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Commission","award":["82301158"],"award-info":[{"award-number":["82301158"]}]},{"name":"Shanghai Science and Technology Commission","award":["22015820100"],"award-info":[{"award-number":["22015820100"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To address the rehabilitation needs of upper limb hemiplegic patients in various stages of recovery, streamline the workload of rehabilitation professionals, and provide data visualization, our research team designed a six-degree-of-freedom upper limb exoskeleton rehabilitation robot inspired by the human upper limb\u2019s structure. We also developed an eight-channel synchronized signal acquisition system for capturing surface electromyography (sEMG) signals and elbow joint angle data. Utilizing Solidworks, we modeled the robot with a focus on modularity, and conducted structural and kinematic analyses. To predict the elbow joint angles, we employed a back propagation neural network (BPNN). We introduced three training modes: a PID control, bilateral control, and active control, each tailored to different phases of the rehabilitation process. Our experimental results demonstrated a strong linear regression relationship between the predicted reference values and the actual elbow joint angles, with an R-squared value of 94.41% and an average error of four degrees. Furthermore, these results validated the increased stability of our model and addressed issues related to the size and single-mode limitations of upper limb rehabilitation robots. This work lays the theoretical foundation for future model enhancements and further research in the field of rehabilitation.<\/jats:p>","DOI":"10.3390\/s23218801","type":"journal-article","created":{"date-parts":[[2023,10,30]],"date-time":"2023-10-30T13:26:55Z","timestamp":1698672415000},"page":"8801","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Design and Analysis of an Upper Limb Rehabilitation Robot Based on Multimodal Control"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-1920-8214","authenticated-orcid":false,"given":"Hang","family":"Ren","sequence":"first","affiliation":[{"name":"School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tongyou","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 201100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinwu","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200000, China"},{"name":"School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 201100, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e56","DOI":"10.1161\/CIR.0000000000000659","article-title":"Heart Disease and Stroke Statistics\u20142019 Update: A Report from the American Heart Association","volume":"139","author":"Benjamin","year":"2019","journal-title":"Circulation"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1108\/IR-09-2022-0239","article-title":"A systematic review of technological advancements in signal sensing, actuation, control and training methods in robotic exoskeletons for rehabilitation","volume":"50","author":"Mathew","year":"2023","journal-title":"Ind. 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