文献类型：期刊文献

英文题名：A Soft Exoskeleton Glove for Hand Bilateral Training via Surface EMG

作者：Chen, Yumiao[1];Yang, Zhongliang[2];Wen, Yangliang[2]

机构：[1]East China Univ Sci & Technol, Sch Art Design & Media, Shanghai 200237, Peoples R China;[2]Donghua Univ, Coll Mech Engn, Shanghai 201620, Peoples R China

年份：2021

卷号：21

期号：2

起止页码：1

外文期刊名：SENSORS

收录：;EI(收录号：20210409810612);WOS:【SCI-EXPANDED(收录号:WOS:000611722800001)】；

基金：This study was partly supported by National Natural Science Foundation of China (No. 51905175), Shanghai Pujiang Talent Program (No. 2019PJC021), the Fundamental Research Funds for the Central Universities (Nos. 50321171922001 and 2232018D3-27) and the Zhejiang Provincial Key Laboratory of integration of healthy smart kitchen system (No. 2014E10014).

语种：英文

外文关键词：exoskeleton; surface electromyography; hand motion recognition; bilateral training

摘要：Traditional rigid exoskeletons can be challenging to the comfort of wearers and can have large pressure, which can even alter natural hand motion patterns. In this paper, we propose a low-cost soft exoskeleton glove (SExoG) system driven by surface electromyography (sEMG) signals from non-paretic hand for bilateral training. A customization method of geometrical parameters of soft actuators was presented, and their structure was redesigned. Then, the corresponding pressure values of air-pump to generate different angles of actuators were determined to support four hand motions (extension, rest, spherical grip, and fist). A two-step hybrid model combining the neural network and the state exclusion algorithm was proposed to recognize four hand motions via sEMG signals from the healthy limb. Four subjects were recruited to participate in the experiments. The experimental results show that the pressure values for the four hand motions were about -2, 0, 40, and 70 KPa, and the hybrid model can yield a mean accuracy of 98.7% across four hand motions. It can be concluded that the novel SExoG system can mirror the hand motions of non-paretic hand with good performance.