{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:23:14Z","timestamp":1783437794368,"version":"3.54.6"},"reference-count":32,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2021,1,15]],"date-time":"2021-01-15T00:00:00Z","timestamp":1610668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51905175"],"award-info":[{"award-number":["51905175"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Pujiang Talent Program","award":["2019PJC021"],"award-info":[{"award-number":["2019PJC021"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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 \u22122, 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.<\/jats:p>","DOI":"10.3390\/s21020578","type":"journal-article","created":{"date-parts":[[2021,1,20]],"date-time":"2021-01-20T03:34:25Z","timestamp":1611113665000},"page":"578","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["A Soft Exoskeleton Glove for Hand Bilateral Training via Surface EMG"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2702-4649","authenticated-orcid":false,"given":"Yumiao","family":"Chen","sequence":"first","affiliation":[{"name":"School of Art, Design and Media, East China University of Science and Technology, Shanghai 200237, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2790-243X","authenticated-orcid":false,"given":"Zhongliang","family":"Yang","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Donghua University, Shanghai 201620, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yangliang","family":"Wen","sequence":"additional","affiliation":[{"name":"College of Mechanical Engineering, Donghua University, Shanghai 201620, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1093\/brain\/awm311","article-title":"Robot-based hand motor therapy after stroke","volume":"131","author":"Takahashi","year":"2008","journal-title":"Brain"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1177\/1545968307305457","article-title":"Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review","volume":"22","author":"Kwakkel","year":"2008","journal-title":"Neurorehabil. 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