{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T17:19:50Z","timestamp":1771003190074,"version":"3.50.1"},"reference-count":24,"publisher":"SAGE Publications","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2021,9,28]]},"abstract":"<jats:p>A novel method of mirror motion recognition by rehabilitation robot with multi-channels sEMG signals is proposed, aiming to help the stroked patients to complete rehabilitation training movement. Firstly the bilateral mirror training is used and the model of muscle synergy with basic sEMG signals is established. Secondly, the constrained L1\/2-NMF is used to extracted the main sEMG signals information which can also reduce the limb movement characteristics. Finally the relationship between sEMG signal characteristics and upper limb movement is described by TSSVD-ELM and it is applied to improve the model stability. The validity and feasibility of the proposed strategy are verified by the experiments in this paper, and the rehabilitation robot can move with the mirror upper limb. By comparing the method proposed in this paper with PCA and full-action feature extraction, it is confirmed that convergence speed is faster; the feature extraction accuracy is higher which can be used in rehabilitation robot systems.<\/jats:p>","DOI":"10.3233\/jcm-204812","type":"journal-article","created":{"date-parts":[[2021,3,16]],"date-time":"2021-03-16T14:20:54Z","timestamp":1615904454000},"page":"1021-1029","source":"Crossref","is-referenced-by-count":1,"title":["Mirror motion recognition method about upper limb rehabilitation robot based on sEMG"],"prefix":"10.1177","volume":"21","author":[{"given":"Lin","family":"Li","sequence":"first","affiliation":[]}],"member":"179","reference":[{"key":"10.3233\/JCM-204812_ref1","first-page":"743","article-title":"Adaptive interaction control for lower limb rehabilitation robots","volume":"44","author":"Du","year":"2018","journal-title":"Acta Automatica Sinica"},{"key":"10.3233\/JCM-204812_ref2","doi-asserted-by":"crossref","first-page":"1972","DOI":"10.1109\/LRA.2018.2811506","article-title":"Approach to the segmentation of sEMG data based on the activation and deactivation of muscle synergies during movement","volume":"3","author":"\u00c1lvaro","year":"2018","journal-title":"IEEE Robotics and Automation Letters"},{"key":"10.3233\/JCM-204812_ref3","first-page":"2000","article-title":"Physical interaction methods for rehabilitation and assistive robots","volume":"44","author":"Peng","year":"2018","journal-title":"Acta Automatica Sinica"},{"key":"10.3233\/JCM-204812_ref4","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1007\/s11517-016-1551-4","article-title":"Classification of ankle joint movements based on surface electromyography signals for rehabilitation robot applications","volume":"55","author":"Ishak","year":"2017","journal-title":"Medical & Biological Engineering & Computing"},{"key":"10.3233\/JCM-204812_ref5","first-page":"1","article-title":"Master-slave upper-limb exoskeletion rehabilitation robot training control method based on fuzzy compensation","volume":"40","author":"Zhang","year":"2018","journal-title":"Robot"},{"key":"10.3233\/JCM-204812_ref6","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1109\/THMS.2014.2358634","article-title":"Hand and wrist movement control of myoelectric prosthesis based on synergy","volume":"45","author":"Ma","year":"2015","journal-title":"Human-Machine Systems"},{"key":"10.3233\/JCM-204812_ref7","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1109\/TSMCB.2012.2185843","article-title":"An EMG-based control for an upper-limb power-assist exoskeleton robot","volume":"42","author":"Kugychi","year":"2012","journal-title":"Systems, Man, and Cybernetics-part B: Cybernetics"},{"key":"10.3233\/JCM-204812_ref8","first-page":"97","article-title":"sEMG-based impedance control for lower-limb rehabilitation robot","volume":"11","author":"Vahab","year":"2017","journal-title":"Intelligent Service Robotics"},{"key":"10.3233\/JCM-204812_ref9","doi-asserted-by":"crossref","first-page":"9022","DOI":"10.3390\/s150409022","article-title":"Comparison of sEMG-based feature extraction and motion classification methods for upper-limb movement","volume":"15","author":"Guo","year":"2015","journal-title":"Sensors"},{"key":"10.3233\/JCM-204812_ref10","first-page":"1765","article-title":"Recent advances in rehabilitation robots and intelligent assistance systems","volume":"42","author":"Hou","year":"2016","journal-title":"Acta Automatica Sinica"},{"key":"10.3233\/JCM-204812_ref11","doi-asserted-by":"crossref","first-page":"036004","DOI":"10.1088\/1741-2560\/6\/3\/036004","article-title":"Muscle synergies as a predictive framework for the EMG