Application of multi-adaptive filter based on radial basis function neural network for real-time somatosensory evoked potential monitoring / 国际生物医学工程杂志

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.