Adaptive stimulus artifact and ECG reduction in somatosensory evoked potential studies

Somatosensory Evoked Potentials (SEPs) are an important class of bioelectric signals which contain clinically valuable information. However, surface measurements of these signals are often contaminated by the stimulus artifact which, depending on the stimulating and recording measurement characteristics, may obscure some of the information contained in the SEPs. In addition, the SEP recordings on the spinal cord are also influenced by the more powerful ECG interference. The purpose of this paper is two fold-firstly, the authors apply a nonlinear adaptive filter based on the second order Volterra series to iteratively minimize the stimulus artifact. Secondly, a two stage adaptive filter structure is proposed to simultaneously reduce the ECG and stimulus artifact components for spinal cord SEPs. Preliminary experimental results showing the effectiveness of the proposed filter structures are included