Daniel S Morris

Jacob O Wobbrock

Babak Abbasi Bastami

Stacy Tantum

Salil Banerjee

Vaibhav Darbari

Manoj Gulati

Brady C Houston

Leah Findlater

Tien-Jui Lee

Shih-Yen Liu

James A Taylor

James W Stout

Qifan Pu

Scott T Saponas

David C Kale

Various arrangements for performing ballistocardiography using a mobile device are presented. A radar integrated circuit of a mobile device may emit frequency-modulated continuous-wave (FMCW) radar. Reflected radio waves based on the FMCW radar being reflected off objects may be received and used to create a raw radar waterfall. The raw radar waterfall may be analyzed to create a ballistocardiography waveform. Data based on the ballistocardiography waveform may be output, such as to a machine-learning application installed on the mobile device.

Heart beat measurements using a mobile device

In some embodiments, techniques for using machine learning to enable visible light pupilometry are provided. In some embodiments, a smartphone may be used to create a visible light video recording of a pupillary light reflex (PLR). A machine learning model may be used to detect a size of a pupil in the video recording over time, and the size over time may be presented to a clinician. In some embodiments, a system that includes a smartphone and a box that holds the smartphone in a predetermined relationship to a subject's face is provided. In some embodiments, a sequential convolutional neural network architecture is used. In some embodiments, a fully convolutional neural network architecture is used.

Smartphone-based digital pupillometer

Various arrangements for performing radar-based measurement of vital signs. Waveform data may be received then filtered of data indicative of static objects to obtain motion-indicative waveform data. The motion-indicative waveform data may be analyzed to determine one or more frequencies of movement present within the motion-indicative waveform data. A spectral analysis may be performed on the motion-indicative waveform data to determine a spectral-analysis state of a monitored region. The spectral-analysis state of the monitored region may be determined to match a predefined spectral-analysis state during which vital sign monitoring is permitted. One or more vital signs of a monitored user present within the monitored region may be determined and output based on analyzing the motion-indicative waveform data.

Sleep tracking and vital sign monitoring using low power radio waves

Techniques of identifying gestures include detecting and classifying inner-wrist muscle motions at a user's wrist using micron-resolution radar sensors. For example, a user of an AR system may wear a band around their wrist. When the user makes a gesture to manipulate a virtual object in the AR system as seen in a head-mounted display (HMD), muscles and ligaments in the user's wrist make small movements on the order of 1-3 mm. The band contains a small radar device that has a transmitter and a number of receivers (e.g., three) of electromagnetic (EM) radiation on a chip (e.g., a Soli chip. This radiation reflects off the wrist muscles and ligaments and is received by the receivers on the chip in the band. The received reflected signal, or signal samples, are then sent to processing circuitry for classification to identify the wrist movement as a gesture.

Hand gesture recognition based on detected wrist muscular movements

A motion sensor assembly may include a cover plate configured to be mounted to an electrical box. The cover plate may include a front surface configured to face away from the electrical box and a rear surface opposite the front surface. The cover plate may further include an aperture configured to receive a toggle or rocker type switch. A motion sensor may be coupled to the cover plate. A power source and processor may be operably coupled to the motion sensor. Furthermore, the processor may be operably coupled to a communication device.

Sensors for detecting presence, occupancy, and/or motion and related systems and methods

Computing systems and methods are provided for detecting skin conditions of humans. A computing device can authenticate a user via a fingerprint scan of a first skin region of the user using a three-dimensional (3D) sonic sensor. The device can generate a three-dimensional (3D) volumetric sonic measurement of a second skin region of the user based at least in part on one or more sonic pulses of the three-dimensional sonic sensor. The device can input data indicative of the 3D volumetric sonic measurement into one or more machine-learning models, generate one or more skin cancer condition identifications associated with the second skin region of the user based on one or more outputs of the one or more machine-learned models, and provide one or more outputs including the one or more skin cancer condition identifications associated with the second skin region of the user.

