A method of replicating a mental state of a first subject in a second subject comprising: capturing a mental state of the first subject represented by brain activity patterns; and replicating the mental state of the first subject in the second subject by inducing the brain activity patterns in the second subject.

Disclosed herein are a method and apparatus for analyzing elements inducing motion sickness in VR content. The method includes acquiring objective data based on an experiment using the VR content for measuring VR motion sickness, the experiment being conducted according to a predetermined protocol; acquiring subjective data input from the multiple participants of the experiment; and constructing a database based on the objective data and the subjective data and analyzing the degree of motion sickness induced by each of the content elements of the VR content using statistical information based on the database.

A method for cell stimulation by mechanical energy as well as a method for determining a subject specific set of treatment parameters for acoustic wave stimulation and a method for validating a set of treatment parameters for acoustic wave stimulation. The method for determining a subject specific set of treatment parameters includes generating subject specific data, which includes measuring a geometric property of a body portion, and determining a target field distribution in the body portion. The method for validating a set of treatment parameters for acoustic wave stimulation includes determining a target field distribution of an acoustic field in a body portion, receiving a related set of treatment parameters for at least one transducer, generating a subject specific 3D model of the body portion, and determining a difference between the target field distribution and a field distribution determined in the subject specific 3D model.

A method for cell stimulation by mechanical energy as well as a method for determining a subject specific set of treatment parameters for acoustic wave stimulation and a method for validating a set of treatment parameters for acoustic wave stimulation. The method for determining a subject specific set of treatment parameters includes generating subject specific data, which includes measuring a geometric property of a body portion, and determining a target field distribution in the body portion. The method for validating a set of treatment parameters for acoustic wave stimulation includes determining a target field distribution of an acoustic field in a body portion, receiving a related set of treatment parameters for at least one transducer, generating a subject specific 3D model of the body portion, and determining a difference between the target field distribution and a field distribution determined in the subject specific 3D model.

A method for classifying or categorizing a polysomnography recording into defined sleep tags.

A method for classifying or categorizing a polysomnography recording into defined sleep tags.

Disclosed is a process for identifying and extracting pain-related electroencephalogram (EEG) signals. The process comprises receiving, from one or more trials, EEG data for each trial; determining a current density for each signal; estimating the current density for a set of neural activity regions of interest, based on the computed current density; and computing at least one spectrum characteristic for each trial based on the estimated current density. Thus mean and variance of changes in the EEG data between EEG data labeled as being indicative of a pain state and EEG data labeled as being indicative of a non-pain state, for each neural activity region of interest can be calculated, and pain-related EEG signals can be identified based on at least one a region of interest at which the variance is below a predetermined threshold.

The system of neurorehabilitation and the method of neurorehabilitation belongs to the medical field, specifically to neurology, and can be used as a system and method of neurorehabilitation during motor rehabilitation of patients after a stroke in various phases, as well as during the rehabilitation of patients with other diseases and disorders of the central nervous system. The objective of the claimed invention is the motor (movement) rehabilitation of patients after stroke and other diseases of the central nervous system that cause motor deficits in the limbs. The technical result of the invention is to increase the effectiveness of rehabilitation, including during early and late rehabilitation period of stroke and other diseases and disorders of the central nervous system through the use of the system and method of neurorehabilitation and methods of this invention, which stimulate the restoration of mobility of paralyzed limbs by forming neural biofeedback connections between the patient's intention to move the limb and its implementation.

The system of neurorehabilitation and the method of neurorehabilitation belongs to the medical field, specifically to neurology, and can be used as a system and method of neurorehabilitation during motor rehabilitation of patients after a stroke in various phases, as well as during the rehabilitation of patients with other diseases and disorders of the central nervous system. The objective of the claimed invention is the motor (movement) rehabilitation of patients after stroke and other diseases of the central nervous system that cause motor deficits in the limbs. The technical result of the invention is to increase the effectiveness of rehabilitation, including during early and late rehabilitation period of stroke and other diseases and disorders of the central nervous system through the use of the system and method of neurorehabilitation and methods of this invention, which stimulate the restoration of mobility of paralyzed limbs by forming neural biofeedback connections between the patient's intention to move the limb and its implementation.

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.