A61M2230/18

DEEP LEARNING-BASED SLEEP ASSISTANCE SYSTEM THROUGH OPTIMIZATION OF ULTRADIAN RHYTHM
20230233794 · 2023-07-27 ·

Disclosed herein are a sound sleep assistance apparatus, a sound sleep assistance method, and a sound sleep assistance system. According to an embodiment, there is provided a sound sleep assistance apparatus for assisting the sound sleep of a user by communicating with a sleep pad, the sound sleep assistance apparatus including: a communication interface configured to communicate with the sleep pad that acquires the physiological index information of the user while the user lies down; and a controller configured to determine the sleep stage of the user based on the physiological index information, and to provide a sound source corresponding to the determined sleep stage.

Controlling light exposure for circadian phase management

This disclosure pertains to a system configured to control light exposure for circadian phase management and/or light deficient disorders of a subject. The system comprises a user interface, physiological sensors configured to generate output signals conveying physiological data of the subject, and a light control valve configured to block or reduce blue light ambient radiation reaching eyes of the subject. Processors are in communication with the user interface, the physiological sensors, the light control valve, and radiation generators. The processors cause the system to receive physiological goals of the subject, determine a light control plan based on the physiological goals, the physiological data, environmental data, and time data. The system operates the light control valve to block or reduce blue light ambient radiation based on the light control plan, and generate, using the one or more radiation generators, therapeutic light radiation based on the light control plan.

Ear-worn electronic device for conducting and monitoring mental exercises

An ear-worn electronic device includes a right ear device comprising a first processor and a left ear device comprising a second processor communicatively coupled to the first processor. A physiologic sensor module comprises one or more physiologic sensors configured to sense at least one physiologic parameter from a wearer. A motion sensor module comprises one or more sensors configured to sense movement of the wearer. The first and second processors are coupled to the physiologic and motion sensor modules. The first and second processors are configured to produce a three-dimensional virtual sound environment comprising relaxing sounds, generate verbal instructions within the three-dimensional virtual sound environment that guide the wearer through a predetermined mental exercise that promotes wearer relaxation, and generate verbal commentary that assesses wearer compliance with the predetermined mental exercise in response to one or both of the sensed movement and the at least one physiologic parameter.

STIMULATION DEVICES, SYSTEMS, AND METHODS

Described herein are noninvasive electrical stimulation devices, systems and methods for stimulation of the Vagus nerve through its auricular branch to provide beneficial physiological responses in subjects, including alleviation, mitigation or elimination of symptoms of various disorders, including metabolic and inflammatory disorders.

STIMULATION DEVICES, SYSTEMS, AND METHODS

Described herein are noninvasive electrical stimulation devices, systems and methods for stimulation of the Vagus nerve through its auricular branch to provide beneficial physiological responses in subjects, including alleviation, mitigation or elimination of symptoms of various disorders, including metabolic and inflammatory disorders.

System and method for enhancing REM sleep with sensory stimulation

The present disclosure pertains to a system and method for automatically detecting rapid eye movement (REM) sleep and delivering sensory stimulation to prolong REM duration, without disturbing sleep. The sensory stimulation may be auditory or other stimulation. The system and method ensure timely delivery of the stimulation and automatically adjust the amount, intensity, and/or timing of stimulation as necessary. REM sleep is detected based on brain activity, cardiac activity and/or other information. REM sleep may be detected and/or predicted by a trained neural network. The amount, timing, and/or intensity of the sensory stimulation may be determined and/or modulated to enhance REM sleep in a subject based on one or more values of one or more intermediate layers of the neural network and one or more brain activity and/or cardiac activity parameters.

System and method for enhancing REM sleep with sensory stimulation

The present disclosure pertains to a system and method for automatically detecting rapid eye movement (REM) sleep and delivering sensory stimulation to prolong REM duration, without disturbing sleep. The sensory stimulation may be auditory or other stimulation. The system and method ensure timely delivery of the stimulation and automatically adjust the amount, intensity, and/or timing of stimulation as necessary. REM sleep is detected based on brain activity, cardiac activity and/or other information. REM sleep may be detected and/or predicted by a trained neural network. The amount, timing, and/or intensity of the sensory stimulation may be determined and/or modulated to enhance REM sleep in a subject based on one or more values of one or more intermediate layers of the neural network and one or more brain activity and/or cardiac activity parameters.

Method and device for enhancing memory consolidation

The present invention relates to methods and devices to consolidate memory and/or cognitive functions by monitoring brain rhythms and delivering a stimulus at an appropriate stage of sleep cycle.

SLEEP ASSESSMENT AND STIMULUS APPARATUS AND METHODS

A sleep assessment system includes a housing, processing circuitry, and a sensor assembly with a plurality of sensors configured to capture measurements that include indications of both brain and eye activity through the forehead of a subject. The processing circuitry is configured to receive sensor signals based on the measurements made by the plurality of sensors, process the sensor signals to generate sleep data, apply a sleep state convolutional neural network to the sleep data to determine a current sleep state of a subject, identify, based on the sleep data and the current sleep state, a sleep state-based data feature, and output a stimulus to the subject based on sleep state-based data feature. The housing is configured to be secured to the forehead of the subject, and the sensor assembly and processing circuitry are disposed on or within the housing.