An exemplary system includes a photodetector configured to generate a plurality of photodetector output pulses over time as a plurality of light pulses are applied to and scattered by a target, a TPSF generation circuit configured to generate, based on the photodetector output pulses, a TPSF representative of a light pulse response of the target, and a control circuit configured to direct the TPSF generation circuit to selectively operate in different resolution modes.

Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an Analytics Engine that receives one more signal files that include neural signal data of a user based on voltages detected by one or more electrodes on a set of headphones worn by a user. The Analytics Engine preprocesses the data, extracts features from the received data, and feeds the extracted features into one or more machine learning models to generate determined output that corresponds to at least one of a current mental state of the user and a type of facial gesture performed by the user. The Analytics Engine sends the determined output to a computing device to perform an action based on the determined output.

Systems and methods to adapt a digital application environment based on psychological attributes of individual users are disclosed. Exemplary implementations may: store, in electronic storage, information associated with the individual users; obtain application usage information from client computing platforms associated with users; obtain stated information provided by the users; determine, based on the sets of answers, sets of psychological parameter values for the individual users; identify, based on the sets of psychological parameter values for the individual users, clusters of users that have similar sets of psychological parameter values; determine adaptions to the digital application environments provided by the client computing platforms for the individual users based on the clusters; and transmit the adaptations to the client computing platforms for implementation.

Apparatus, systems, and methods for monitoring a sensor module mounted in a sensor platform, wherein the sensor platform includes an adhesive side and a pocket, wherein the pocket is designed to receive the sensor module, to facilitate sensing by the sensor module of physiological attributes, and to allow insertion and removal of the sensor device from the pocket.

A system and method for prompting a patient experiencing ventilatory depression to breathe includes at least one sensor for detecting ventilatory depression by detecting inadequate breathing or lack of breathing in the patient. The system also includes one or more sensors for determining the type of breathing problem experienced by the patient. A sensor for detecting motion of the patient is used to determine whether the patient is moving. If inadequate or a lack of breathing is detected and the patient is not moving, the system provides verbal prompts or tactile stimuli to prompt the patient to breathe to improve patient ventilation.

A percussive therapy system that includes a percussive massage device including a network interface, and an intelligence engine. The intelligence engine is configured to receive manual capture data and real-time tracking data from the percussive massage device, receive remote data from a remote data source, and generate recommendation data comprising a recommended protocol to be performed by the percussive massage device. The recommendation data is generated from demographic, activity, temporal, analytics, and biometric data, received from the manual capture data, the real-time tracking data, and the remote data inputs.

A method and a system for providing feedback to a user for adjusting sleep pattern of the user. The method includes collecting a set of information related to the user, receiving a set of measurement data related to the user from a wearable electronic device, defining circadian rhythm and duration of sleep of the user, determining sleep scores for a predefined number of days and associating each sleep score with a corresponding go-to-bed time or time of falling asleep of the user. A sleep score is determined for each of the predefined number of days from the collected set of information, the set of measurement data, the circadian rhythm and the duration of sleep of the user. The method further includes analysing the sleep scores and associated go-to-bed time or time of falling asleep of the user to determine an optimum bedtime window for the user and providing feedback to the user based on the analysed sleep scores and the optimum bedtime window.

An autonomic nerve control device includes an obtainer that obtains a physiological quantity of a user before the user occupies a moving body, and a controller that controls the autonomic nerves of the user occupying the moving body based on the physiological quantity of the user obtained by the obtainer.

Various embodiment disclosed herein include a method for monitoring serum potassium in a patient. The method can include gathering cardiac electrogram data from the patient using two or more electrodes, separating the cardiac electrogram data into discrete subunits including a T-wave, aligning T-waves to create aligned discrete subunits, averaging the aligned discrete subunits to generate an average T-wave for the cardiac electrogram data, and determining a serum potassium value using the average T-wave for the cardiac electrogram data and a predetermined model relating T-wave values with serum potassium magnitudes.

An electronic device includes a first outputter and a processor. The processor is configured to acquire biometric information that is information about a living body, calculate a reliability of the biometric information based on the acquired biometric information, and output the biometric information to the first outputter in an output mode associated with the calculated reliability.