{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T03:18:11Z","timestamp":1789960691479,"version":"4.0.1"},"reference-count":43,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T00:00:00Z","timestamp":1765497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["82402979"],"award-info":[{"award-number":["82402979"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National clinical key specialty construction project of China","award":["Z155080000004"],"award-info":[{"award-number":["Z155080000004"]}]},{"name":"Shanghai Disabled Persons\u2019 Federation Key Laboratory of Intelligent Rehabilitation Assistive Appliance and Technology"},{"name":"Science and Technology Innovation Program of the Shanghai Municipal Science and Technology Commission","award":["22Y31900200"],"award-info":[{"award-number":["22Y31900200"]}]},{"name":"Science and Technology Innovation Program of the Shanghai Municipal Science and Technology Commission","award":["22Y31900203"],"award-info":[{"award-number":["22Y31900203"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Stroke-induced motor impairment necessitates objective and quantitative assessment tools for rehabilitation planning. In this study, a gesture-specific framework based on high-density surface electromyography (HD-sEMG) was developed to characterize neuromuscular dysfunction using eight macroscopic features and two microscopic motor unit decomposition features. HD-sEMG recordings were collected from stroke patients (n = 11; affected and unaffected sides) and healthy controls (n = 8; dominant side) during seven standardized hand gestures. Feature-level comparisons revealed hierarchical abnormalities, with the affected side showing significantly reduced activation\/coordination relative to healthy controls, while the unaffected side exhibited intermediate deviations. For each gesture, dedicated K-nearest neighbors (KNN) models were constructed for clinical validation. For Brunnstrom stage classification, wrist extension yielded the best performance, achieving 92.08% accuracy and effectively discriminating severe (Stage 4), moderate (Stage 5), and mild (Stage 6) impairment as well as healthy controls. For fine motor recovery prediction, the thumb\u2013index\u2013middle finger pinch provided the optimal regression performance, predicting Upper Extremity Fugl\u2013Meyer Assessment (UE-FMA) scores with R = 0.86 and RMSE = 3.24. These results indicate that gesture selection should be aligned with the clinical endpoint: wrist extension is most informative for gross recovery staging, whereas pinch gestures better capture fine motor control. Overall, the proposed HD-sEMG framework provides an objective approach for monitoring post-stroke recovery and supporting personalized rehabilitation assessment.<\/jats:p>","DOI":"10.3390\/bioengineering12121357","type":"journal-article","created":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T14:04:40Z","timestamp":1765548280000},"page":"1357","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Evaluating Stroke-Related Motor Impairment and Recovery Using Macroscopic and Microscopic Features of HD-sEMG"],"prefix":"10.3390","volume":"12","author":[{"given":"Wenting","family":"Qin","sequence":"first","affiliation":[{"name":"The Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Persons\u2019 Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200125, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Tan","sequence":"additional","affiliation":[{"name":"The College of Engineering and Design, Hunan Normal University, Changsha 410081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Yu","sequence":"additional","affiliation":[{"name":"The College of Engineering and Design, Hunan Normal University, Changsha 410081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujie","family":"Zhang","sequence":"additional","affiliation":[{"name":"The School of Information Science and Technology, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhanhui","family":"Lin","sequence":"additional","affiliation":[{"name":"The School of Information Science and Technology, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenyun","family":"Dai","sequence":"additional","affiliation":[{"name":"The School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200241, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxiang","family":"Yang","sequence":"additional","affiliation":[{"name":"The College of Engineering and Design, Hunan Normal University, Changsha 410081, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingyu","family":"Liu","sequence":"additional","affiliation":[{"name":"The Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Persons\u2019 Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200125, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7199-2578","authenticated-orcid":false,"given":"Lingjing","family":"Jin","sequence":"additional","affiliation":[{"name":"The Department of Neurology and Neurological Rehabilitation, Shanghai Disabled Persons\u2019 Federation Key Laboratory of Intelligent Rehabilitation Assistive Devices and Technologies, Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai 200125, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/S1474-4422(19)30415-6","article-title":"Advances and Challenges in Stroke Rehabilitation","volume":"19","author":"Stinear","year":"2020","journal-title":"Lancet Neurol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/S1474-4422(18)30499-X","article-title":"Global, Regional, and National Burden of Neurological Disorders, 1990\u20132016: A Systematic Analysis for the Global Burden of Disease Study 2016","volume":"18","author":"Feigin","year":"2019","journal-title":"Lancet Neurol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1016\/S1474-4422(21)00252-0","article-title":"Global, Regional, and National Burden