{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:19:46Z","timestamp":1788913186882,"version":"build-2803163510"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T00:00:00Z","timestamp":1708300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20210930"],"award-info":[{"award-number":["BK20210930"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010023","name":"Natural Science Research of Jiangsu Higher Education Institutions of China","doi-asserted-by":"publisher","award":["21KJB510039"],"award-info":[{"award-number":["21KJB510039"]}],"id":[{"id":"10.13039\/501100010023","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurosci."],"abstract":"<jats:p>The clinical rehabilitation assessment methods for hemiplegic upper limb motor function are often subjective, time-consuming, and non-uniform. This study proposes an automatic rehabilitation assessment method for upper limb motor function based on posture and distributed force measurements. Azure Kinect combined with MediaPipe was used to detect upper limb and hand movements, and the array distributed flexible thin film pressure sensor was employed to measure the distributed force of hand. This allowed for the automated measurement of 30 items within the Fugl-Meyer scale. Feature information was extracted separately from the affected and healthy sides, the feature ratios or deviation were then fed into a single\/multiple fuzzy logic assessment model to determine the assessment score of each item. Finally, the total score of the hemiplegic upper limb motor function assessment was derived. Experiments were performed to evaluate the motor function of the subjects\u2019 upper extremities. Bland-Altman plots of physician and system scores showed good agreement. The results of the automated assessment system were highly correlated with the clinical Fugl-Meyer total score (<jats:italic>r<\/jats:italic>\u2009=\u20090.99, <jats:italic>p<\/jats:italic>\u2009&amp;lt;\u20090.001). The experimental results state that this system can automatically assess the motor function of the affected upper limb by measuring the posture and force distribution.<\/jats:p>","DOI":"10.3389\/fnins.2024.1362495","type":"journal-article","created":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T04:28:54Z","timestamp":1708316934000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["Automatic rehabilitation assessment method of upper limb motor function based on posture and distribution force"],"prefix":"10.3389","volume":"18","author":[{"given":"Jing","family":"Bai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guocheng","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuanming","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiulan","family":"Wen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,2,19]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.17219\/acem\/152596","article-title":"Accuracy of machine learning algorithms for the assessment of upper-limb motor impairments in patients with post-stroke hemiparesis: a systematic review and meta-analysis","volume":"31","author":"Ambros-Antemate","year":"2022","journal-title":"Adv. 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Neural Repair"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.1109\/TNSRE.2020.2978197","article-title":"A heterogeneous sensing suite for multisymptom quantification of Parkinson\u2019s disease","volume":"28","author":"Huo","year":"2020","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref14","doi-asserted-by":"publisher","first-page":"1622","DOI":"10.3390\/s20061622","article-title":"Analysis of machine learning-based assessment for elbow spasticity using inertial sensors","volume":"20","author":"Kim","year":"2020","journal-title":"Sensors"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1109\/TNSRE.2017.2755667","article-title":"Automated evaluation of upper-limb motor function impairment using Fugl\u2013Meyer assessment","volume":"26","author":"Lee","year":"2018","journal-title":"IEEE Trans. Neural Syst. Rehabil. 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