Samsung Electronics Co., Ltd.

James Young

Sajid Hassan Sadi

Cody Blair Wortham

Jawahar Jain

Pranav K Mistry

Ayesha Mudassir Khwaja

Abhijit Z Bendale

Ye Zhao

Paul Kim

Ruokan He

Selene A Mota Toledo

Bo Hyun Moon

In one embodiment, the system receives unlabeled data from one or more sensors. The one or more sensors are associated with a computing device of a user. The system clusters the unlabeled data into one or more unlabeled clusters. The system determines, based on one or more rules, at least one label for at least one unlabeled cluster of the one or more unlabeled clusters. The system expands, by a natural language processing algorithm, the at least one label for the at least one unlabeled cluster to produce one or more semantic terms associated with the at least one unlabeled cluster. The system generates, based on the one or more semantic terms, a personalized graph associated with one or more behavioral patterns of the user.

Methods and systems for interacting with mobile device

A system for evaluating health-related quality of life (HRQOL) can include a sensor adapted to generate sensor data for a user, a memory adapted to store the sensor data, and a processor coupled to the sensor and the memory. The processor can be configured to initiate executable operations including determining a first biological marker for the user from the sensor data, wherein the first biological marker is indicative of a first dimension of HRQOL, performing speech analysis on user provided speech to determine a second biological marker indicative of a second dimension of HRQOL. The processor is further configured to initiate executable operations including comparing the first biological marker and the second biological marker with a baseline for the first biological marker and a baseline for the second biological marker, respectively, and outputting a result of the comparing.

Sensor assisted evaluation of health and rehabilitation

Chronotherapeutic dosing can include receiving, using a processor, sensor data from a sensor for a user, wherein the sensor data is collected subsequent to the user starting a regimen for a medication, determining, using the processor, a biological marker from the sensor data, wherein the biological marker is correlated with the medication, and comparing, using the processor, the biological marker with an expected state of the biological marker based upon a dose time of the medication. Chronotherapeutic dosing can also include providing, using the processor, a notification indicating a result of the comparing.

Chronotherapeutic dosing of medication and medication regimen adherence

Processing PPG data using a device can include determining a quality estimate for a segment of PPG data and, in response to determining that the quality estimate exceeds a quality threshold, filtering the segment of the PPG data based upon an estimate of periodicity of the segment of the PPG data. A health marker can be determined for the segment of PPG data. The health marker can be validated based upon a prior determination of the health marker from PPG data. In response to the validation, the health marker can be output.

Determining health markers using portable devices

Evaluating health of a user can include providing an equilibrium envelope for a user, wherein the equilibrium envelope includes a range for each of a plurality of vital signs, and detecting, using a processor, a current metric. The current metric corresponds to an exit condition for the equilibrium envelope determined based upon sensor data or a re-entry condition for the equilibrium envelope determined based upon the sensor data. A health status for the user can be determined, using the processor, based upon a comparison of the current metric with a historical metric for the user.

Determining a health status for a user

In one embodiment, a computer-readable non-transitory storage medium embodies software that is operable when executed to, in real time, capture a number of images of a user; identify one or more regions of interest corresponding to one or more superficial arteries of the user. The identification is based on a signal-to-noise ratio of photoplethysmogram (PPG) data obtained from the plurality of images. The software is further operable to measure, based on the PPG data, blood volume pulse (BVP) signals; and based on the measured BVP signals, compute one or more cardiological metrics for the user.

Determining artery location using camera-based sensing

In one embodiment, a computer-readable non-transitory storage medium embodies software that is operable when executed to, in real time, capture a number of images of a user; and determine a time-series signal for the user based on the plurality of images. The signal includes one or more segments that are physiologically plausible and one or more segments that are physiologically implausible. The software is further operable to identify one or more of the physiologically plausible sub-segments based on one or more pre-defined signal characteristics; and calculate one or more heartrate measurements based on the physiologically plausible sub-segments.

