{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T16:48:54Z","timestamp":1792169334285,"version":"4.4.0"},"reference-count":32,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T00:00:00Z","timestamp":1752105600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Deanship of Scientific Research","award":["KFU252174"],"award-info":[{"award-number":["KFU252174"]}]},{"name":"The University of Oradea, Romania"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Background: Lokomat-assisted robotic rehabilitation is increasingly used for gait restoration in patients with spinal cord injury (SCI). However, the objective evaluation of treatment effectiveness through biomechanical parameters and machine learning approaches remains underexplored. Methods: This study analyzed data from 29 SCI patients undergoing Lokomat-based rehabilitation. A dataset of 46 variables including range of motion (L-ROM), joint stiffness (L-STIFF), and muscular force (L-FORCE) was examined using statistical methods (paired t-test, ANOVA, and ordinary least squares regression), clustering techniques (k-means), dimensionality reduction (t-SNE), and anomaly detection (Isolation Forest). Predictive modeling was applied to assess the influence of age, speed, body weight, body weight support, and exercise duration on biomechanical outcomes. Results: No statistically significant asymmetries were found between left and right limb measurements, indicating functional symmetry post-treatment (p &gt; 0.05). Clustering analysis revealed a weak structure among patient groups (Silhouette score \u2248 0.31). Isolation Forest identified minimal anomalies in stiffness data, supporting treatment consistency. Regression models showed that body weight and body weight support significantly influenced joint stiffness (p &lt; 0.01), explaining up to 60% of the variance in outcomes. Conclusions: Lokomat-assisted robotic rehabilitation demonstrates high functional symmetry and biomechanical consistency in SCI patients. Machine learning methods provided meaningful insight into the structure and predictability of outcomes, highlighting the clinical value of weight and support parameters in tailoring recovery protocols.<\/jats:p>","DOI":"10.3390\/bioengineering12070752","type":"journal-article","created":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T13:44:19Z","timestamp":1752241459000},"page":"752","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Lokomat-Assisted Robotic Rehabilitation in Spinal Cord Injury: A Biomechanical and Machine Learning Evaluation of Functional Symmetry and Predictive Factors"],"prefix":"10.3390","volume":"12","author":[{"given":"Alexandru","family":"Ilies","sequence":"first","affiliation":[{"name":"Faculty of Medicine and Pharmacy, University of Oradea, Str. Piata 1 Decembrie nr. 10, 410087 Oradea, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cornel","family":"Cheregi","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Pharmacy, University of Oradea, Str. Piata 1 Decembrie nr. 10, 410087 Oradea, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0510-3730","authenticated-orcid":false,"given":"Hassan","family":"Thowayeb","sequence":"additional","affiliation":[{"name":"Social Studies Department, College of Arts, King Faisal University, Al-Ahsa 31982, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"Wendt","sequence":"additional","affiliation":[{"name":"Szpital \u015aw. Wincentego a Paulo w Gdyni, ul. W\u00f3jta Radtkego 1, 81-348 Gdynia, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8828-7517","authenticated-orcid":false,"given":"Maur","family":"Horgos","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Pharmacy, University of Oradea, Str. Piata 1 Decembrie nr. 10, 410087 Oradea, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liviu","family":"Lazar","sequence":"additional","affiliation":[{"name":"Faculty of Medicine and Pharmacy, University of Oradea, Str. Piata 1 Decembrie nr. 10, 410087 Oradea, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.jocn.2021.07.019","article-title":"Robot-assisted gait training in individuals with spinal cord injury: A systematic review for the clinical effectiveness of Lokomat","volume":"91","author":"Alashram","year":"2021","journal-title":"J. Clin. Neurosci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1058","DOI":"10.1177\/1545968312448232","article-title":"Lokomat robotic-assisted versus overground training within 3 to 6 months of incomplete spinal cord lesion: Randomised controlled trial","volume":"26","year":"2012","journal-title":"Neurorehabilit. Neural Repair"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Baronchelli, F., Zucchella, C., Serrao, M., Intiso, D., and Bartolo, M. (2021). 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