Graph-Driven Simultaneous and Proportional Estimation of Wrist Angle and Grasp Force via High-Density EMG

• Published in: IEEE journal of biomedical and health informatics Vol. 28; no. 5; pp. 2723 - 2732
• Main Authors: Li, Dongxuan, Kang, Peiqi, Yu, Yang, Shull, Peter B.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.05.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adult; Biomechanical Phenomena - physiology; Correlation coefficient; Correlation coefficients; Degrees of freedom; Electrodes; Electromyography; Electromyography - methods; Feature extraction; Female; Force; Grasping force; Hand Strength - physiology; High density; High-density electromyography (HD-EMG); Humans; Interfaces; Kinematics; Kinetic theory; Male; Muscles; Myoelectricity; Proportional control; Prostheses; Prosthetics; Quality of life; Signal Processing, Computer-Assisted; simultaneous and proportional control (SPC); spatial-temporal model; Wrist; Wrist - physiology; Young Adult
• ISSN: 2168-2194; 2168-2208; 2168-2208
• DOI: 10.1109/JBHI.2024.3373432

Myoelectric prostheses are generally unable to accurately control the position and force simultaneously, prohibiting natural and intuitive human-machine interaction. This issue is attributed to the limitations of myoelectric interfaces in effectively decoding multi-degree-of-freedom (multi-DoF) kinematic and kinetic information. We thus propose a novel multi-task, spatial-temporal model driven by graphical high-density electromyography (HD-EMG) for simultaneous and proportional control of wrist angle and grasp force. Twelve subjects were recruited to perform three multi-DoF movements, including wrist pronation/supination, wrist flexion/extension, and wrist abduction/adduction while varying grasp force. Experimental results demonstrated that the proposed model outperformed five baseline models, with the normalized root mean square error of 13.2% and 9.7% and the correlation coefficient of 89.6% and 91.9% for wrist angle and grasp force estimation, respectively. In addition, the proposed model still maintained comparable accuracy even with a significant reduction in the number of HD-EMG electrodes. To the best of our knowledge, this is the first study to achieve simultaneous and proportional wrist angle and grasp force control via HD-EMG and has the potential to empower prostheses users to perform a broader range of tasks with greater precision and control, ultimately enhancing their independence and quality of life.