Estimation of motor unit firing statistics from surface EMG

Abstract

We present a method for estimating the mean and standard deviation of inter-pulse intervals (IPIs) of individual motor unit action potential (MUAP) trains. Through a weighted matching between the observed IPI probability density function and the modeled function, the firing parameters are estimated. The weighted function is used to approximate the validity of IPI data so that all valid information provided by IPI data are utilized as far as possible. For this reason, the method can provide reliable estimations even the MUAP trains are extracted with significant errors. Thus, this method is very useful for estimating the firing statistics of surface EMG where the individual MUAP trains are difficult to be accurately identified.