patterns of new hand postures","volume":"6","author":"Ajiboye","year":"2009","journal-title":"Journal of Neural Engineering"},{"key":"10.3233\/JCM-204812_ref12","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1109\/TKDE.2012.51","article-title":"Nonnegative matrix factorization: a comprehensive review","volume":"25","author":"Wang","year":"2013","journal-title":"Knowledge and Data Engineering"},{"key":"10.3233\/JCM-204812_ref13","doi-asserted-by":"crossref","first-page":"478","DOI":"10.1109\/JBHI.2014.2326660","article-title":"Non negative matrix factorisation for the identification of EMG finger movements: evaluation using matrix analysis","volume":"19","author":"Naik","year":"2015","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"10.3233\/JCM-204812_ref14","doi-asserted-by":"crossref","first-page":"2427","DOI":"10.1109\/TNSRE.2017.2769659","article-title":"Direction modulation of muscle synergies in a hand-reaching task","volume":"25","author":"Israely","year":"2017","journal-title":"IEEE Transactions on Neural Systems and Rehabilitation Engineering"},{"key":"10.3233\/JCM-204812_ref15","first-page":"317","article-title":"EEG frequency PCA in EEG-ERP dynamics","volume":"55","author":"Barry","year":"2017","journal-title":"Engineering Structures"},{"key":"10.3233\/JCM-204812_ref16","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.jelekin.2018.05.002","article-title":"Identification of regional activation by factorization of high-density surface EMG signals: a comparison of principal component analysis and non-negative matrix factorization","volume":"41","author":"Gallinaa","year":"2018","journal-title":"Journal of Electromyography and Kinesiology"},{"key":"10.3233\/JCM-204812_ref17","doi-asserted-by":"crossref","first-page":"2975","DOI":"10.1109\/TGRS.2014.2365953","article-title":"Substance dependence constrained sparse NMF for hyperspectral unmixing","volume":"53","author":"Yuan","year":"2015","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"10.3233\/JCM-204812_ref18","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1109\/THMS.2017.2751549","article-title":"Modified, nonnegative matrix factorization using the hadamard product to estimate real-time continuous finger-motion intentions","volume":"47","author":"Kim","year":"2017","journal-title":"IEEE Transactions on Human-Machine Systems"},{"key":"10.3233\/JCM-204812_ref19","doi-asserted-by":"crossref","unstructured":"H. Norsalina and A.R. Dzati, A comparative study of blind source separation for bioacoustics sounds based on FastICA, PCA and NMF, Procedia Computer Science 126 (2018), 363\u2013372.","DOI":"10.1016\/j.procs.2018.07.270"},{"key":"10.3233\/JCM-204812_ref20","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.neucom.2005.12.126","article-title":"Extreme learning machine: theory and application","volume":"2006","author":"Huang","year":"2006","journal-title":"Neurocomputing"},{"key":"10.3233\/JCM-204812_ref21","doi-asserted-by":"crossref","first-page":"8","DOI":"10.14419\/jacst.v5i1.5225","article-title":"A review on data stream classification approaches","volume":"5","author":"Homayoun","year":"2016","journal-title":"Journal of Advanced Computer Science & Technology"},{"key":"10.3233\/JCM-204812_ref22","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1109\/TVLSI.2016.2558842","article-title":"VLSI, extreme learning machine: a design space exploration","volume":"25","author":"Yao","year":"2017","journal-title":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems"},{"key":"10.3233\/JCM-204812_ref23","first-page":"1769","article-title":"Maintenance level decision based on singular value decomposition of extreme learning machine","volume":"48","author":"Liu","year":"2017","journal-title":"Journal of Central South University (Science and Technology)"},{"key":"10.3233\/JCM-204812_ref24","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.knosys.2017.07.014","article-title":"A novel double deep ELMs ensemble system for time series forecasting","volume":"134","author":"Song","year":"2017","journal-title":"Knowledge-Based Systems"}],"container-title":["Journal of Computational Methods in Sciences and Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/JCM-204812","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T16:31:38Z","timestamp":1771000298000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/JCM-204812"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,28]]},"references-count":24,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.3233\/jcm-204812","relation":{},"ISSN":["1472-7978","1875-8983"],"issn-type":[{"value":"1472-7978","type":"print"},{"value":"1875-8983","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,9,28]]}}}