Application of multi-adaptive filter based on radial basis function neural network for real-time somatosensory evoked potential monitoring
10.3760/cma.j.issn.1673-4181.2012.03.003
- VernacularTitle:径向基函数网络在体感诱发电位实时监测中的应用
- Author:
Hongyan CUI
;
Xiaobo XIE
;
Shengpu XU
;
Chongfei SHEN
;
Yong HU
- Publication Type:Journal Article
- Keywords:
Somsatosensory evoked potential;
Aadial basis function;
Adaptive signal enhance;
Adaptive noise canceller;
Multi-adaptive filter,Least mean square error algorithm
- From:
International Journal of Biomedical Engineering
2012;35(3):137-141
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo design multi-adaptive filter based on radial basis function (MAF-RBF) for efficiently extracting somatosensory evoked potential (SEP) in real-time SEP monitoring.MethodsWith 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.ResultsIn 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.ConclusionWith 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.
