Kim, Minjae Kim, Keehoon Chung, Wan Kyun 2024-01-19T21:05:15Z 2024-01-19T21:05:15Z 2021-09-04 2018-12 1534-4320 https://pubs.kist.re.kr/handle/201004/120635 Surface electromyography (sEMG) measurements have demonstrated the potential to recognize complex hand motions. In addition, sEMG enables natural recognition without disturbing movements, and thus, can be used in various fields such as teleoperation, assistant robots, and prosthetic hands. However, sEMG signals highly depend on electrode placements due to the complex muscle structures. A shift of the electrode can lead to inconsistent signal measurement. Thus, sEMG-based recognition is not practical for applications that require long-term and repeated usage. This paper proposes compensation of sEMG interface rotation for robust motion recognition. Once the relationship between sEMG signals and motions is trained, additional training for different electrode configurations is not necessary for a band-type interface. The proposed process is simple and fast. The interface rotation can be compensated for by performing only a single motion for approximately 2 s. The single motion for compensation is dependent on the muscle properties of the user. Generally, ulnar deviation may work. To demonstrate the proposed compensation, recognition of five hand motions is conducted. The experimental results indicate that the proposed compensation can cover the overall range of rotation. In addition, the proposed compensation is validated with a transradial amputee. English IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC PROPORTIONAL MYOELECTRIC CONTROL STRATEGY Simple and Fast Compensation of sEMG Interface Rotation for Robust Hand Motion Recognition Article 10.1109/TNSRE.2018.2878439 1 IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, v.26, no.12, pp.2397 - 2406 IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 26 12 2397 2406 scie scopus 000452440100019 Engineering, Biomedical Rehabilitation Engineering Rehabilitation Article PROPORTIONAL MYOELECTRIC CONTROL STRATEGY Surface electromyography sEMG signal reconstruction sEMG model