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Erschienen in:
2022 | OriginalPaper | Buchkapitel
Heterogeneous sEMG Sensing for Stroke Motor Restoration Assessment
verfasst von : Hongyu Yang, Hui Chang, Jia Zeng, Ruikai Cao, Yifan Liu, Honghai Liu
Erschienen in: Intelligent Robotics and Applications
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Abstract
Stroke is a common global health-care problem that has had serious negative impact on the life quality of the patients. Motor impairment after stroke typically affects one side of the body. The main focus of stroke rehabilitation is the recovery of the affected neuromuscular functions and the achievement of independent body control. This paper proposes a heterogeneous sEMG sensing system for motor restoration assessment after stroke. The 136 sEMG nodes have been heterogeneously distributed to sense both dexterous and lump motion. The 128 sEMG nodes are clustered to acquire high density sEMG data acquisition; the other 8 are sparsely arranged for sEMG data acquisition in lump motion. Preliminary experiments demonstrate that the system outperforms existing similar systems and shows potential for evaluating motor restoration after stroke.