Hirose G, Tsuchitani Y, Huang J
Electroencephalogr Clin Neurophysiol. 1986 Feb;63(2):192-202. doi: 10.1016/0013-4694(86)90013-1.
Nerve conduction velocity (NCV) measurements have been widely used to assess the electrophysiological properties of peripheral nerves and to detect neuropathies at a subclinical stage. Conventional NCVs are usually expressed as the NCV for the fastest conducting fibers and the current standard methods do neither supply information about slower conducting fibers, nor detect information about individual fiber groups. We present a new analytical method, to estimate the distribution of conduction velocity (DCV), based upon spectral analysis of the wave forms of two compound action potentials (CAPs) recorded by surface electrodes from a nerve bundle. If the spectra of the two CAPs recorded at two different sites in response to supramaximal electrical stimulation at distances l1 and l2 are given as G11(omega) and G12(omega), the spectral representation of the latency distribution P12(omega) for the propagation distance l2 is expressed as follows: P12(l1 omega/l2) = [G11(omega)/G12(omega)]P12(omega), where omega is an angular frequency. We developed an algorithm that computes P12(omega) successively without using iterative calculation methods. Our estimation method is theoretically based upon the principle that the CAPs are recorded monopolarly to estimate the DCV, but in practical use, it is almost impossible to obtain appropriate CAP wave forms by monopolar recording methods, because of stimulation and muscle artefacts. In order to evaluate the efficacy of bipolarly recorded CAP wave forms for this computation algorithm, we examined the two CAP wave forms reconstructed by simulation techniques. We found that the difference between the monopolar and bipolar recording methods was reflected in the wave form extracted for the single fiber action potentials but not in the latency distribution. The distance between the bipolarly recorded electrodes (1.5 cm was the minimal distance used) did not affect the reproducibility of estimating the latency distribution. This new method is non-invasive and could be used for evaluation of peripheral neuropathies.
