{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:29:38Z","timestamp":1772263778307,"version":"3.50.1"},"reference-count":65,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2022,11,11]],"date-time":"2022-11-11T00:00:00Z","timestamp":1668124800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Grants-in-Aid for Scientific Research (KAKENHI) Program","doi-asserted-by":"publisher","award":["22H03990"],"award-info":[{"award-number":["22H03990"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In clinical practice, acute post-stroke paresis of the extremities fundamentally complicates timely rehabilitation of motor functions; however, recently, residual and distorted musculoskeletal signals have been used to initiate feedback-driven solutions for establishing motor rehabilitation. Here, we investigate the possibilities of basic hand gesture recognition in acute stroke patients with hand paresis using a novel, acute stroke, four-component multidomain feature set (ASF-4) with feature vector weight additions (ASF-14NP, ASF-24P) and supervised learning algorithms trained only by surface electromyography (sEMG). A total of 19 (65.9 \u00b1 12.4 years old; 12 men, seven women) acute stroke survivors (12.4 \u00b1 6.3 days since onset) with hand paresis (Brunnstrom stage 4 \u00b1 1\/4 \u00b1 1, SIAS 3 \u00b1 1\/3 \u00b1 2, FMA-UE 40 \u00b1 20) performed 10 repetitive hand movements reflecting basic activities of daily living (ADLs): rest, fist, pinch, wrist flexion, wrist extension, finger spread, and thumb up. Signals were recorded using an eight-channel, portable sEMG device with electrode placement on the forearms and thenar areas of both limbs (four sensors on each extremity). Using data preprocessing, semi-automatic segmentation, and a set of extracted feature vectors, support vector machine (SVM), linear discriminant analysis (LDA), and k-nearest neighbors (k-NN) classifiers for statistical comparison and validity (paired t-tests, p-value &lt; 0.05), we were able to discriminate myoelectrical patterns for each gesture on both paretic and non-paretic sides. Despite any post-stroke conditions, the evaluated total accuracy rate by the 10-fold cross-validation using SVM among four-, five-, six-, and seven-gesture models were 96.62%, 94.20%, 94.45%, and 95.57% for non-paretic and 90.37%, 88.48%, 88.60%, and 89.75% for paretic limbs, respectively. LDA had competitive results using PCA whereas k-NN was a less efficient classifier in gesture prediction. Thus, we demonstrate partial efficacy of the combination of sEMG and supervised learning for upper-limb rehabilitation procedures for early acute stroke motor recovery and various treatment applications.<\/jats:p>","DOI":"10.3390\/s22228733","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T04:30:52Z","timestamp":1668400252000},"page":"8733","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Supervised Myoelectrical Hand Gesture Recognition in Post-Acute Stroke Patients with Upper Limb Paresis on Affected and Non-Affected Sides"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3509-759X","authenticated-orcid":false,"given":"Alexey","family":"Anastasiev","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, Graduate School of Comprehensive Human Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2953-6434","authenticated-orcid":false,"given":"Hideki","family":"Kadone","sequence":"additional","affiliation":[{"name":"Center for Cybernics Research, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8573, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aiki","family":"Marushima","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4436-5437","authenticated-orcid":false,"given":"Hiroki","family":"Watanabe","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6833-9866","authenticated-orcid":false,"given":"Alexander","family":"Zaboronok","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9953-8665","authenticated-orcid":false,"given":"Shinya","family":"Watanabe","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akira","family":"Matsumura","sequence":"additional","affiliation":[{"name":"Ibaraki Prefectural University of Health Sciences, 4669-2 Amicho, Inashiki 300-0394, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1736-5404","authenticated-orcid":false,"given":"Kenji","family":"Suzuki","sequence":"additional","affiliation":[{"name":"Center for Cybernics Research, Artificial Intelligence Laboratory, Faculty of Engineering Information and Systems, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8573, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuji","family":"Matsumaru","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eiichi","family":"Ishikawa","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba 305-8575, Ibaraki, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1161\/STROKEAHA.118.022913","article-title":"Long-term survival and function after stroke: A longitudinal observational study from the Swedish Stroke Register","volume":"50","author":"Norrving","year":"2019","journal-title":"Stroke"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"S85","DOI":"10.1016\/j.wneu.2011.07.023","article-title":"Epidemiology and the Global Burden of Stroke","volume":"76","author":"Mukherjee","year":"2011","journal-title":"World Neurosurg."},{"key":"ref_3","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. 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