EEG relaxation recognition method and device based on frequency domain and phase space

Abstract

The invention discloses an electroencephalogram relaxing degree identifying method and an electroencephalogram relaxing degree identifying device based on frequency domain and phase space. The electroencephalogram relaxing degree identifying method comprises the following steps: acquiring electroencephalogram sequence signals to be processed, and carrying out extracting to obtain signal waves; calculating the energy of the signal waves, calculating the frequency mean square root of the signal waves according to the energy of the signal waves and brain waves, thus obtaining the characteristic quantity in the frequency domain space; according to the signal waves and the electroencephalogram sequence signals to be processed, forming a two-dimensional chart containing the signals, and counting the signal coverage density on each two-dimensional chart, thus obtaining the characteristic quantity in the phase space; and classifying the characteristic quantity in the phase space and the characteristic quantity in the frequency domain space of the electroencephalogram sequence signals to be processed by adopting a pre-trained classifier, and carrying out identification according to the classifying result, thus obtaining the electroencephalogram relaxing degree. With the method and the device, the characteristics in different angles of each brain wave can be comprehensively extracted, and thus the accurate identification for the electroencephalogram relaxing degree is realized.

Description

technical field [0001] The invention relates to the field of relaxation therapy, in particular to a method and device for identifying the degree of relaxation of brain electricity based on frequency domain and phase space. Background technique [0002] Relaxation training is one of the most widely used techniques in behavior therapy. It is a consultation and treatment method established and developed on the basis of psychological experiments. Good curative effects have been achieved in menopausal syndrome and changing bad behavior patterns. [0003] Existing relaxation training mainly includes recording guidance, oral guidance and biofeedback guidance. Among them, the recording instruction method is rigid and unchanged, and cannot change the content according to the state of the trainee; the oral instruction requires high requirements for the object of the oral instruction, and is limited by time and place; the biofeedback instruction is mainly based on EEG feedback, which ...

AI Technical Summary

Problems solved by technology

[0005] The existing feature extraction methods generally can only extract the features of brain waves from a single angle, and the evaluation method is single, which cannot guarantee the accuracy of the classification results

Moreover, the calculation and processing process of the existing feature extraction algorithm is complicated. On the one hand, it increases the requirements for hardware. On the other hand, due to the complicated calculation, the classification result cannot be obtained in time, which affects the effect of relaxation therapy.

Images