{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T07:52:26Z","timestamp":1769154746312,"version":"3.49.0"},"reference-count":38,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T00:00:00Z","timestamp":1631491200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFC2001704"],"award-info":[{"award-number":["2018YFC2001704"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61703232"],"award-info":[{"award-number":["61703232"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62073187"],"award-info":[{"award-number":["62073187"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Major Scientific and Technological Innovation Project in Shandong Province","award":["2019JZZY011111"],"award-info":[{"award-number":["2019JZZY011111"]}]},{"name":"Science and Technology Innovation Special Plan Project of Rizhao","award":["2019CXZX2212"],"award-info":[{"award-number":["2019CXZX2212"]}]},{"name":"Jining City Key Research and Development Program Project","award":["2020JKNS004"],"award-info":[{"award-number":["2020JKNS004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To improve the recognition rate of lower limb actions based on surface electromyography (sEMG), an effective weighted feature method is proposed, and an improved genetic algorithm support vector machine (IGA-SVM) is designed in this paper. First, for the problem of high feature redundancy and low discrimination in the surface electromyography feature extraction process, the weighted feature method is proposed based on the correlation between muscles and actions. Second, to solve the problem of the genetic algorithm selection operator easily falling into a local optimum solution, the improved genetic algorithm-support vector machine is designed by championship with sorting method. Finally, the proposed method is used to recognize six types of lower limb actions designed, and the average recognition rate reaches 94.75%. Experimental results indicate that the proposed method has definite potentiality in lower limb action recognition.<\/jats:p>","DOI":"10.3390\/s21186147","type":"journal-article","created":{"date-parts":[[2021,9,14]],"date-time":"2021-09-14T03:46:14Z","timestamp":1631591174000},"page":"6147","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Action Recognition of Lower Limbs Based on Surface Electromyography Weighted Feature Method"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8064-7741","authenticated-orcid":false,"given":"Jiashuai","family":"Wang","sequence":"first","affiliation":[{"name":"School of Engineering, Qufu Normal University, Rizhao 276826, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6179-2991","authenticated-orcid":false,"given":"Dianguo","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Engineering, Qufu Normal University, Rizhao 276826, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4786-168X","authenticated-orcid":false,"given":"Jinqiang","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Engineering, Qufu Normal University, Rizhao 276826, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1965-3020","authenticated-orcid":false,"given":"Chengyu","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"207914","DOI":"10.1109\/ACCESS.2020.3038422","article-title":"Recognition of Muscle Fatigue Status Based on Improved Wavelet Threshold and CNN-SVM","volume":"8","author":"Wang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1109\/TBME.1979.326534","article-title":"Physiology and Mathematics of Myoelectric Signals","volume":"BME-26","year":"1979","journal-title":"IEEE Trans. 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