Evaluation of HD-sEMG descriptor sensitivity to changes of anatomical and neural properties with aging : A simulation study

Abstract

Background and objectivesA reliable evaluation of anatomical and neural muscle properties and its effects on the electrical signals measured at the skin surface aims to develop a medical non-invasive aid-diagnosis tool assisted by model and personalized to the patient. This tool will be dedicated to understand and evaluate muscle diseases and aging. MethodsWe perform a new Robust Morris Screening Method: RMSM in Douania et al. (2023), to assess the impact of muscle anatomy (model inputs) uncertainties and variations on a simulated HD-sEMG signals (model outputs). The model describes a complex neuromuscular system simulating HD-sEMG (high density surface electromyography) signals generated from motor units electrical sources of a striated muscle: the Biceps Brachii (BB). Two subjects categories and two contractions levels are studied: young men (YM) and old men (OM) at low and high contraction (LC = 20% of MVC and HC = 60% of MVC). A 33 features in time and frequency domains are used as model outputs. ResultsWe have demonstrated that the neuromuscular model is able to deliver HD-sEMG signals sensitive to the same anatomical and neural muscle factors as in real cases. Time domain features are mainly sensitive to muscle thickness, conduction velocity of fibers, electrode locations (at HC), number of motor units, and to the number of slow and fast fibers for young and aged categories respectively. Frequency domain feature are sensitive mainly to the conduction velocity of fibers and muscle conductivities (no significant differences between YM and OM are observed). ConclusionThis result is important, it allows to obtain simulated HD-sEMG signals close to experimental ones with low cost and in reduced time. However, for a reliable evaluation of muscle aging, the neuromuscular model should be enhanced to better describe structural, morphological, and functional age-related phenomena.