Abstract: A method, device and recording medium for providing therapy through brain wave data analysis are provided. The method by which a computing device provides therapy through brain wave data analysis, according to various embodiments of the present invention, comprises the steps of: acquiring brain wave data of a user; determining a therapy protocol on the basis of the acquired brain wave data; and using the determined therapy protocol to provide therapy to the user.

Abstract: Provided are a digital phenotyping method, apparatus, and recording medium for drug response classification and prediction. A digital phenotyping method for drug response classification and prediction that is performed by a computing device according to various embodiments of the present invention includes acquiring biometric data of a patient, and analyzing the acquired biometric data using a disease diagnostic model to perform a multiple disease diagnosis on the patient, in which the disease diagnostic model includes a plurality of diagnostic models that independently perform diagnoses of each of multiple distinct diseases based on the acquired biometric data.

Abstract: The present disclosure relates to an EEG measuring device which is in close contact with a head of a subject while having an adjustable size to fit the head of the subject.

Abstract: Disclosed is a computer program stored in a computer-readable storage medium for achieving the above-described objects. When the computer program is executed by one or more processors, the computer program causes the one or more processors to perform the following operations of generating video data for diagnosing a health condition and a pathological symptom on the basis of a biosignal. The operations include receiving a biosignal of a user, preprocessing the biosignal to generate a plurality of pieces of video sub-data, and selecting at least two of the plurality of pieces of video sub-data to generate one or more pieces of video data.

Abstract: Provided is a cognitive impairment diagnosis method including: receiving an electroencephalogram signal of a user by a cognitive impairment diagnosis device; preprocessing the electroencephalogram signal by the cognitive impairment diagnosis device; extracting features, by the cognitive impairment diagnosis device, from the electroencephalogram signal by using a brain connectivity-based analysis method; and outputting cognitive impairment diagnosis information of the user by the cognitive impairment diagnosis device, on the basis of features having a causal relationship with the cognitive impairment diagnosis information, among the extracted features.

Abstract: Provided is a method for classifying severe cognitive impairment patients by analyzing electroencephalogram (EEG) data. The method of classifying severe cognitive impairment patients by analyzing EEG data includes a brainwave collection step of collecting EEG data on a plurality of users, a first classification step of classifying the plurality of users into a severe cognitive impairment group or a non-severe cognitive impairment group by analyzing the collected EEG data, a second classification step of classifying users included in the non-severe cognitive impairment group into a normal group or an amnestic mild cognitive impairment (aMCI) group, and a third classification group of classifying users included in the normal group into a within normal limits (WNL) group or a preclinical Alzheimer's disease (AD) group and classifying users included in the aMCI group into a non-AD MCI group or a prodromal AD group.

Abstract: Disclosed is a computer program stored in a computer-readable storage medium for achieving the above-described objects. When the computer program is executed by one or more processors, the computer program causes the one or more processors to perform the following operations of generating video data for diagnosing a health condition and a pathological symptom on the basis of a biosignal. The operations include receiving a biosignal of a user, preprocessing the biosignal to generate a plurality of pieces of video sub-data, and selecting at least two of the plurality of pieces of video sub-data to generate one or more pieces of video data.

Abstract: Provided is a cognitive impairment diagnosis method including: receiving an electroencephalogram signal of a user by a cognitive impairment diagnosis device; preprocessing the electroencephalogram signal by the cognitive impairment diagnosis device; extracting features, by the cognitive impairment diagnosis device, from the electroencephalogram signal by using a brain connectivity-based analysis method; and outputting cognitive impairment diagnosis information of the user by the cognitive impairment diagnosis device, on the basis of features having a causal relationship with the cognitive impairment diagnosis information, among the extracted features.