Attention rehabilitation training and evaluation method based on spectral entropy

Abstract

The invention relates to an attention rehabilitation training and evaluation method based on spectral entropy. The method comprises the step S1 of collecting an EEG related potential of a rehabilitation training object to a simple speech attention task and preprocessing the EEG data; the step S2 of calculating the power spectral density of the preprocessed EEG data; the step S3 of calculating thespectral entropy value; the step S4 of utilizing a support vector machine to train attention EEG signals in the rehabilitation training with the spectral entropy value as the characteristic to obtaina classification model; the step S5 of collecting the resting state data before training of the rehabilitation training object; the step S6 of conducting rehabilitation training on the rehabilitationtraining object to classify the EEG data during the rehabilitation training process in real time; the step S7 of feeding back based on a real-time classification result and giving corresponding prompts to help pay attention; the step S8 of collecting the resting state data after the training of the rehabilitation training object; the step S9 of judging the rehabilitation training effect accordingto the change of the spectral entropy value collected by the resting state data before and after the training.

Description

technical field [0001] The invention belongs to the technical field of attention rehabilitation and relates to a spectral entropy-based attention rehabilitation training and evaluation method. Background technique [0002] At present, the main treatment methods for ADHD include drug therapy and non-drug therapy. The central nervous system stimulant represented by methylphenidate is the most commonly used drug, with fast onset and significant effect, but due to the short action time of the drug and its side effects on patients, more and more patients prefer to choose non-drug treatment. Among many non-drug treatments, EEG biofeedback therapy has gradually become the main direction for the treatment of attention-deficit patients due to its advantages of safety, effectiveness, long-lasting efficacy, and no side effects. A large number of clinical trials have proved that the efficacy of EEG biofeedback therapy in the treatment of attention deficit is equivalent to that of cent...

AI Technical Summary

Problems solved by technology

[0005] Some patents now mention the use of BCI to do rehabilitation training for patients with attention deficits, but almost no one pays attention to the evaluation index of the rehabilitation training effect

For example, a system that uses EEG signals to test and train human brain attention in real time (application number: CN 107024987), but this patent focuses on the construction of the system, and does not propose in detail the selection of classification features in attention rehabilitation training. , and no evaluation of treatment effects

The patent based on EEG signal feature extraction and its monitoring and extraction system (application number: CN 108236464) also mentions the use of entropy as a feature for attention rehabilitation training, but the method of mainly using information entropy is different from the spectral entropy in the present invention, and This invention also does not provide the evaluation index of rehabilitation training effect

Images