Hybrid sEMG, NIRS and MMG Sensor System

计算机科学 计算机视觉 人工智能
作者
Xuecong Ding,Mian Wang,Weichao Guo,Xinjun Sheng,Xiangyang Zhu
标识
DOI:10.1109/m2vip.2018.8600866
摘要

In recent years, surface electromyography (sEMG) is widely used in human-computer interface (HCI). For example, it is used for prosthetic manipulation to improve the quality of amputees' life. However, sEMG approaches has some drawbacks such as poor robustness of the electrode-skin interface. Near-infrared spectroscopy (NIRS) and mechanomyography (MMG) can also monitor muscle motion. Comparing with approaches that only use sEMG signal, hybrid sEMG, NIRS and MMG sensor system will have better system performance. Investigations about the fusion of sEMG, NIRS and MMG are scant. This paper presents a hybrid sEMG, NIRS and MMG sensor system and puts it into practice. Fuse surface electromyography, near-infrared spectroscopy and mechanomyography acquisition circuits into a compact sensor, which can measure the muscle motion from the modalities of electrophysiology, optics and acoustics. Using the hybrid sensor system, incremental grip force experiment is carried out to explore the relationship between the three signals, blood oxygen metabolism and grip force. And muscle fatigue is carried out in order to explain the phenomenon of muscle fatigue from the perspective of electrophysiology, blood oxygen metabolism and mechanomyography.
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