of Stroke and Its Risk Factors, 1990\u20132019: A Systematic Analysis for the Global Burden of Disease Study 2019","volume":"20","author":"Feigin","year":"2021","journal-title":"Lancet Neurol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1186\/s12984-024-01496-6","article-title":"Telerehabilitation Using a 2-D Planar Arm Rehabilitation Robot for Hemiparetic Stroke: A Feasibility Study of Clinic-to-Home Exergaming Therapy","volume":"21","author":"Chua","year":"2024","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2095","DOI":"10.1001\/jama.296.17.2095","article-title":"Effect of Constraint-Induced Movement Therapy on Upper Extremity Function 3 to 9 Months After Stroke: The EXCITE Randomized Clinical Trial","volume":"296","author":"Wolf","year":"2006","journal-title":"JAMA"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"016070","DOI":"10.1088\/1741-2552\/ab673e","article-title":"Transcutaneous Innervation Zone Imaging from High-Density Surface Electromyography Recordings","volume":"17","author":"Liu","year":"2020","journal-title":"J. Neural Eng."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"046047","DOI":"10.1088\/1741-2552\/ac86f4","article-title":"Motor Unit Distribution and Recruitment in Spastic and Non-Spastic Bilateral Biceps Brachii Muscles of Chronic Stroke Survivors","volume":"19","author":"Liu","year":"2022","journal-title":"J. Neural Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1186\/s12984-024-01376-z","article-title":"Mapping of Spastic Muscle Activity after Stroke: Difference between Passive Stretch and Active Contraction","volume":"21","author":"Xie","year":"2024","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"056006","DOI":"10.1088\/1741-2552\/ad6fd5","article-title":"Characterizing Upper Limb Motor Dysfunction with Temporal and Spatial Distribution of Muscle Synergy Extracted from High-Density Surface Electromyography","volume":"21","author":"Zhang","year":"2024","journal-title":"J. Neural Eng."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1109\/TNSRE.2024.3486026","article-title":"Changes in Spatiotemporal Variability of Muscular Response Under the Influence of Post-Stroke Spasticity","volume":"33","author":"Xie","year":"2025","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3293","DOI":"10.1109\/TBME.2024.3416908","article-title":"Quantifying Muscle Co-Activation for Impaired Finger Independence in Stroke Survivors","volume":"71","author":"Ruan","year":"2024","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.jbmt.2013.11.006","article-title":"Stroke-Related Motor Outcome Measures: Do They Quantify the Neurophysiological Aspects of Upper Extremity Recovery?","volume":"18","author":"Pandian","year":"2014","journal-title":"J. Bodyw. Mov. Ther."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1109\/TNSRE.2021.3082551","article-title":"Open Access Dataset, Toolbox and Benchmark Processing Results of High-Density Surface Electromyogram Recordings","volume":"29","author":"Jiang","year":"2021","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4006313","DOI":"10.1109\/TIM.2023.3277930","article-title":"Extracting Spatial Muscle Activation Patterns in Facial and Neck Muscles for Silent Speech Recognition Using High-Density sEMG","volume":"72","author":"Tan","year":"2023","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1070","DOI":"10.1109\/JBHI.2020.3027389","article-title":"Cancelable HD-sEMG-Based Biometrics for Cross-Application Discrepant Personal Identification","volume":"25","author":"Jiang","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_16","unstructured":"Fougner, A.L. (2007). Proportional Myoelectric Control of a Multifunction Upper-Limb Prosthesis. [Master\u2019s Thesis, Norwegian University of Science and Technology]."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1016\/j.cap.2010.11.051","article-title":"Comparison of K-Nearest Neighbor, Quadratic Discriminant and Linear Discriminant Analysis in Classification of Electromyogram Signals Based on the Wrist-Motion Directions","volume":"11","author":"Kim","year":"2011","journal-title":"Curr. Appl. Phys."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1109\/10.204774","article-title":"A New Strategy for Multifunction Myoelectric Control","volume":"40","author":"Hudgins","year":"1993","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.compeleceng.2017.04.003","article-title":"Pattern Recognition of Electromyography Signals Based on Novel Time Domain Features for Amputees\u2019 Limb Motion Classification","volume":"67","author":"Samuel","year":"2018","journal-title":"Comput. Electr. Eng."},{"key":"ref_20","unstructured":"Du, S. (2003). Feature Extraction for Classification of Prehensile Electromyography Patterns, San Diego State University."},{"key":"ref_21","unstructured":"Du, S., and Vuskovic, M. (2004, January 8\u201310). Temporal vs. Spectral Approach to Feature Extraction from Prehensile EMG Signals. Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, Las Vegas, NV, USA. IRI 2004."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1109\/TNSRE.2025.3539700","article-title":"Exploring Control Mechanism of Motoneuron Pools for the Forearm Antagonist Synergistic Muscles","volume":"33","author":"Ren","year":"2025","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"026027","DOI":"10.1088\/1741-2560\/13\/2\/026027","article-title":"Multi-Channel Intramuscular and Surface EMG Decomposition by Convolutive Blind Source Separation","volume":"13","author":"Negro","year":"2016","journal-title":"J. Neural Eng."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hyvarinen, A., Oja, E., and Karhunen, J. (2001). Adaptive and learning systems for signal processing, communications, and control. Independent Component Analysis, J. Wiley.","DOI":"10.1002\/0471221317"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/S0893-6080(00)00026-5","article-title":"Independent Component Analysis: Algorithms and Applications","volume":"13","author":"Oja","year":"2000","journal-title":"Neural Netw."