{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T04:21:23Z","timestamp":1782447683457,"version":"3.54.5"},"reference-count":29,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T00:00:00Z","timestamp":1724716800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Physiotherapy plays a crucial role in the rehabilitation of damaged or defective organs due to injuries or illnesses, often requiring long-term supervision by a physiotherapist in clinical settings or at home. AI-based support systems have been developed to enhance the precision and effectiveness of physiotherapy, particularly during the COVID-19 pandemic. These systems, which include game-based or tele-rehabilitation monitoring using camera-based optical systems like Vicon and Microsoft Kinect, face challenges such as privacy concerns, occlusion, and sensitivity to environmental light. Non-optical sensor alternatives, such as Inertial Movement Units (IMUs), Wi-Fi, ultrasound sensors, and ultrawide band (UWB) radar, have emerged to address these issues. Although IMUs are portable and cost-effective, they suffer from disadvantages like drift over time, limited range, and susceptibility to magnetic interference. In this study, a single UWB radar was utilized to recognize five therapeutic exercises related to the upper limb, performed by 34 male volunteers in a real environment. A novel feature fusion approach was developed to extract distinguishing features for these exercises. Various machine learning methods were applied, with the EnsembleRRGraBoost ensemble method achieving the highest recognition accuracy of 99.45%. The performance of the EnsembleRRGraBoost model was further validated using five-fold cross-validation, maintaining its high accuracy.<\/jats:p>","DOI":"10.3390\/s24175533","type":"journal-article","created":{"date-parts":[[2024,8,27]],"date-time":"2024-08-27T06:19:01Z","timestamp":1724739541000},"page":"5533","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Therapeutic Exercise Recognition Using a Single UWB Radar with AI-Driven Feature Fusion and ML Techniques in a Real Environment"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6989-4271","authenticated-orcid":false,"given":"Shahzad","family":"Hussain","sequence":"first","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Abu Dhabi Road, Rahim Yar Khan 64200, Punjab, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0671-2060","authenticated-orcid":false,"given":"Hafeez Ur Rehman","family":"Siddiqui","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Abu Dhabi Road, Rahim Yar Khan 64200, Punjab, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2468-8471","authenticated-orcid":false,"given":"Adil Ali","family":"Saleem","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Abu Dhabi Road, Rahim Yar Khan 64200, Punjab, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8881-1307","authenticated-orcid":false,"given":"Muhammad Amjad","family":"Raza","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Abu Dhabi Road, Rahim Yar Khan 64200, Punjab, Pakistan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9872-3082","authenticated-orcid":false,"given":"Josep Alemany","family":"Iturriaga","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias Sociales y Humanidades, Universidad Europea del Atl\u00e1ntico, Isabel Torres 21, 39011 Santander, Spain"},{"name":"Departamento de Ciencias de Lenguaje, Educaci\u00f3n y Comunicaciones, Universidad Internacional Iberoamericana Arecibo, Arecibo, PR 00613, USA"},{"name":"Universidad de La Romana, Edificio G&G, C\/ H\u00e9ctor Ren\u00e9 Gil, Esquina C\/ Francisco Castillo Marquez, La Romana 22000, Dominican Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9795-0904","authenticated-orcid":false,"given":"Alvaro","family":"Velarde-Sotres","sequence":"additional","affiliation":[{"name":"Facultad de Ciencias de la Salud, Universidad Europea del Atl\u00e1ntico, 39011 Santander, Spain"},{"name":"Departamento de Salud, Universidad Internacional Iberoamericana, Campeche 24560, Mexico"},{"name":"Faculdade de Ci\u00eancias de Sa\u00fade, Universidade Internacional do Cuanza Bairro Kaluanda, Cuito EN 250, Bi\u00e9, Angola"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isabel De la Torre","family":"D\u00edez","sequence":"additional","affiliation":[{"name":"Department of Signal Theory, Communications and Telematics Engineering, University of Valladolid, 47011 Valladolid, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,27]]},"reference":[{"key":"ref_1","first-page":"1176","article-title":"Kinect-based physiotherapy and assessment: A comprehensive","volume":"11","author":"Rashid","year":"2018","journal-title":"Indones. 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