A Home-based Dual-mode Upper Limb Rehabilitation System: Teleoperation Mode and Bilateral Mode with sEMG and IMU

• Published in: IEEE journal of biomedical and health informatics Vol. PP; pp. 1 - 14
• Main Authors: Li, He, Guo, Shuxiang, He, Ruijie, Wang, Bin, Ding, Mingchao
• Format: Journal Article
• Language: English
• Published: United States IEEE 14.07.2025
• Subjects: Cloud-based telerehabilitation; Exoskeletonassisted rehabilitation; Exoskeletons; Force; Force feedback; Human-robot interaction; Inertial Measurement Unit (IMU); Limbs; Main-secondary; Motors; Servers; Shoulder; Surface Electromyography (sEMG); Training; Upper limb hemiplegia; Wrist
• ISSN: 2168-2194; 2168-2208; 2168-2208
• DOI: 10.1109/JBHI.2025.3588404

Upper limb hemiplegia is a common functional disorder among stroke patients, significantly affecting their quality of life. To address this issue, robot-assisted upper limb rehabilitation training has emerged as a new therapeutic approach, breaking through time and space limitations of traditional rehabilitation. Based on the above, a home-based dual-mode upper limb rehabilitation system is built, including teleoperation mode based on a cloud server and bilateral mode with fusion of Surface Electromyography (sEMG) and Inertial Measurement Unit (IMU). In the telerehabilitation mode, patients can receive professional guidance and regular training at home, greatly enhancing the accessibility of rehabilitation services. The experiments with the master side in Beijing City (China) and the slave side in three different cities are conducted through a cloud server. The slave side is controlled by the master side, and the contact force is sent back to the master side. In the bilateral mode, the intention of continuous movements across subjects can be accurately predicted via the fusion of sEMG and IMU, improving the naturalness of human-robot interaction. In the subject-independent modeling, the Root Mean Square Error (RMSE) under fusion showed a relative decrease of 15.0329% (p <10 -4 ) compared to IMU data alone, and a significantly greater reduction of 61.9376% (p <10 -4 ) in comparison with sEMG data alone. Robot-assisted upper limb exoskeleton, cloud-based teleoperation and bilateral training based on sEMG and IMU collectively form a new rehabilitation system, representing part of the future rehabilitation trend.