132263 20260217205506.0 doi 10.3390/s24030831 sideral 137416 ART-2024-137416 eng Villalba-Meneses, Fernando Classification of the Pathological Range of Motion in Low Back Pain Using Wearable Sensors and Machine Learning 2024 Access copy available to the general public Unrestricted Low back pain (LBP) is a highly common musculoskeletal condition and the leading cause of work absenteeism. This project aims to develop a medical test to help healthcare professionals decide on and assign physical treatment for patients with nonspecific LBP. The design uses machine learning (ML) models based on the classification of motion capture (MoCap) data obtained from the range of motion (ROM) exercises among healthy and clinically diagnosed patients with LBP from Imbabura–Ecuador. The following seven ML algorithms were tested for evaluation and comparison: logistic regression, decision tree, random forest, support vector machine (SVM), k-nearest neighbor (KNN), multilayer perceptron (MLP), and gradient boosting algorithms. All ML techniques obtained an accuracy above 80%, and three models (SVM, random forest, and MLP) obtained an accuracy of >90%. SVM was found to be the best-performing algorithm. This article aims to improve the applicability of inertial MoCap in healthcare by making use of precise spatiotemporal measurements with a data-driven treatment approach to improve the quality of life of people with chronic LBP. info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 3.5 2024 CHEMISTRY, ANALYTICAL 38 / 111 = 0.342 2024 Q2 T2 INSTRUMENTS & INSTRUMENTATION 24 / 79 = 0.304 2024 Q2 T1 ENGINEERING, ELECTRICAL & ELECTRONIC 134 / 368 = 0.364 2024 Q2 T2 0.764 2024 Instrumentation 2024 Q1 Analytical Chemistry 2024 Q1 Medicine (miscellaneous) 2024 Q2 Information Systems 2024 Q2 Biochemistry 2024 Q2 Atomic and Molecular Physics, and Optics 2024 Q2 Electrical and Electronic Engineering 2024 Q2 8.2 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Guevara, Cesar Lojan, Alejandro B. Gualsaqui, Mario G. Arias-Serrano, Isaac Velásquez-López, Paolo A. Almeida-Galárraga, Diego Tirado-Espín, Andrés Marín, Javier Universidad de Zaragoza (orcid)0000-0003-4527-3267 Marín, José J. Universidad de Zaragoza (orcid)0000-0003-3223-1324 5002 720 Universidad de Zaragoza Dpto. Ingeniería Diseño Fabri. Área Proyectos de Ingeniería 24, 3 (2024), 831 [15 pp.] Sensors Sensors 1424-8220 1658496 http://zaguan.unizar.es/record/132263/files/texto_completo.pdf Versión publicada 2792345 http://zaguan.unizar.es/record/132263/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:132263 articulos driver 2026-02-17-20:23:35 ARTICLE