Application of multi-adaptive filter based on radial basis function neural network for real-time somatosensory evoked potential monitoring
Hongyan Cui, Xiaobo Xie, Shengpu Xu, Chongfei Shen, Yong Sheng Hu · Guoji shengwu yixue gongcheng zazhi · 2012
Objective To design multi-adaptive filter based on radial basis function (MAF-RBF) for efficiently extracting somatosensory evoked potential (SEP) in real-time SEP monitoring.Methods With the optimization of important parameters that influence the performance of radial basis function neural network,the performance of extracting SEP was compared to that of a multi-adaptive filter (MAF),which developed from the combination of well-developed adaptive noise canceller and adaptive signal enhancer.Results In this simulation study,the outputs of MAF-RBF showed a similar waveform with SEP template signals,and a smoother waveform than the.output of MAF.Conclusion With appropriate parameter values,MAF-RBFNN is able to extract the latency and amplitude of SEP from the extremely noisy background rapidly and reliably without averaging. Key words: Somsatosensory evoked potential; Aadial basis function; Adaptive signal enhance; Adaptive noise canceller; Multi-adaptive filter,Least mean square error algorithm