A system and method for identifying sleep states of a subject are provided. In some aspects, the method includes acquiring physiological data from a subject over a sleep period using sensors positioned about the subject, and assembling the physiological data into time-series datasets. The method also includes selecting a temporal window in which signals associated with the time-series datasets are substantially stationary, computing a time bandwidth product based on a selected spectral resolution and the selected temporal window, and determining a number of tapers using the computed time bandwidth product. The method further includes computing a spectrogram using the determined number of tapers and the time-series datasets, analyzing the spectrogram to identify signatures of sleep in the subject, and generating, using the identified signatures, a report indicative of sleep states of the subject.

A system and method for identifying sleep states of a subject are provided. In some aspects, the method includes acquiring physiological data from a subject over a sleep period using sensors positioned about the subject, and assembling the physiological data into time-series datasets. The method also includes selecting a temporal window in which signals associated with the time-series datasets are substantially stationary, computing a time bandwidth product based on a selected spectral resolution and the selected temporal window, and determining a number of tapers using the computed time bandwidth product. The method further includes computing a spectrogram using the determined number of tapers and the time-series datasets, analyzing the spectrogram to identify signatures of sleep in the subject, and generating, using the identified signatures, a report indicative of sleep states of the subject.

A system for carbon dioxide (CO2) removal from a circulatory system of a patient includes a medical device providing extracorporeal lung assist (ECLA) treatment to the patient through extracorporeal removal of CO2 from the patient's blood; at least one control unit controlling the operation of the medical device so as to control a degree of CO2 removal obtained by the ECLA treatment; and a bioelectric sensor detecting a bioelectric signal indicative of the patient's efforts to breathe. The at least one control unit is configured to control the operation of the medical device based on the detected bioelectric signal.

A system for carbon dioxide (CO2) removal from a circulatory system of a patient includes a medical device providing extracorporeal lung assist (ECLA) treatment to the patient through extracorporeal removal of CO2 from the patient's blood; at least one control unit controlling the operation of the medical device so as to control a degree of CO2 removal obtained by the ECLA treatment; and a bioelectric sensor detecting a bioelectric signal indicative of the patient's efforts to breathe. The at least one control unit is configured to control the operation of the medical device based on the detected bioelectric signal.

Various embodiments of an apparatus, methods, systems and computer program products described herein are directed to an Analytics Engine that receives one more signal files that include neural signal data of a user based on voltages detected by one or more electrodes on a set of headphones worn by a user. The Analytics Engine preprocesses the data, extracts features from the received data, and feeds the extracted features into one or more machine learning models to generate determined output that corresponds to at least one of a current mental state of the user and a type of facial gesture performed by the user. The Analytics Engine sends the determined output to a computing device to perform an action based on the determined output.

The present disclosure discloses a method for displaying a motion monitoring interface. The method includes: obtaining a movement signal during a motion of a user from at least one sensor, wherein the movement signal at least includes an electromyographic signal or an attitude signal; determining information related to the motion of the user by processing the movement signal; and displaying the information related to the motion of the user.

The present disclosure discloses a method for displaying a motion monitoring interface. The method includes: obtaining a movement signal during a motion of a user from at least one sensor, wherein the movement signal at least includes an electromyographic signal or an attitude signal; determining information related to the motion of the user by processing the movement signal; and displaying the information related to the motion of the user.

A device for diagnosing an abnormality by measuring a minimal change in a muscle according to an embodiment includes a vibration unit that provides vibration to a body part of a user; a measuring unit that detects a minimal change in a muscle by measuring a change in elasticity of the body part according to the vibration; and a processing unit that calculates an abnormality of the body part based on the change in the elasticity of the body part, wherein the processing unit calculates the abnormality of the body party by using an algorithm that detects a degree to which a specific value of the muscle is far from a distribution chart by analyzing data distribution or an anomaly detection algorithm that detects whether there is anomaly in a variable.

A device for diagnosing an abnormality by measuring a minimal change in a muscle according to an embodiment includes a vibration unit that provides vibration to a body part of a user; a measuring unit that detects a minimal change in a muscle by measuring a change in elasticity of the body part according to the vibration; and a processing unit that calculates an abnormality of the body part based on the change in the elasticity of the body part, wherein the processing unit calculates the abnormality of the body party by using an algorithm that detects a degree to which a specific value of the muscle is far from a distribution chart by analyzing data distribution or an anomaly detection algorithm that detects whether there is anomaly in a variable.

Systems and methods for correlating inputs found external to a user to inputs measured from the user are disclosed, using wearables, various types of non-wearable sensors, and other external data sources and mobile device technology. Pattern matching and rules can be used to provide useful suggestions or control external machines based on the correlated inputs.