A system includes one or more sensors to detect activities of a mobile object; and a processor coupled to the sensor and the wireless transceiver to classify sequences of motions into groups of similar postures each represented by a model and to apply the models to identify an activity of the object.

Respiratory-based biofeedback devices, systems, and methods are provided. A respiratory biofeedback method includes producing a respiratory signal in response to a user's respiratory activity, generating an audio output signal that includes a modified version of the respiratory signal, and converting the audio output signal into sound waves output to the user to provide biofeedback. The sound waves can be output to the user in real time response to the user's respiratory activity. A microphone can be used to generate the respiratory signal. The generated audio output signal can includes the respiratory signal modified to increase a volume level of a portion of the respiratory signal where the volume level exceeds a specified volume level.

The present disclosure relates to an electrical connector for providing signal isolation between various components of a physiological monitoring system. In an embodiment, the electrical connector is placed between a sensor and associated monitoring system and includes a physical barrier and inductive components.

Systems and methods for discovery and characterization of neuroactive drugs are provided. In some aspects, a method for evaluating an effectiveness of a drug administered to a subject includes receiving neurophysiological data acquired from a subject under an administration of a drug, and analyzing the neurophysiological data to generate signatures indicative of brain states induced by the drug. The method also includes correlating the generated signatures with a database comprising information associated with a plurality of drug profiles, and determining, using the information, a molecular activity profile for the drug. The method further includes generating a report indicative of the effectiveness of the drug using the molecular activity profile.

Systems and methods for inducing natural sleep in a subject is provided. In some aspects, the method includes inducing a first sleep state; monitoring a first plurality of characteristics of a brain of the subject to verify the subject is in the first sleep state; inducing a second sleep state after the subject has been in the first sleep state for a predetermined amount of time; and monitoring a second plurality of characteristics of the brain of the subject to verify the subject is in the second sleep state.

An earpiece includes an earpiece housing, at least one biometric sensor disposed within the earpiece, a wireless transceiver disposed within the earpiece for voice communications, an intelligent control operatively connected to the at least one biometric sensor and the wireless transceiver, a speaker operatively connected to the intelligent control, and at least one microphone operatively connected to the intelligent control. The earpiece is configured to monitor biometrics of a user using the at least one biometric sensor, communicate biometric data to the user, detect a crisis level event, and communicate occurrence of the crisis level event using the wireless transceiver.

A monitoring apparatus includes a wearable electronic device having an audio port and a headset having at least one earbud, at least one physiological and/or environmental sensor, and circuitry that processes signals produced by the at least one physiological and/or environmental sensor and transmits the processed signals to the electronic device via the audio port. The headset may include a microphone in audio communication with the electronic device via the audio port, and the circuitry modulates audio signals produced by the microphone and signals produced by the at least one physiological and/or environmental sensor for transmission to the electronic device via the audio port. The circuitry may power the at least one physiological and/or environmental sensor via power supplied by the electronic device through the audio port and may include a processor that coordinates collection, modulation, and/or transmission of signals produced by the at least one physiological and/or environmental sensor.

A method and system for monitoring impairment indicators. The method includes, during a first time window, measuring a first movement signal related to movement of the person with a movement sensor associated with the person, and measuring a first biological signal of the person with a biological sensor attached to the person. The method further includes electronically storing at least one numerical descriptor derived from the first movement signal and at least one numerical descriptor derived from the first biological signal as reference data for the person. The method includes during a second time window, measuring a second signal related to movement of the person with the movement sensor, and measuring a second biological signal of the person with the biological sensor. The method further includes comparing at least one numerical descriptor derived from the second signal and at least one numerical descriptor derived from the second biological signal to the reference data to identify an impairment indicator.

[Problem]

It is intended to quantitatively evaluate deterioration in brain function associated with a disease such as dementia, with a high degree of accuracy by a simplified method using signals acquired from a few sensors arranged on the scalp.

[Solution]

The present invention relates to a brain activity measurement device comprising: a signal acquisition part configured to acquire a signal from a brain of the subject, using three sensors attached to different locations on the surface of the head of a subject; a data extraction part configured to extract, from each of the three signals acquired from respective ones of the sensors, a deep-brain potential signal having a specific frequency band arising from an activity of a deep brain region, and acquire data from the extracted deep-brain potential signal with a sampling period; a correlation value calculation part configured to calculate a correlation value indicative of a correlative relationship among the deep-brain potential signals acquired from each respective sensors, based on a phase relationship among three pieces of time-series data each extracted from the respective sensors by the data extraction part; and an index value calculation part configured to analyze the deep-brain potential signals from the deep brain region, based on the calculated correlation value, to calculate an index value for determining a brain function.

The present invention belongs to the technical field of processing and analysis of biomedical signals, and provides a calibration method for the critical point of mental fatigue based on self-organized criticality. It constructs a self-organized criticality model by using the dynamic characteristics of a brain network, and deduces the avalanche dynamics of mental fatigue, which is consistent with the internal mechanism of evolution of fatigue complexity. The critical state of calibration is dynamically stable and robust. Through the verification of the behavior data, the reliability of the critical state of mental fatigue determined from physiological and behavioral dimensions is high, providing support for the setting of the fatigue category labels to complete more accurate classification and recognition.