{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T06:27:18Z","timestamp":1774679238756,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T00:00:00Z","timestamp":1651104000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2018YFC1313600"],"award-info":[{"award-number":["2018YFC1313600"]}]},{"name":"National Key Research and Development Program of China","award":["SS201851"],"award-info":[{"award-number":["SS201851"]}]},{"name":"Suzhou Science and Technology Plan Program","award":["2018YFC1313600"],"award-info":[{"award-number":["2018YFC1313600"]}]},{"name":"Suzhou Science and Technology Plan Program","award":["SS201851"],"award-info":[{"award-number":["SS201851"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Motor function evaluation is a significant part of post-stroke rehabilitation protocols, and the evaluation of wrist motor function helps provide patients with individualized rehabilitation training programs. However, traditional assessment is coarsely graded, lacks quantitative analysis, and relies heavily on clinical experience. In order to objectively quantify wrist motor dysfunction in stroke patients, a novel quantitative evaluation system based on force feedback and machine learning algorithm was proposed. Sensors embedded in the force-feedback robot record the kinematic and movement data of the subject, and the rehabilitation doctor used an evaluation scale to score the wrist function of the subject. The quantitative evaluation models of wrist motion function based on random forest (RF), support vector machine regression (SVR), k-nearest neighbor (KNN), and back propagation neural network (BPNN) were established, respectively. To verify the effectiveness of the proposed quantitative evaluation system, 25 stroke patients and 10 healthy volunteers were recruited in this study. Experimental results show that the evaluation accuracy of the four models is all above 88%. The accuracy of BPNN model is 94.26%, and the Pearson correlation coefficient between model prediction and clinician scores is 0.964, indicating that the BPNN model can accurately evaluate the wrist motor function for stroke patients. In addition, there was a significant correlation between the prediction score of the quantitative assessment system and the physician scale score (p &lt; 0.05). The proposed system enables quantitative and refined assessment of wrist motor function in stroke patients and has the feasibility of helping rehabilitation physicians in evaluating patients\u2019 motor function clinically.<\/jats:p>","DOI":"10.3390\/s22093368","type":"journal-article","created":{"date-parts":[[2022,4,28]],"date-time":"2022-04-28T22:20:06Z","timestamp":1651184406000},"page":"3368","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Quantitative Evaluation System of Wrist Motor Function for Stroke Patients Based on Force Feedback"],"prefix":"10.3390","volume":"22","author":[{"given":"Kangjia","family":"Ding","sequence":"first","affiliation":[{"name":"School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China"},{"name":"Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bochao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China"},{"name":"Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zongquan","family":"Ling","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China"},{"name":"Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China"},{"name":"Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liquan","family":"Guo","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China"},{"name":"Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daxi","family":"Xiong","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China"},{"name":"Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiping","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Suzhou 215163, China"},{"name":"Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2064","DOI":"10.1161\/STR.0b013e318296aeca","article-title":"An updated definition of stroke for the 21st century: A statement for healthcare professionals from the American Heart Association\/American Stroke Association","volume":"44","author":"Sacco","year":"2013","journal-title":"Stroke"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e139","DOI":"10.1161\/CIR.0000000000000757","article-title":"Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association","volume":"141","author":"Virani","year":"2020","journal-title":"Circulation"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e98","DOI":"10.1161\/STR.0000000000000098","article-title":"Guidelines for Adult Stroke Rehabilitation and Recovery: A Guideline for Healthcare Professionals From the American Heart Association\/American Stroke Association","volume":"47","author":"Winstein","year":"2016","journal-title":"Stroke"},{"key":"ref_4","first-page":"CD010820","article-title":"Interventions for improving upper limb function after stroke","volume":"11","author":"Pollock","year":"2014","journal-title":"Cochrane Database Syst. 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