Severe depression identification system and application based on brain-computer interface and deep learning

Abstract

A severe depression identification system and application based on brain-computer interface and deep learning, including a portable EEG acquisition device, an EEG analysis system, and a classification recognition system. The portable EEG acquisition device collects EEG from the brain of a subject After completing the collection process of electrical signals, the EEG analysis system analyzes the collected EEG EEG signals and establishes a multi-layered brain complex network. The classification recognition system accurately identifies the brain state on the basis of the multi-layered brain complex network and completes the identification. process, after a specified number of collection and identification processes, the system will give the possibility that the subject is a normal person or a severe depression, and then complete the identification task for patients with severe depression. The present invention can achieve a higher recognition accuracy rate of severe depression, can realize a rapid and accurate system for preliminary identification of patients with severe depression, and further provides a basis for later diagnosis.

Description

technical field [0001] The present invention relates to a severe depression identification system. In particular, it relates to a major depression identification system and application based on a brain-computer interface and deep learning. Background technique [0002] Major depressive disorder is a global, serious mental illness. Unlike mild mood changes, major depressive disorder has a higher risk of serious health problems. Research shows that the prevalence of major depressive disorder in Chinese children and adolescents is about 1.3%, which brings a huge burden to adolescent mental health work. In addition, the suicide rate of patients with major depressive disorder was significantly higher than that of healthy people. Therefore, accurate and timely identification of patients with severe depression is of great significance to scientific research and the development of human society. At present, more and more attention has been paid to the identification of patients ...

AI Technical Summary

Problems solved by technology

[0004] The brain is a complex system, and the EEG signal has the characteristics of nonlinearity and unsteady state, so it is difficult to capture its effective characteristic information by using traditional signal processing theory

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