A state assessment system, a diagnosis and treatment system and a method for operating the diagnosis and treatment system are disclosed. An oscillator model converts a physiological signal of a subject into a defined feature image. A classification model analyzes state information of the subject based on the feature image. An analysis model outputs a treatment suggestion for the subject based on the state information of the subject. An AR projection device projects acupoint positions of a human body onto the subject, for the subject to be treated based on the treatment suggestion.

Disclosed are methods and medical device systems for automated delivery of therapies for pain and determination of need for and safety of treatment. In one embodiment, such a medical device system may comprise a sensor configured to sense at least one body signal from a patient; and a medical device configured to receive a first sensed body signal from the sensor; determine a patient pain index based at least in part on said first sensed body signal; determine whether said patient pain index is above at least a first pain index threshold; determine a safety index based at least in part on a second sensed body signal; select a pain treatment regimen based on at least one of said safety index and or a determination that said pain index is above said first pain index threshold; and deliver said pain treatment regimen.

Systems and methods for authenticating users are described herein. One or more inputs including of biometric data, physical trait data, and other data sources may be collected passively when an individual is present in a space. A confidence ratio associated with one or more of the collected inputs may be determined. One or more of the determined confidence ratios may be evaluated together to determine a final confidence ratio for a user, on which an authentication decision is based. An access level may be selected from a plurality of access levels with different access privileges based on the determined confidence ratio. Authentication may be continuous or ongoing.

In one embodiment, a health-monitoring system may access a waist-hip measurement of a user. The system may determine one or more stress-related parameters of the user using one or more computing devices. The system may determine one or more correlations between the waist-hip measurement and the one or more stress-related parameters of the user. The system may provide feedback to the user based on one or more of the one or more stress-related parameters or the determined correlations between the waist-hip measurement and the one or more stress-related parameters.

A virtual reality and augmented reality system configured for meditation applications including a headset comprising an adjustable strap and a display. The headset further includes heating and cooling elements to provide an immersive virtual reality environment to a wearer. The virtual reality system is operable to determine the physiological condition of the wearer and adjust the virtual reality environment based on the physiological condition of the wearer.

A method of classifying a mental state of a user using a computing device, which includes a microphone, a camera, a display, a wireless communication unit, and a processor, and a mental state classification server is provided. The method comprises: by the microphone, detecting ambient noise of the user; by the camera, generating an image by photographing a face of the user; by the processor, checking whether each of ambient noise of the user, ambient brightness of the face of the user obtained from the image, and a face position of the user obtained from the image is suitable for a heart rate variability measurement environment; by the processor, controlling to display on the display images indicating whether each of the ambient noise, the ambient brightness, and the face position is suitable for the heart rate variability.

A measurement unit for measuring a bio-impedance of a body, the measurement unit comprising a current generator circuit, a readout circuit, and a baseline cancellation current circuit, wherein the current generator circuit is configured to amplify a reference current to form a measurement current to be driven through a body to generate a measurement voltage representing the bio-impedance; wherein the readout circuit comprises a Instrumentation amplifier (IA) which has a transconductance stage and a transimpedance stage, wherein the IA is configured to: produce a first current in the transconductance stage, the first current being proportional to the measurement voltage, receive a second current from the baseline cancellation current circuit, produce an output voltage in the transimpedance stage, the output voltage being proportional to a difference between the first current and the second current and representative of the measured bio-impedance; wherein the baseline cancellation current circuit is configured to amplify the reference current by a factor to form the second current and deliver it to the IA, wherein the factor is such that that the absolute value of the difference between the first and the second current is below a threshold such that a baseline of the first current is cancelled by the second current.

Disclosed is a method for the generation of a consciousness indicator for a non-communicating subject, including the steps of generating an auditory stimulation, receiving an electrocardiographic signal of the subject obtained from a recording during the generation of the auditory stimulation, extracting at least one feature from the electrocardiographic signal and deducing a consciousness indicator from an analysis of the electrocardiographic feature.

An ambulatory medical device including a plurality of sensing electrodes and one or more processors operably coupled to the plurality of sensing electrodes is provided. Each sensing electrodes is configured to be coupled eternally to a patient and to detect one or more ECG signals. The one or more processors are configured to receive at least one electrode-specific digital signal for each of the plurality of sensing electrodes, determine a noise component for each of the electrode-specific digital signals, analyze each of the noise components for each of the plurality of sensing electrodes, generate electrode matching information for each sensing electrode of the plurality of sensing electrodes based upon analysis of each of the noise components, determine one or more sensing electrode pairs based upon the electrode matching information, and monitor each of the one or more sensing electrode pairs for ECG activity of the patient.

Provided is a method of evaluating emotional intelligence, the method including evaluating an accuracy of emotional recognition of subjects for the emotional image stimuli, evaluating an accuracy of interpersonal emotional recognition of subjects for a facial image stimulus with a certain emotion, a classification step of presenting a video stimulus of a certain emotion to selected subjects with high accuracy, extracting a heart rate variability (HRV) the subjects, forming a classification model by classification of the video stimulus and machine learning using the HRV through a model generating unit, and evaluating an emotional intelligence of the subject exposed to the image stimulus using the classification model.