A computer-implemented method for direct photoplethysmography or direct PPG comprises obtaining during a time interval plural PPG signals for respective sensors in a wearable device; and combining the plural PPG signals to thereby obtain a multi-sensor PPG signal.

Aspects of the present disclosure provide methods, apparatuses, and systems for closed-loop sleep protection and/or sleep regulation. According to an aspect, sleep disturbing noises are predicted and a biosignal parameter is measured to dynamically mask predicted disturbing environmental noises in the sleeping environment with active attenuation. Environmental noises in a sleeping environment of a subject are detected, input, or predicted based on historical data of the sleeping environment collected over a period of time. The biosignal parameter is used to determine sleep physiology of a subject. Based on the environmental noises in the sleeping environment and the determined sleep physiology, the noises are predicted to be disturbing or non-disturbing noises. For predicted disturbing noises, one or more actions are taken to regulate sleep and avoid sleep disruption by using sound masking prior to or concurrently with the occurrence of the predicted disturbing noises.

Devices and methods for generating synthetic cardio-respiratory signals from one or more ballistocardiogram (BCG) sensors. A method for determining item specific parameters includes obtaining ballistocardiogram (BCG) data from one or more sensors, where the one or more sensors capture BCG data for one or more subjects in relation to a substrate. For each subject, the captured BCG data is pre-processed to obtain cardio-respiratory BCG data. The cardio-respiratory BCG data is sub-sampled to generate the cardio-respiratory BCG data at a cardio-respiratory sampling rate conducive to cardio-respiratory signal generation. The sub-sampled cardio-respiratory BCG data is cardio-respiratory processed to generate a cardio-respiratory parameter set. A synthetic cardio-respiratory signal is generated from at least the cardio-respiratory parameter set and a cardio-respiratory event morphology template. A condition of the subject is determined based on the synthetic cardio-respiratory signal.

Embodiments of the present disclosure sets forth a computer-implemented method comprising receiving, from at least one sensor, sensor data associated with an environment, computing, based on the sensor data, a cognitive load associated with a user within the environment, computing, based on the sensor data, an affective load associated with an emotional state of the user, determining, based on both the cognitive load at the affective load, an affective-cognitive load, determining, based on the affective-cognitive load, a user readiness state associated with the user, and causing one or more actions to occur based on the user readiness state.

Vision-based stimulus monitoring and response systems and methods are presented, wherein detection, via image(s) of a patient through an external stimulus, such as a caregiver, prompts analysis of the response of the patient, via secondary patient sensors or via analysis of patient image(s), to determine an autonomic nervous system (ANS) state.

Systems, devices, and methods described herein relate to multi-sensory presentation devices, including virtual reality (VR) devices, visual display devices, sound devices, haptic devices, and other forms of presentation devices, that are configured to present sensory elements, including visual and/or audio scenes, to a user. In some embodiments, one or more sensors including electroencephalography (EEG) sensors and a photoplethysmography (PPG) sensors, e.g., included in a brain-computer interface, can measure physiological data of a user to monitor a state of the user during the presentation of the visual and/or audio scenes. Such systems, devices, and methods can adapt one or more visual and/or audio scenes based on user physiological data, e.g., to control or manage the state of the user.

A local wearable brain wave cap device for detection is provided to simultaneously detect brainwave and heart rate variability data of a subject and includes a brain wave detection cap, at least one ear electrode and a transmission unit. The brain wave detection cap includes a wearable device and a plurality of electrode units. The wearable device is suitable for arranging the plurality of electrode units on brain wave positions corresponding to head of a subject. Each of the plurality of electrode units includes an accelerator, a storage unit, an input/output unit and a primary amplifier for detecting a brain wave.

A portable apparatus includes an exercise-measurement circuitry that measures exercise-related measurement data related to a user carrying out an exercise, a communication circuitry configured to provide the portable apparatus with wireless communication capability, and a processing circuitry configured to a perform operations. The operations include receiving the exercise-related measurement data from the exercise-measurement circuitry, receiving configuration data from an external user interface apparatus over a bidirectional wireless communication connection established through the communication circuitry and capable of transferring payload data to both directions, processing the exercise-related measurement data according to the received exercise-related parameters in order to obtain advanced exercise-related data, and communicating the advanced exercise-related measurement data to the user interface apparatus over the bidirectional wireless communication connection.

Methods for calculating a MetaKG signal are provided. The method including illuminating a region of interest in a sample with a near-infrared (NIR) light source and/or a visible light source. The region of interest includes a sample portion and background portion, each having a different set of optical characteristics. Images of the region of interest are acquired and processed to obtain metadata associated with the acquired images. MetaKG signals are calculated for the region of interest and for the background. The MetaKG signal for the background is used to adjust the MetaKG signal for the region of interest to provide a final adjusted MetaKG signal for the region of interest.

Described are systems for beds that can include sensors for sensing physical phenomena in an environment surrounding a bed, a display for outputting information about the environment, the bed, and a sleeper, and a controller communicably coupled to the sensors. The controller can receive the sensed physical phenomena from the sensors, analyze the physical phenomena to determine at least one of environmental, sleep, and health metrics of a sleeper in the bed, and determine, based on at least one of the environmental, sleep, and health metrics of the sleeper, control signals to modify the environment surrounding the bed. The controller can also output, at the display, the environmental, sleep, and health metrics of the sleeper. The controller can also transmit the control signals to a second controller in order to engage a home automation device. The physical phenomena can include ambient sound, ambient light, ambient CO2 concentration, and/or ambient temperature.