{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:28:27Z","timestamp":1772252907872,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,8,2]],"date-time":"2018-08-02T00:00:00Z","timestamp":1533168000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministerio de Economia Industria y Competitividad","award":["DPI2013-47944-C4-3-R"],"award-info":[{"award-number":["DPI2013-47944-C4-3-R"]}]},{"name":"Ministerio de Economia Industria y Competitividad","award":["DPI2016-75346-R"],"award-info":[{"award-number":["DPI2016-75346-R"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A high-level control algorithm capable of generating position and torque references from surface electromyography signals (sEMG) was designed. It was applied to a shape memory alloy (SMA)-actuated exoskeleton used in active rehabilitation therapies for elbow joints. The sEMG signals are filtered and normalized according to data collected online during the first seconds of a therapy session. The control algorithm uses the sEMG signals to promote active participation of patients during the therapy session. In order to generate the reference position pattern with good precision, the sEMG normalized signal is compared with a pressure sensor signal to detect the intention of each movement. The algorithm was tested in simulations and with healthy people for control of an elbow exoskeleton in flexion\u2013extension movements. The results indicate that sEMG signals from elbow muscles, in combination with pressure sensors that measure arm\u2013exoskeleton interaction, can be used as inputs for the control algorithm, which adapts the reference for exoskeleton movements according to a patient\u2019s intention.<\/jats:p>","DOI":"10.3390\/s18082522","type":"journal-article","created":{"date-parts":[[2018,8,3]],"date-time":"2018-08-03T03:03:15Z","timestamp":1533265395000},"page":"2522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A High-Level Control Algorithm Based on sEMG Signalling for an Elbow Joint SMA Exoskeleton"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3070-0994","authenticated-orcid":false,"given":"Dorin","family":"Copaci","sequence":"first","affiliation":[{"name":"Department of Systems Engineering and Automation, Carlos III University of Madrid, 28911 Legan\u00e9s, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5434-6857","authenticated-orcid":false,"given":"David","family":"Serrano","sequence":"additional","affiliation":[{"name":"Department of Systems Engineering and Automation, Carlos III University of Madrid, 28911 Legan\u00e9s, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis","family":"Moreno","sequence":"additional","affiliation":[{"name":"Department of Systems Engineering and Automation, Carlos III University of Madrid, 28911 Legan\u00e9s, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dolores","family":"Blanco","sequence":"additional","affiliation":[{"name":"Department of Systems Engineering and Automation, Carlos III University of Madrid, 28911 Legan\u00e9s, Madrid, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,8,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1093","DOI":"10.1007\/s11517-011-0799-y","article-title":"Assessing the effectiveness of robot facilitates neurorehabilitation for relearning motor skills","volume":"49","author":"Harwin","year":"2011","journal-title":"Med. 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