Determining cardiovascular features using camera-based sensing

In one embodiment, a computer-readable non-transitory storage medium embodies software that is operable when executed to, in real time, capture, by a single sensor, a number of images of a user; determine, based on the number of images, one or more short-term cardiological signals of the user during a period of time; estimate, based on the cardiological signals, a first short-term emotional state of the user; determine, based on the number of images, one or more short-term neurological signals of the user during the period of time; estimate, based on the neurological signals, a second short-term emotional state of the user; compare the first estimated emotional state to the second estimated emotional state; and in response to a determination that the first estimated emotional state corresponds to the second estimated emotional state, determine a short-term emotion of the user during the period of time.

Determining emotions using camera-based sensing

A system and method for remote active noise correction at a remote device includes receiving, at the remote device, an ambient noise signal from a microphone. The remote device is disposed along a processing and transmission path between the microphone and a headphone. The processing and transmission path exhibit non-zero latency. The remote device further analyzes the ambient noise signal to generate an anti-noise signal, performs a first correction of the anti-noise signal for a headphone interface effect, performs a second correction of the anti-noise signal for the non-zero latency of the processing and transmission path between the microphone and the headphone. The remote device then transmits the corrected anti-noise signal to the headphone.

Mobile platform based active noise cancellation (ANC)

In one embodiment, a method includes accessing first time-series data based on electromagnetic radiation in a first spectrum and second time-series data based on electromagnetic radiation in a second spectrum. The method also includes comparing the first time-series data with the second time-series data and determining, based on the comparison, (1) whether a stopping condition associated with a device has occurred or (2) whether a discarding condition associated with the first time-series data or the second time-series data has occurred.

Detecting live tissues using signal analysis

A method for monitoring a health characteristic of a user based on one or more biological measurements may include selecting a context from a plurality of contexts, each context corresponding to a baseline health value, and each context being defined by a plurality of recorded events each comprising one or more of repeated biological states, repeated user activity, or space-time coordinates of the user, and then monitoring the health characteristic of the user based on one or more bio-sensing measurements in comparison to the baseline health value corresponding to the selected context.

Determining baseline contexts and stress coping capacity

In particular embodiments, a method for determining a heart-rate variability (HRV) measurement of a user may include receiving, from a sensor of an electronic device of the user, heart sensor data, determining a noise level of the heart sensor data, and then adjusting the HRV measurement by an amount calculated based on the determined noise level. The sensor data may include data on a photoplethysmograph (PPG) signal over a noise-calculation time period.

Performance of biological measurements in the presence of noise

Detecting chronotropic incompetence includes determining, using a processor, a baseline cardiac health measure for a user based upon an estimate of activity level for the user, validating, using the processor, the estimate of activity level for the user with a validation factor determined from sensor data and determining, using the processor, a cardiac health measure for the user from the sensor data. A signal indicating chronotropic incompetence for the user can be provided by the processor based upon a comparison of the cardiac health measure for the user with the baseline cardiac health measure.

Detection of chronotropic incompetence

A method for monitoring a stress level of a user may include determining, based on biological measurements on one or more physiological markers received in a first sampling mode, the stress level of the user, and then dynamically switching to a second sampling mode when it is determined that one or more of the physiological markers are above a threshold level, the second sampling mode being different from the first sampling mode.

Continuous stress measurement with built-in alarm fatigue reduction features

Monitoring health status of a user may be performed by an apparatus that includes a sensor adapted to generate sensor data, a memory adapted to store a plurality of baseline biological markers for a user, wherein the plurality of baseline biological markers include respiratory rhythm, and a processor coupled to the memory and the sensor. The processor is adapted to, in response to detecting that the user is performing physical activity, determine a biological marker from the sensor data. The processor is adapted to compare the biological marker with the baseline biological marker. The processor is further adapted to, in response to detecting a change in the biological marker, provide a notification indicating a change in health status.

Growing community of inventors

Menlo Park, CA, United States of America

James Young