Real-Time Finger Force Estimation from Surface Electromyography (sEMG) and a Musculoskeletal Model

Abstract

This paper presents a methodology of the thumb-tip force estimation for applications in the force control of telerobotic hand manipulator. Among five fingers, thumb was selected for the force estimation because of its primary fuction of hand. Phenomenological muscle model named the Hill-based muscle model was used to estimate thumb-tip force under four different configurations to investigate the potential for estimations under conditions in which the thumb configuration changes. To overcome the difficulties in measurement of muscle activities and the complex musculoskeletal structure of thumb, the surface electromyogram (sEMG) signals of the muscles near surface were measured and converted to muscle activation information and the activations of deep muscles were inferred from the ratios from earlier study. The muscle length of each contributed muscle was obtained by using motion capture system and musculoskeletal modeling software packages. Once muscle forces were calculated, thumb-tip force was estimated based on the mapping model from the muscle force to thumb-tip force. The propsoed method was compared with the conventional linear proportional method using sEMG for evaluation. The experimental results showed proposed method had acceptable errors and higher corrleation values than linear regression method in every experimental cases. Therefore, it can be considered that proposed method is feasible in the real-time force control of a telerobotic finger.