{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T09:27:15Z","timestamp":1780392435744,"version":"3.54.1"},"reference-count":70,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T00:00:00Z","timestamp":1714694400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Shanghai Pujiang Program","award":["21PJ1404000"],"award-info":[{"award-number":["21PJ1404000"]}]},{"name":"The Shanghai Pujiang Program","award":["62103252"],"award-info":[{"award-number":["62103252"]}]},{"name":"the National Natural Science Foundation of China","award":["21PJ1404000"],"award-info":[{"award-number":["21PJ1404000"]}]},{"name":"the National Natural Science Foundation of China","award":["62103252"],"award-info":[{"award-number":["62103252"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study aimed to propose a portable and intelligent rehabilitation evaluation system for digital stroke-patient rehabilitation assessment. Specifically, the study designed and developed a fusion device capable of emitting red, green, and infrared lights simultaneously for photoplethysmography (PPG) acquisition. Leveraging the different penetration depths and tissue reflection characteristics of these light wavelengths, the device can provide richer and more comprehensive physiological information. Furthermore, a Multi-Channel Convolutional Neural Network\u2013Long Short-Term Memory\u2013Attention (MCNN-LSTM-Attention) evaluation model was developed. This model, constructed based on multiple convolutional channels, facilitates the feature extraction and fusion of collected multi-modality data. Additionally, it incorporated an attention mechanism module capable of dynamically adjusting the importance weights of input information, thereby enhancing the accuracy of rehabilitation assessment. To validate the effectiveness of the proposed system, sixteen volunteers were recruited for clinical data collection and validation, comprising eight stroke patients and eight healthy subjects. Experimental results demonstrated the system\u2019s promising performance metrics (accuracy: 0.9125, precision: 0.8980, recall: 0.8970, F1 score: 0.8949, and loss function: 0.1261). This rehabilitation evaluation system holds the potential for stroke diagnosis and identification, laying a solid foundation for wearable-based stroke risk assessment and stroke rehabilitation assistance.<\/jats:p>","DOI":"10.3390\/s24092925","type":"journal-article","created":{"date-parts":[[2024,5,3]],"date-time":"2024-05-03T09:39:47Z","timestamp":1714729187000},"page":"2925","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Rehabilitation Assessment System for Stroke Patients Based on Fusion-Type Optoelectronic Plethysmography Device and Multi-Modality Fusion Model: Design and Validation"],"prefix":"10.3390","volume":"24","author":[{"given":"Liangwen","family":"Yan","sequence":"first","affiliation":[{"name":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ze","family":"Long","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Qian","sequence":"additional","affiliation":[{"name":"Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianhua","family":"Lin","sequence":"additional","affiliation":[{"name":"Department of Rehabilitation Therapy, Yangzhi Affiliated Rehabilitation Hospital of Tongji University, Shanghai 201619, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2641-2620","authenticated-orcid":false,"given":"Sheng Quan","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Sheng","sequence":"additional","affiliation":[{"name":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200444, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1016\/S0140-6736(20)30925-9","article-title":"Global burden of 369 diseases and injuries in 204 countries and territories, 1990\u20132019: A systematic analysis for the Global Burden of Disease Study 2019","volume":"396","author":"Vos","year":"2020","journal-title":"Lancet"},{"key":"ref_2","first-page":"33","article-title":"China stroke surveillance report 2021","volume":"10","author":"Tu","year":"2023","journal-title":"Mil. 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