Parameter setting method and device for electroencephalogram neural feedback training, and related medium

Abstract

The invention discloses a parameter setting method and device for electroencephalogram neural feedback training, and a related medium. The parameter setting method comprises the following steps of: obtaining the resting-state electroencephalogram signal and the resting-state functional magnetic resonance data of a subject; calculating individual alpha oscillation peak frequency corresponding to the resting-state electroencephalogram signal; calculating the standardized clustering coefficient of an individual functional brain network topology attribute corresponding to the resting-state functional magnetic resonance data; and before the electroencephalogram feedback training of frontal lobe alpha asymmetry is carried out, setting an alpha frequency band parameter used for extracting feedback signals on the basis of the individual alpha oscillation peak frequency, and setting the training difficulty parameter of the electroencephalogram neural feedback on the basis of the standardized clustering coefficient of a resting-state functional magnetic resonance brain network. According to the parameter setting method, alpha frequency band parameters and the training difficulty parameters are calculated by collecting the resting-state electroencephalogram signal and the resting-state functional magnetic resonance data of the subject, so that better parameters are set for the electroencephalogram neural feedback training, and the subject can be better helped to achieve a better training effect.

Description

Technical field [0001] The present invention relates to computer software technology, and particularly relates to a method for setting parameters of neural EEG feedback training, and the apparatus associated media. Background technique [0002] EEG is a neural feedback technique of the subject by collecting EEG signals through real-time processing after a visual, audible, or other forms of real-time feedback to the subject, so that the subject can be adjusted autonomously according to the feedback and coaching technical brain activity. EEG neurofeedback technology as a non-drug, non-invasive interventions, with a safe non-invasive, economical and other advantages, has been widely used to improve the cognitive abilities of healthy individuals, as well as a variety of rehabilitation of mental illness. Due to the influence of biological, psychological and social environment and many other factors, caused some people appear depressed, pessimistic symptoms of depression, which may lea...

AI Technical Summary

Problems solved by technology

However, the current technical solution lacks personalized design, and does not set the parameters and task difficulty of emotion regulation EEG feedback training according to the individual differences of subjects' EEG signals and the learning effect of feedback training, which is not conducive to the optimization of training effects

Images