Abstract: Embodiments in accordance with the present disclosure are directed to methods and apparatuses used for slow wave activity (SWA) optimization. An example method includes receiving one or more bio-signals from a user and classifying sleep stages by processing the bio-signals. The method further include determining dominant peripheral nervous system (PNS) oscillations based on the bio-signals and as a function of time and stage of sleep, and characterizing at least one property of the dominant PNS oscillations, including a phase, a phase shift, an amplitude, and/or frequency. The method further include providing an indication of an optimal window for maximizing SWA generation based on the phase, the phase shift, the amplitude, or the frequency. The indication is provided to stimulation circuitry that delivers stimulation to the user within the optimal window. Feedback is provided responsive to the stimulation based on an EEG signal of the user.

Abstract: Embodiments are directed to a non-transitory computer-readable storage medium comprising instructions that when executed cause processor circuitry to generate a longitudinal dataset of a set of features from tracked physical measurements of a user received from sensor circuitry, apply at least one machine learning model to the longitudinal dataset of the set of features to identify a pattern within the set of features indicative of a probability of the user being in a state of menopause, predict a current state of menopause for the user based on the identified pattern, and communicate a data message indicative of the current state of menopause for the user. In some embodiments, the set of features are compressed to pseudo-features and input to a first ML model using a second ML model.

Abstract: Embodiments in accordance with the present disclosure are directed to systems and methods for managing hot flashes and/or menopause symptoms. An example system includes sensor circuitry and logic circuitry. The sensor circuitry obtains a physical measurement associated with a user and communicates the physical measurement. The logic circuitry generates a predictive model that indicates a probability of the user having a hot flash at a date and time based on a plurality of input parameters, revises the probability based on the physical measurement using the predictive model, and communicates data indicative of an action in response to the revised probability being outside a threshold, such as providing cooling relief.

Abstract: Example embodiments are directed systems including processing circuitry and memory circuitry to store a predictive data model indicative of different patterns and probabilities of a user transitioning from an awake state to a sleep state. The processing circuitry is to detect, using data indicative of a current psychophysiological state of the user, a pattern among the different patterns of the predictive data model that is indicative of a probability of the user transitioning from the awake state to the sleep state at a date and time, based on the detected pattern, select an intervention action predicted to increase the probability of the user transitioning to the sleep state at the date and time, and communicate a message indicative of the intervention action to the user.

Abstract: Embodiments in accordance with the present disclosure are directed to systems, devices, and methods involving hot flash (HF) multi-sensor circuits. An example system includes a plurality of sensor circuits and processor circuitry. The sensor circuits obtain a plurality of sensor signals associated with the user. The processor circuitry extracts features from the plurality of sensor signals obtained by the plurality of sensor circuits, aligns the extracted features to a common time point, identifies a HF event for the user using a predictive data model indicative of probability of the HF event occurring for the user at a date and time and based on the aligned extracted features, and communicates a message indicative of the HF event to the user.

Abstract: A restorative health and wellness system that provides an immersive environment is provided herein. In some embodiments, the system includes one or more sensors configured to measure physiological properties of an individual and/or the properties of the individual's surroundings, one or more actuators configured to create the immersive environment for the individual, a control loop module configured to receive and analyze input from the one or more sensors, and to provide information to the actuators to create the immersive environment for the individual, wherein the one or more actuators dynamically create or adjust the immersive environment based on at least one of (A) the physiological properties measured or (B) the properties of the individual's surroundings, and at least one of (A) a pre-determined individual priority balance set for the individual or (B) an optimized set of parameters determined through advanced analytic techniques.

Abstract: Embodiments in accordance with the present disclosure are directed to methods and apparatuses used for slow wave activity (SWA) optimization. An example method includes receiving one or more bio-signals from a user and classifying sleep stages by processing the bio-signals. The method further include determining dominant peripheral nervous system (PNS) oscillations based on the bio-signals and as a function of time and stage of sleep, and characterizing at least one property of the dominant PNS oscillations, including a phase, a phase shift, an amplitude, and/or frequency. The method further include providing an indication of an optimal window for maximizing SWA generation based on the phase, the phase shift, the amplitude, or the frequency. The indication is provided to stimulation circuitry that delivers stimulation to the user within the optimal window. Feedback is provided responsive to the stimulation based on an EEG signal of the user.

Abstract: Embodiments in accordance with the present disclosure are directed to systems and methods for managing hot flashes and/or menopause symptoms. An example system includes sensor circuitry and logic circuitry. The sensor circuitry obtains a physical measurement associated with a user and communicates the physical measurement. The logic circuitry generates a predictive model that indicates a probability of the user having a hot flash at a date and time based on a plurality of input parameters, revises the probability based on the physical measurement using the predictive model, and communicates data indicative of an action in response to the revised probability being outside a threshold, such as providing cooling relief.

Abstract: A restorative health and wellness system that provides an immersive environment is provided herein. In some embodiments, the system includes one or more sensors configured to measure physiological properties of an individual and/or the properties of the individual's surroundings, one or more actuators configured to create the immersive environment for the individual, a control loop module configured to receive and analyze input from the one or more sensors, and to provide information to the actuators to create the immersive environment for the individual, wherein the one or more actuators dynamically create or adjust the immersive environment based on at least one of (A) the physiological properties measured or (B) the properties of the individual's surroundings, and at least one of (A) a pre-determined individual priority balance set for the individual or (B) an optimized set of parameters determined through advanced analytic techniques.

Abstract: Biofeedback virtual reality sleep assistant technologies monitor one or more physiological parameters while presenting an immersive environment. The presentation of the immersive environment changes over time in response to changes in the values of the physiological parameters. The changes in the presentation of the immersive environment are configured using biofeedback technology and are designed to promote sleep.

Abstract: Biofeedback virtual reality sleep assistant technologies monitor one or more physiological parameters while presenting an immersive environment. The presentation of the immersive environment changes over time in response to changes in the values of the physiological parameters. The changes in the presentation of the immersive environment are configured using biofeedback technology and are designed to promote sleep.

Abstract: Biofeedback virtual reality sleep assistant technologies monitor one or more physiological parameters while presenting an immersive environment. The presentation of the immersive environment changes over time in response to changes in the values of the physiological parameters. The changes in the presentation of the immersive environment are configured using biofeedback technology and are designed to promote sleep.