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  • Title: Optimal filtering of whole nerve signals.
    Author: Jezernik S, Grill WM.
    Journal: J Neurosci Methods; 2001 Mar 30; 106(1):101-10. PubMed ID: 11248345.
    Abstract:
    Electroneurographic recordings suffer from low signal to noise (S/N) ratios. The S/N ratio can be improved by different signal processing methods including optimal filtering. A method to design two types of optimal filters (Wiener 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, bladder, and rectal mechanoreceptors. The S1 spinal root recordings were also filtered using various band-pass (BP) filters with different cut-off frequencies, since the frequency responses of the Wiener and Matched filters had a band-pass character. The mean increase in the S/N ratio across all recordings was 54, 89, and 85% for the selected best Wiener, Matched, and band-pass filters, respectively. There were no statistically significant differences 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 selectivity of the recordings for different sensory modalities. This might be important when recording nerve activity from a mixed nerve innervating multiple end-organs to increase the modality selectivity for the nerve fibers of interest. The mean Modality Selectivity Indices (MSI) over different receptor types 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). Improving the S/N ratio and modality selectivity of neurographic recordings is an important development to increase the utility of neural signals for understanding neural function and for use as feedback or control signals in neural prosthetic devices.
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