Extracting deep brain evoked potentials based on EEPS-BSS algorithm
Ruxiang Xu · Tianjin Gongye Daxue xuebao · 2013
Deep brain evoked potentials play an important role in exploring the mechanism of nerve stimulator to treat diseases.In clinical treatment,there is a problem defined as underdetermined blind source separation that the number of collect electrodes is fewer than the source signal′s.To solve this problem,an improved blind source separation without a priori knowledge is proposed in underdetermined case.In connection with extracting deep brain evoked potentials from single channel,the empirical mode decomposition is used for stratifying the observed signals,and the observed signals are expanded according to the signals that reconstructed in certain rules.Simulation and measured data show that the novel method could effectively achieve extraction of weak evoked potentials from signals under low signal-to-noise ratio.Compared to unseparated,the cross-correlation coefficients among the respective separated signals are dropped significantly,accordingly,the validity of the algorithm that extracts evoked potentials is confirmed.