A system includes a collar that is worn around a neck of the user. A stimulator is coupled to the collar such that the stimulator is positioned adjacent to an airway of the user. The sensor is coupled to the collar and configured to generate data associated with the airway of the user. The memory is coupled to the collar and storing machine-readable instructions. The control system is coupled to the collar and includes one or more processors configured to execute the machine-readable instructions to determine, based at least on an analysis of the generated data, that the user is currently experiencing an apnea event. In response to the determination, the control system causes the stimulator to provide electrical stimulation, at a first intensity level, to one or more muscles of the user that are adjacent to the airway to aid in stopping the apnea event.

A lighting system for establishing a database of multispectral circadian rhythm lighting scenario and psychological stress indicators is configured in space, which is characterized by downloading the multispectral circadian rhythm lighting scenario database from the cloud; the multispectral lighting parameters and circadian rhythm parameters are selected from the multispectral circadian rhythm lighting scenario database to start the light-emitting device for lighting; the ambient light sensor measures and judges whether the circadian rhythm parameters reach the set value; when each circadian rhythm parameter in the circadian rhythm lighting scenario database has reached the set value, the light-emitting device is started for lighting; after the blood or saliva of the light control subjects were tested, the psychological stress index values of the illuminators were obtained; the portable communication device transmits the circadian rhythm parameters and psychological stress index values to the cloud; among them, the circadian rhythm parameters include: circadian rhythm lighting parameters and circadian rhythm scenario parameters.

The present invention provides a method and apparatus for treating a subject suffering from obstructive sleep apnea (OSA). In one embodiment, the method of the present invention is configured to deliver negative airway pressure to a subject's airway to strengthen the airway muscle tone.

Medical device systems and methods for operating medical device systems conserve energy by efficiently managing computational demands of the systems. A first analysis, having relatively lower computational processing demand than at least a second analysis, processes signals from a subject to determine a first estimate of a propensity for the subject to have a neurological event. If the first estimate meets a set of specified criteria, a second analysis is performed to determine a second estimate of the propensity for the subject to have a neurological event.

Medical device systems and methods for operating medical device systems conserve energy by efficiently managing computational demands of the systems. A first analysis, having relatively lower computational processing demand than at least a second analysis, processes signals from a subject to determine a first estimate of a propensity for the subject to have a neurological event. If the first estimate meets a set of specified criteria, a second analysis is performed to determine a second estimate of the propensity for the subject to have a neurological event.

A sleep assessment system includes a blood flow measurement unit and a assessment unit. The blood flow measurement unit acquires first information related to the blood flow of the user. The assessment unit determines the sleep stage of the user based on the first biological information.

A sleep assessment system includes a blood flow measurement unit and a assessment unit. The blood flow measurement unit acquires first information related to the blood flow of the user. The assessment unit determines the sleep stage of the user based on the first biological information.

A subject's Default Mode Network is accessed through corresponding measurements of the Micro-Coherence Oximetry Network Strength (MCO-S). An associated MCO-S system (100) includes a wearable (102), a user device (112) and a processing platform (123). The wearable (102) collects subject information sufficient to enable monitoring and optimization of the subject's Default Mode Network include sensors such as pulse oximetry instrumentation and EEG electrodes to obtain brainwave data, oxygen saturation data, heart rate variability data, and galvanic skin conductance data. Information from the sensors may be communicated to a user device (112), such as a cell phone or VR headset. The user device (112) communicates with a remote processing platform (123) that may execute artificial intelligence functionality and other logic in connection with assessing the patient's micro-coherence network strength and optimizing behavior modification protocols in relation to attributes and objectives of the subject.

A subject's Default Mode Network is accessed through corresponding measurements of the Micro-Coherence Oximetry Network Strength (MCO-S). An associated MCO-S system (100) includes a wearable (102), a user device (112) and a processing platform (123). The wearable (102) collects subject information sufficient to enable monitoring and optimization of the subject's Default Mode Network include sensors such as pulse oximetry instrumentation and EEG electrodes to obtain brainwave data, oxygen saturation data, heart rate variability data, and galvanic skin conductance data. Information from the sensors may be communicated to a user device (112), such as a cell phone or VR headset. The user device (112) communicates with a remote processing platform (123) that may execute artificial intelligence functionality and other logic in connection with assessing the patient's micro-coherence network strength and optimizing behavior modification protocols in relation to attributes and objectives of the subject.

In one example embodiment of the invention, a simulation based training system is provided having a sensor that unobtrusively collects objective data for individuals and teams experiencing training content to determine the cognitive states of individuals and teams; time-synchronizes the various data streams; automatically determines granular and objective measures for individual cognitive load (CL) of individuals and teams; and automatically determines a cognitive load balance (CLB) and a relative cognitive load (RCL) measure in real or near-real time. Data is unobtrusively gathered through physiological or other activity sensors such as electroencephalogram (EEG) and electrocardiogram (ECG) sensors. Some embodiments are further configured to also include sociometric data in the determining cognitive load. Sociometric data may be obtained through the use of sociometric badges. Some embodiments further automatically customize the simulation content by automatically selecting content based on the CL of the individuals and teams.