Simultaneous estimation of grip force and wrist angles by surface electromyography and acceleration signals

Abstract

In myoelectric control, simultaneous and proportional (SP) control of multiple degrees of freedom (DOFs) can realize a high level of dexterity. This study proposed a new control scheme that simultaneously estimates continuous grip force and wrist angles using a combination of surface electromyography (sEMG) and acceleration (ACC) signals. Four popular EMG features were utilized to study the regression accuracy. Nine intact subjects were recruited. They performed six force-position varying movements which involved simultaneous activation of four DOFs (wrist flexion/extension, ulnar/radial deviation, pronation/supination, and grip). The estimation performance was evaluated by the Pearson Correlation Coefficient (cc). The highest cc value was 92.12 ± 1.51%, 96.68 ± 1.16%, and 97.18 ± 0.69% for the sEMG-only, ACC-only, and multi-modal methods, respectively. Results indicate that the multi-modal approach can significantly improve regression accuracy of concurrent grip force and wrist angles, especially in pronation/supination. Besides, the multi-modal method showed higher robustness when the available number of sensors decreased and better generalization ability between movements. In conclusion, the proposed multi-modal approach has the potential for SP control of future hand prostheses.