EMG-Informed Neuromusculoskeletal Modelling Estimates Muscle Forces and Joint Moments During Electrical Stimulation.

Abstract

This study implemented an electromyogram (EMG)-informed neuromusculoskeletal (NMS) model evaluating the volitional contributions to muscle forces and joint moments during functional electrical stimulation (FES). The NMS model was calibrated using motion and EMG (biceps brachii and triceps brachii) data recorded from able-bodied participants (n=3) performing weighted elbow flexion and extension cycling movements while equipped with an EMG-controlled closed-loop FES system. Models were executed using three computational approaches (i) EMG-driven, (ii) EMG-hybrid and (iii) EMG-assisted to estimate muscle forces and joint moments. Both EMG-hybrid and EMG-assisted modes were able estimate the elbow moment (root mean squared error and coefficient of determination), but the EMG-hybrid method also enabled quantifying the volitional contributions to muscle forces and elbow moments during FES. The proposed modelling method allows for assessing volitional contributions of patients to muscle force during FES rehabilitation, and could be used as biomarkers of recovery, biofeedback, and for real-time control of combined FES and robotic systems.