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1109\/JBHI.2020.3002329","article-title":"Quantifying Spatial Activation Patterns of Motor Units in Finger Extensor Muscles","volume":"25","author":"Jiang","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"760","DOI":"10.1109\/JBHI.2019.2926307","article-title":"Finger Joint Angle Estimation Based on Motoneuron Discharge Activities","volume":"24","author":"Dai","year":"2020","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"066006","DOI":"10.1088\/1741-2552\/ab2c55","article-title":"Real-Time Isometric Finger Extension Force Estimation Based on Motor Unit Discharge Information","volume":"16","author":"Zheng","year":"2019","journal-title":"J. Neural Eng."},{"key":"ref_29","first-page":"986","article-title":"KNN Model-Based Approach in Classification","volume":"2888","author":"Meersman","year":"2003","journal-title":"On the Move to Meaningful Internet Systems 2003: CoopIS, DOA, and ODBASE"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"789","DOI":"10.1177\/001316447403400406","article-title":"An Empirical Comparison of the Anova F-Test, Normal Scores Test and Kruskal-Wallis Test Under Violation of Assumptions","volume":"34","author":"Toothaker","year":"1974","journal-title":"Educ. Psychol. Meas."},{"key":"ref_31","unstructured":"(2025, October 30). A Simple Sequentially Rejective Multiple Test Procedure | Semantic Scholar. Available online: https:\/\/www.semanticscholar.org\/paper\/A-Simple-Sequentially-Rejective-Multiple-Test-Holm\/b0ebbcf713b3ddf3f94325bc58dc39ff76fdc412."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1007\/s002210100891","article-title":"Coordination of Upper and Lower Limb Segments: Deficits on the Ipsilesional Side after Unilateral Stroke","volume":"141","author":"Debaere","year":"2001","journal-title":"Exp. Brain Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.gaitpost.2006.08.007","article-title":"The Effects of Auditory Rhythms and Instruction on Walking Patterns in Individuals Post Stroke","volume":"26","author":"Ford","year":"2007","journal-title":"Gait Posture"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1016\/j.pmr.2015.06.008","article-title":"Upper Limb Motor Impairment After Stroke","volume":"26","author":"Raghavan","year":"2015","journal-title":"Phys. Med. Rehabil. Clin. North Am."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Kisiel-Sajewicz, K., Marusiak, J., Rojas-Mart\u00ednez, M., Janecki, D., Chomiak, S., Kami\u0144ski, \u0141., Mencel, J., Ma\u00f1anas, M.\u00c1., Jask\u00f3lski, A., and Jask\u00f3lska, A. (2020). High-Density Surface Electromyography Maps after Computer-Aided Training in Individual with Congenital Transverse Deficiency: A Case Study. BMC Musculoskelet. Disord., 21.","DOI":"10.1186\/s12891-020-03694-4"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0004-9514(06)70003-4","article-title":"Strengthening Interventions Increase Strength and Improve Activity after Stroke: A Systematic Review","volume":"52","author":"Ada","year":"2006","journal-title":"Aust. J. Physiother."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1002\/mus.20284","article-title":"Pathophysiology of Spastic Paresis. I: Paresis and Soft Tissue Changes","volume":"31","author":"Gracies","year":"2005","journal-title":"Muscle Nerve"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/1743-0003-3-15","article-title":"Behaviour of Motor Unit Action Potential Rate, Estimated from Surface EMG, as a Measure of Muscle Activation Level","volume":"3","author":"Kallenberg","year":"2006","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"046029","DOI":"10.1088\/1741-2552\/ac823d","article-title":"Neural Decoding from Surface High-Density EMG Signals: Influence of Anatomy and Synchronization on the Number of Identified Motor Units","volume":"19","author":"Oliveira","year":"2022","journal-title":"J. Neural Eng."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1007\/s001980070103","article-title":"Walking after Stroke: Does It Matter? Changes in Bone Mineral Density Within the First 12 Months after Stroke. A Longitudinal Study","volume":"11","author":"Jacobsen","year":"2000","journal-title":"Osteoporos. Int."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"McManus, L., Hu, X., Rymer, W.Z., Suresh, N.L., and Lowery, M.M. (2017). Motor Unit Activity during Fatiguing Isometric Muscle Contraction in Hemispheric Stroke Survivors. Front. Hum. Neurosci., 11.","DOI":"10.3389\/fnhum.2017.00569"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1101","DOI":"10.1002\/mus.880181006","article-title":"Characteristics of Motor Unit Discharge in Subjects with Hemiparesis","volume":"18","author":"Gemperline","year":"1995","journal-title":"Muscle Nerve"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Kim, W.-S., Cho, S., Baek, D., Bang, H., and Paik, N.-J. (2016). Upper Extremity Functional Evaluation by Fugl-Meyer Assessment Scoring Using Depth-Sensing Camera in Hemiplegic Stroke Patients. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0158640"}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/12\/12\/1357\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,14]],"date-time":"2025-12-14T05:13:09Z","timestamp":1765689189000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/12\/12\/1357"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,12]]},"references-count":43,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["bioengineering12121357"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering12121357","relation":{},"ISSN":["2306-5354"],"issn-type":[{"value":"2306-5354","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,12]]}}}