A method to improve the estimation of conduction velocity distributions over a short segment of nerve

Accurate, noninvasive determination of the distribution of conduction veloc ities (DCV) among fibers of a peripheral nerve has the potential to improve both clinical diagnoses of pathology and longitudinal studies of the progr ess of disease or the efficacy of treatments. Current techniques rely on lo ng distances of propagation to increase the amount of temporal dispersion i n the compound signals and reduce the relative effect of errors in the forw ard model. The method described in this paper attempts to reduce errors in DCV estimation through transfer function normalization and, thereby, elimin ate the need for long segments of nerve, Compound action potential (CAP) si gnals are recorded from several, equally spaced electrodes in an array span ning only a 10-cm length of nerve. Relative nerve-to-electrode transfer fun ctions (NETF's) between the nerve and each of the array electrodes are esti mated by comparing discrete Fourier transforms of the array signals, NETF's are normalized along the array so that waveform differences can be attribu ted to the effects of temporal dispersion between recordings, and more accu rate DCV estimates can be calculated from the short nerve segment. The meth od is tested using simulated and real CAP data, DCV estimates are improved for simulated signals. The normalization procedure results in DCV's that qu alitatively match those from the literature when used on actual CAP recordi ngs.