{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T13:50:43Z","timestamp":1785419443051,"version":"3.56.0"},"reference-count":45,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T00:00:00Z","timestamp":1769299200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shanghai Class IV Peak Discipline Construction Fund"},{"name":"Shanghai Advanced Rehabilitation Medical Technology and Management Innovation Project","award":["SHKFJS002F"],"award-info":[{"award-number":["SHKFJS002F"]}]},{"name":"Shanghai Science and Technology Support Project","award":["23S31902800"],"award-info":[{"award-number":["23S31902800"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accurate upper-limb motor assessment is critical for post-stroke rehabilitation but relies on subjective clinical scales. This study proposes the Action-Aware Multimodal Wavelet Fusion Network (AMWFNet), integrating surface electromyography (sEMG) and robotic kinematics for automated Fugl-Meyer Assessment (FMA-UE)-aligned quantification. Continuous Wavelet Transform (CWT) converts heterogeneous signals into unified time-frequency scalograms. A learnable modality gating mechanism dynamically weights physiological and kinematic features, while action embeddings encode task contexts across 18 standardized reaching tasks. Validated on 40 participants (20 post-stroke, 20 healthy), AMWFNet achieved 94.68% accuracy in six-class classification, outperforming baselines by 9.17% (Random Forest: 85.51%, SVM: 85.30%, 1D-CNN: 91.21%). The lightweight architecture (1.27 M parameters, 922 ms inference) enables real-time assessment-training integration in rehabilitation robots, providing an objective, efficient solution.<\/jats:p>","DOI":"10.3390\/s26030804","type":"journal-article","created":{"date-parts":[[2026,1,26]],"date-time":"2026-01-26T16:13:48Z","timestamp":1769444028000},"page":"804","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Action-Aware Multimodal Wavelet Fusion Network for Quantitative Elbow Motor Function Assessment Using sEMG and Robotic Kinematics"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9716-4649","authenticated-orcid":false,"given":"Zilong","family":"Song","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, College of Biomedical Engineering, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-2450-6411","authenticated-orcid":false,"given":"Pei","family":"Zhu","sequence":"additional","affiliation":[{"name":"Changhai Hospital, Naval Medical University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3338-5835","authenticated-orcid":false,"given":"Cuiwei","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, College of Biomedical Engineering, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3478-6692","authenticated-orcid":false,"given":"Daomiao","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, College of Biomedical Engineering, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0694-2669","authenticated-orcid":false,"given":"Jialiang","family":"Song","sequence":"additional","affiliation":[{"name":"Changhai Hospital, Naval Medical University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3952-1178","authenticated-orcid":false,"given":"Daoyu","family":"Wang","sequence":"additional","affiliation":[{"name":"Zdroid Medtech Co., Ltd., Shanghai 201210, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7535-5242","authenticated-orcid":false,"given":"Fanfu","family":"Fang","sequence":"additional","affiliation":[{"name":"Changhai Hospital, Naval Medical University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8169-7894","authenticated-orcid":false,"given":"Yixi","family":"Wang","sequence":"additional","affiliation":[{"name":"Zdroid Medtech Co., Ltd., Shanghai 201210, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1016\/S1474-4422(17)30299-5","article-title":"Global, Regional, and National Burden of Neurological Disorders during 1990\u20132015: A Systematic Analysis for the Global Burden of Disease Study 2015","volume":"16","author":"Feigin","year":"2017","journal-title":"Lancet Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"100941","DOI":"10.1016\/j.cegh.2021.100941","article-title":"Assessing Quality of Life and Associated Factors in Post-Stroke Patients Using the World Health Organization Abbreviated Generic Quality of Life Questionnaire","volume":"13","author":"Martini","year":"2022","journal-title":"Clin. 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