Application of LMS adaptive filters to signal estimation for tracking transient latency changes in short latency somatosensory evoked potentials

The noisy character of somatosensory evoked potential (SEP) signals acquired during human whole-body indirect impact acceleration experiments at the Naval Biodynamics Laboratory presents problems to researchers monitoring transient SEP latency changes. Standard ensemble averaging has proven to be an inadequate technique for this purpose. Least-mean-square (LMS) adaptive filtering is an effective means of improving the signal character of noisy signals. This study applies various EMS adaptive filters to simulated evoked potential data in order to ascertain the behavior of these filters under various noise and filter parameter conditions