A method of evoked EEG extraction based on stochastic gradient adaptive filtering

Abstract

The invention discloses an evoked potential extracting method based on random gradient adaptive filtering. Potential signals repeatedly stimulated are collected through multiple potential measuring systems and comprise mixed signals of spontaneous potentials, spontaneous potentials obtained after stimulation is applied, and evoked potentials, all the mixed signals are superposed for averaging, and an average mixed signal is obtained; the stimulation application time serves as a starting point of counting of extracting time, a section of signal with the length being N is extracted from the average mixed signal to serve as a first main signal, a signal obtained by delaying the first main signal by one time interval serves as a first reference signal, the first main signal and the first reference signal are input into LMS adaptive filters, and first output signals of all channels are obtained; then, the first output signals serve as second reference signals, a section of spontaneous potential with the length being N serves as a second main signal, the second reference signals and the second main signal are put into the LMS adaptive filters, and evoked potentials of all the channels are obtained. By means of the evoked potential extracting method, the evoked potentials high in quality are obtained under the background that adequate priori knowledge is not available, and the number of repeated stimulation times is effective reduced.

Description

technical field [0001] The invention belongs to the field of neural information technology, and relates to a method for extracting induced EEG, in particular to a method for extracting induced EEG based on stochastic gradient (LMS, least mean square) adaptive filtering. Background technique [0002] Spontaneous EEG (spontaneous EEG signal) refers to the spontaneous bioelectrical activity of brain cell groups that is recorded in the scalp using sophisticated electronic equipment without trauma; etc.) will produce induced EEG (induced EEG signal), and induced EEG is considered to be a new window for studying the advanced functions of the human brain. [0003] However, in practical applications, since the evoked EEG is always submerged in strong background noise (including spontaneous EEG, power frequency interference, eye electricity, myoelectricity, and ECG, etc.), its amplitude is only 0.2-20uV, The signal-to-noise ratio is 0-10dB, and the EEG signal itself is random and no...

AI Technical Summary

Problems solved by technology

However, due to the limitations of different methods, there is no recognized single extraction method that has been widely used. At the same time, various types of evoked EEG signals have different characteristics. characteristics to design the corresponding method of use, at this time the acquisition of signal characteristics becomes another problem

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