Robust estimation of average twitch contraction forces of populations of motor units in humans

Abstract

The characteristics of motor unit force twitch profiles provide important information for the understanding of the muscle force generation. The twitch force is commonly estimated with the spike-triggered averaging technique, which, despite the many limitations, has been important for clarifying central issues in force generation. In this study, we propose a new technique for the estimation of the average twitch profile of populations of motor units with uniform contractile properties. The method encompasses a model-based deconvolution of the force signal using the identified discharge times of a population of motor units. The proposed technique was validated using simulations and tested on signals recorded during voluntary activation. The results of the simulations showed that the proposed method provides accurate estimates (relative error <25%) of the main parameters of the average twitch force when the number of identified motor units is between 5% and 15% of the total number of active motor units. It is discussed that current detection and decomposition methods of multi-channel surface EMG signals allow decoding this relative sample of the active motor unit pool. However, even when this condition is not met, our results show that the estimates provided by the new method are anyway always superior to those obtained by the spike triggered average approach, especially for high motor unit synchronization levels and when a relatively small number of triggers is available. In conclusion, we present a new method that overcome the main limitations of the spike-triggered average for the study of contractile properties of individual motor units. The method provides a new reliable tool for the investigation of the determinants of muscle force.

Keywords: Deconvolution; Force; Motor unit; Twitch; iEMG.