EMG-Based Volitional Torque Estimation in Functional Electrical Stimulation Control

• Published in: 2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES) pp. 171 - 176
• Main Authors: Kavianirad, Hossein, Endo, Satoshi, Keller, Thierry, Hirche, Sandra
• Format: Conference Proceeding
• Language: English
• Published: IEEE 07.12.2022
• Subjects: Adaptive filters; closed-loop control; Electromyography; EMG; Estimation; FES; human-in-the-loop; human-machine interaction; Iron; Muscles; Nonlinear filters; rehabilitation; Torque
• DOI: 10.1109/IECBES54088.2022.10079376

Functiona1 electrical stimulation (FES) applies electrical pulses to muscle fibers through the skin for assisting functional movements in patients with motor disability. Muscle activity feedback such as volitional Electromyography (vEMG) can optimize the performance of the FES system in both rehabilitation or activity of daily living (ADL), however, artifacts caused by simultaneous use of FES and EMG on the same muscles contaminate the EMG signal. This paper, using an adaptive filter, aims to investigate the estimation of the volitional torque from filtered vEMG. Based on this estimation, the usability and performance of the adaptive filter for estimating volitional torque are studied on 5 healthy participants and we show that this filter can be used for volitional torque estimation. In the next step, it is shown how this map can be used in closed-loop FES control for estimating volitional torque.