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Mechanomyography (MMG) signals offer unparalleled advantages over sEMG, reflecting the intention of human movement while being noninvasive. Therefore, in this paper, based on MMG, a combined scheme of gray relational analysis (GRA) and support vector regression optimized by an improved cuckoo search algorithm (ICS-SVR) is proposed to estimate the knee joint extension force. Firstly, the features reflecting muscle activity comprehensively, such as time-domain features, frequency-domain features, time\u2013frequency-domain features, and nonlinear dynamics features, were extracted from MMG signals, and the relational degree was calculated using the GRA method to obtain the correlation features with high relatedness to the knee joint extension force sequence. Then, a combination of correlated features with high relational degree was input into the designed ICS-SVR model for muscle force estimation. The experimental results show that the evaluation indices of the knee joint extension force estimation obtained by the combined scheme of GRA and ICS-SVR were superior to other regression models and could estimate the muscle force with higher estimation accuracy. It is further demonstrated that the proposed scheme can meet the need of muscle force estimation required for rehabilitation devices, powered prostheses, etc.<\/jats:p>","DOI":"10.3390\/s22124651","type":"journal-article","created":{"date-parts":[[2022,6,22]],"date-time":"2022-06-22T04:12:01Z","timestamp":1655871121000},"page":"4651","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Estimation of Knee Extension Force Using Mechanomyography Signals Based on GRA and ICS-SVR"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6195-9798","authenticated-orcid":false,"given":"Zebin","family":"Li","sequence":"first","affiliation":[{"name":"Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"},{"name":"Department of Science Island, University of Science and Technology of China, Hefei 230026, China"},{"name":"School of Electrical and Photoelectric Engineering, West Anhui University, Lu\u2019an 237012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lifu","family":"Gao","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"},{"name":"Department of Science Island, University of Science and Technology of China, Hefei 230026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Lu","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"},{"name":"Department of Science Island, University of Science and Technology of China, Hefei 230026, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4060-4234","authenticated-orcid":false,"given":"Daqing","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huibin","family":"Cao","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Photoelectric Engineering, West Anhui University, Lu\u2019an 237012, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"50299","DOI":"10.1109\/ACCESS.2020.2980053","article-title":"A Method for Identification of Mechanical Response of Motor Units in Skeletal Muscle Voluntary Contractions Using Ultrafast Ultrasound Imaging\u2014Simulations and Experimental Tests","volume":"8","author":"Yu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Hou, J., Sun, Y., Sun, L., Pan, B., Huang, Z., Wu, J., and Zhang, Z. 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