sEMG-based hand posture recognition and visual-feedback training
J. M. Kim, B. M. Koo, S. M. Yang, Y. J. Nam, Y. H. Kim
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AbstractsEMG-based recognition system provides the intuitive and accurate classification of various gestures and useful for human-computer interaction. Especially, recognition of hand postures is often suggested as the interaction protocol of rehabilitation systems or robotic orthosis for the elderly and disabled [1]. However, the variability of the sEMG signal was caused by the individual differences and the change of the force or proficiency. In this study, the hand posture recognition algorithm was developed using sEMG sensors, and the visual-feedback training was performed to improve the classification performance.Keywords: sEMG, recognition, hand posture, amputee, visual feedback training
J. M. Kim, B. M. Koo, S. M. Yang, Y. J. Nam, Y. H. Kim (2022). sEMG-based hand posture recognition and visual-feedback training. Gerontechnology, 21(s),1-1
https://doi.org/10.4017/gt.2022.21.s.656.pp1