Hand motion automatic correction and recognition method based on electroencephalogram signal detection

Abstract

The invention relates to a hand motion automatic correction and recognition method based on electroencephalogram signal detection. The method includes the following steps that 1, ERP components of electroencephalogram signals of a healthy subject are acquired; 2, electroencephalogram signals, in a corresponding brain area, of a patient suffering from serious motion limitation are acquired; 3, a feature calculation time window Fw is set, the peak value, the mean value Mean, the standard deviation SD, the correlation coefficient CORR of collected electrode signals, the autoregression model coefficient AR and the electroencephalogram signal energy E, in the feature calculation time window Fw, of the electroencephalogram signals in the finger motion automatic correction test of the healthy subject are acquired, and the peak value, the mean value Mean, the standard deviation SD, the correlation coefficient CORR of collected electrode signals, the autoregression model coefficient AR and the electroencephalogram signal energy E, in the feature calculation time window Fw, of the electroencephalogram signals in the finger motion automatic correction test of the patient suffering from serious limitation are acquired; 4, classification and recognition are carried out through a binary classification support vector machine, and whether a motion completed by the subject in the hand motion automatic correction test is a correctly-completed automatically-corrected motion is judged. Compared with the prior art, the method has the advantages of being applicable to hand motion automatic correction, accurate in recognition result, broad in application prospect and the like.

Description

Technical field [0001] The invention relates to the field of brain electrical signal detection, in particular to a method for automatically correcting and identifying hand movements based on brain electrical signal detection. Background technique [0002] Human motion detection refers to the analysis and recognition of human motion patterns. It is a hot issue in the field of pattern recognition in recent years. It is widely used in many fields such as human-computer interaction, motion analysis, and medical rehabilitation. The automatic correction of human hand movements is a special and extremely important action behavior. When humans stretch their fingers and other actions, the corresponding hand movements will be adjusted quickly and without intentional control following the sudden change of the target object. , And the brain area of ​​the posterior parietal cortex is considered to be the brain neural basis of the automatic steering behavior mechanism of the hand. Movement tr...

AI Technical Summary

Problems solved by technology

Movement training using automatic correction of hand movements can be used as a means of human limb rehabilitation, and movement detection methods are an important part of the rehabilitation training system. For patients with normal or slightly impaired hand movements, motion capture equipment can be used to detect them Actions, such as infrared tracking, accelerometers, etc., but for the automatic correction of action detection for patients with severely limited hand activities (such as: only fingers can move, etc.), there is still a lack of effective detection methods, which leads to the application of this type of rehabilitation training system crowd greatly reduced

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