Optimal filtering of whole nerve signals

Electroneurographic recordings suffer from low signal to noise (S/N) ratios . The S/N ratio can be improved by different signal processing methods incl uding optimal filtering. A method to design two types of optimal filters (W iener and Matched filters) was developed for use with neurographic signals, and the calculated filters were applied to nerve cuff recordings from the cat S1 spinal root that were recorded during the activation of cutaneous, b ladder, and rectal mechanoreceptors. The S1 spinal root recordings were als o filtered using various band-pass (BP) filters with different cut-off freq uencies, since the frequency responses of the Wiener and Matched filters ha d a band-pass character. The mean increase in the S/N ratio across all reco rdings was 54, 89, and 85% for the selected best Wiener. Matched, and band- pass filters, respectively, There were no statistically significant differe nces between the performance of the selected filters when all three methods were compared. However, Matched filters yielded a greater increase in S/N ratio than Wiener filters when only two filtering techniques were compared. All three filtering methods have in most cases also improved the selectivi ty of the recordings for different sensory modalities. This might be import ant when recording nerve activity from a mixed nerve innervating multiple e nd-organs to increase the modality selectivity for the nerve fibers of inte rest, The mean Modality Selectivity Indices (MSI) over different receptor t ypes and for the same selected filters as above were 1.12, 1.27, and 1.29, respectively, and indicate increases in modality selectivity (MSI > 1). Imp roving the S/N ratio and modality selectivity of neurographic recordings is an important development to increase the utility of neural signals for und erstanding neural function and for use as Feedback or control signals in ne ural prosthetic devices. (C) 2001 Published by Elsevier Science B.V.