SEMG-Based Complex Human In-Hand Motion Recognition for Dexterous Robotic Manipulation

• Published in: IEEE access Vol. 13; pp. 51042 - 51053
• Main Authors: Xue, Yaxu, Ru, Feifei, Du, Haojie, Yin, Kaiyang, Li, Pengfei, Ju, Zhaojie
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Bionics; Brain modeling; Classification algorithms; Complexity; Control methods; Data analysis; Decision trees; Electromyography; ensemble empirical mode decomposition; Feature extraction; gradient boosting decision tree; Hand (anatomy); Hands; human in-hand motion; Human motion; Machine learning; Motion perception; multivariate autoregressive; Noise; Prediction algorithms; Recognition; Robot sensing systems; SEMG; Signal processing; Signal processing algorithms; Signal quality

Surface electromyography (SEMG) signals have emerged as a natural and intuitive control method, offering significant advantages for the operation of bionic hands. This technology has been widely applied in various fields, including medical rehabilitation and human-computer interaction. This paper pr...