Abstract: A device can include a first transparent display having a at least one pixel, wherein transparency of the at least one pixel is electronically controlled, and a second transparent display configured to emit an image. Selected regions of the image are shown by having regions of the second transparent display corresponding to the selected regions of the image be transparent and regions of the first transparent display corresponding to the selected regions of the image appear opaque.

Abstract: An apparatus for assessing heart failure can include an image sensor configured to capture image data of a patient, a sensor configured to capture sensor data for the patient, a memory configured to store the image data and the sensor data, and a processor coupled to the image sensor, the sensor, and the memory. The processor is configured to receive image data in response to detecting a biological condition from the sensor data, wherein the biological condition is indicative of psychophysiological health and cardiac health. The processor is further configured to detect a visual characteristic from the image data, wherein the visual characteristic is indicative of heart health, and, in response to detecting the visual characteristic, provide an indication that the patient is experiencing a worsening of heart failure.

Abstract: 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.

Abstract: Detecting depression may include generating, using a sensor, sensor data for a user and automatically detecting, using a processor, a marker for depression in the sensor data. Responsive to determining, using the processor, that a condition is satisfied based upon the marker for depression, a survey is presented using a device.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method for determining a stress level of a user based on a sympathovagal balance (SVB) value calculated based on a set of measurement data may include determining a heart-rate variability (HRV) characteristic as a ratio involving a number of autonomic nervous system (ANS) activity markers within a first portion of the set of measurement data and the number of ANS activity markers within a second portion of the set of measurement data, and then determining the stress level of the user based on the HRV characteristic. The first and second portions of the set of measurement data may be selected based on a user-specific baseline SVB value that divides a histogram representation of the set of measurement data into the first and second portions.

Abstract: 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.

Abstract: 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.

Abstract: The touch sensor is a touch sensor that senses changes in characteristics of the electromagnetic signal in an environment in order to detect the contact or the proximity.

Abstract: In one embodiment, one or more computer-readable non-transitory storage media embody software that is operable when executed to determine, based on cardiac-activity data, a shift in sympathovagal balance (SVB) during the period of time; obtain an emotional-state characteristic the emotional-state characteristic being based on brain-wave activity data; and determine, based on the SVB shift and the emotional-state characteristic, an estimate of an emotional state of the user during the period of time.

Abstract: In one embodiment, a wearable apparatus includes a sensor, a processor coupled to the sensor, and a memory coupled to the processor that includes instructions executable by the processor. When executing the instructions, the processor detects by the sensor movement of at least a portion of an arm of a user; detects, based at least in part on the movement, a gesture made by the user; and processes the gesture as input to the wearable apparatus.

Abstract: In one embodiment, a wearable apparatus includes a sensor, a processor coupled to the sensor, and a memory coupled to the processor that includes instructions executable by the processor. When executing the instructions, the processor detects by the sensor movement of at least a portion of an arm of a user; detects, based at least in part on the movement, a gesture made by the user; and processes the gesture as input to the wearable apparatus.

Abstract: In one embodiment, a method includes determining, based on output from a sensor, a proximity of an object to a device and comparing the determined proximity to a threshold proximity. The method further includes selecting, based on the comparison, an interaction mode for processing interactions between the object and the device. The method further includes processing interactions between the object and the device according to the selected interaction mode.

Abstract: In one embodiment, an electronic device may include a light source configured to emit light that penetrates into a portion of a user's body, a plurality of light sensors configured to detect a pattern of diffusion of the emitted light, and a controller configured to detect a gesture made by the user based on the detected pattern of diffusion of the emitted light. The controller may be configured to control the light source and the plurality of light sensors to detect the gesture made by the user.