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A better understanding of the influence of gait kinematics on synergies and a better synergy-modeling method are important for device design and improvement. To this end, gait data from healthy, amputee, and stroke subjects were collected. First, continuous relative phase (CRP) was used to quantify their synergies and explore the influence of kinematics. Second, long short-term memory (LSTM) and principal component analysis (PCA) were adopted to model interlimb synergy and intralimb synergy, respectively. The results indicate that the limited hip and knee range of motions (RoMs) in stroke patients and amputees significantly influence their synergies in different ways. In interlimb synergy modeling, LSTM (RMSE: 0.798\u00b0 (hip) and 1.963\u00b0 (knee)) has lower errors than PCA (RMSE: 5.050\u00b0 (hip) and 10.353\u00b0 (knee)), which is frequently used in the literature. Further, in intralimb synergy modeling, LSTM (RMSE: 3.894\u00b0) enables better synergy modeling than PCA (RMSE: 10.312\u00b0). In conclusion, stroke patients and amputees perform different compensatory mechanisms to adapt to new interlimb and intralimb synergies different from healthy people. LSTM has better synergy modeling and shows a promise for generating trajectories in line with the wearer\u2019s motion for lower limb assistive devices.<\/jats:p>","DOI":"10.3390\/s22134814","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T22:50:23Z","timestamp":1656283823000},"page":"4814","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Gait Synergy Analysis and Modeling on Amputees and Stroke Patients for Lower Limb Assistive Devices"],"prefix":"10.3390","volume":"22","author":[{"given":"Feng-Yan","family":"Liang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China"},{"name":"Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Gao","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China"},{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junyi","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Mechanical Engineering, Xi\u2019an Jiaotong University, Xi\u2019an 710049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheung-Wai","family":"Law","sequence":"additional","affiliation":[{"name":"Tai Po Hospital, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7221-5906","authenticated-orcid":false,"given":"Wei-Hsin","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,25]]},"reference":[{"key":"ref_1","unstructured":"Kawamoto, H., Lee, S., Kanbe, S., and Sankai, Y. 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