Early skin condition diagnostics using sonic sensors

Various arrangements for performing fall detection are presented. A smart-home device (), comprising a monolithic radar integrated circuit (), may transmit radar waves. Based on reflected radar waves, raw waveform data may be created. The raw waveform data may be processed to determine that a fall by a person () has occurred. Speech may then be output announcing that the fall has been detected via the speaker () of the smart home device ().

Privacy-preserving radar-based fall monitoring

A system including a sensing device configured to (i) measure pressure of water in cold and hot water lines proximate to a fixture of a water system of a structure, and (ii) generate pressure measurement data representing the pressure of the water. The system also includes one or more processors. The system additionally includes one or more non-transitory computer readable media storing machine-executable instructions configured, when executed on the one or more processors, to perform detecting a non-cyclical pressure event corresponding to a water leak in the water system of the structure during a first time period based on an analysis of information comprising the pressure measurement data. Other embodiments are described.

Water leak detection using pressure sensing

A method for determining one or more vital signs of a person includes recording video images of a scene with an egocentric camera coupled to the person's body, detecting and magnifying image frame-to-image frame movements in the video images of the scene, representing the magnified image frame-to-image frame movements in the video images of the scene by a one-dimensional (1D) amplitude-versus-time series, and transforming the 1D amplitude-versus-time series representation into a frequency spectrum. The method further includes identifying one or more local frequency maxima in the frequency spectrum as corresponding to one or more vital signs of the person.

Measurement of vital signs based on images recorded by an egocentric camera

A method and system for detecting small leaks in a plumbing system is disclosed. A temperature sensor coupled to the water in the plumbing system is used to determine if there is a leak. During times of inactivity for fixtures in the plumbing systems, a flow sensor might measure usage of water that would indicate a leak. For very small leaks, the flow is below a minimum measurable flow of the flow sensor. Embodiments of the invention measure temperature of water within a pipe coupled to the plumbing system. Temperature will generally decay in a particular predicable way when there is flow as the temperature of water upon entry to the building is lower than the air temperature within the building. Signal processing, machine learning and/or statistical approaches are used to analyze the temperature and optionally flow and/or pressure over time to determine when a leak is likely.

Passive leak detection for building water supply

A computing device, such as a wearable device, may include at least two electrodes mounted on a body. The computing device may determine an electrical signal associated with a circuit that includes the at least two electrodes and the user. A pressure applied to at least one electrode of the at least two electrodes may be determined from the electrical signal, and at least one function of the computing device may be implemented, based on the pressure.

Touch pressure input for devices

By monitoring pressure transients in a liquid within a liquid distribution system using only a single sensor, events such as the opening and closing of valves at specific fixtures are readily detected. The sensor, which can readily be coupled to a faucet bib, transmits an output signal to a computing device. Each such event can be identified by the device based by comparing characteristic features of the pressure transient waveform with previously observed characteristic features for events in the system. These characteristic features, which can include the varying pressure, derivative, and real Cepstrum of the pressure transient waveform, can be used to select a specific fixture where a valve open or close event has occurred. Flow to each fixture and leaks in the system can also be determined from the pressure transient signal. A second sensor disposed at a point disparate from the first sensor provides further event information.

Sensing events affecting liquid flow in a liquid distribution system

The various embodiments herein provide an energy harvester which can capacitively harvest stray electric field from low-voltage AC power lines without a physical grounding connection. The energy harvester comprises an inner electrode, an outer electrode and a circuit. The inner electrode forms an inner periphery of an upper portion of a harvester housing. The outer electrode forms an inner base of a lower portion of the harvester housing to provide a local ground reference. The circuit is housed within the lower portion of the harvester housing to direct stored energy and control an energy discharge.

Capacitive energy harvester from AC power lines

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Seattle, WA, United States of America

Shwetak N Patel