{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T14:39:10Z","timestamp":1790174350655,"version":"4.1.0"},"reference-count":25,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T00:00:00Z","timestamp":1775433600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Human pose estimation is a crucial task in computer vision with widespread applications in healthcare, rehabilitation, sports, and remote monitoring. In this paper, we propose a deep learning-based method for automatic human pose estimation and joint angle computation, tailored specifically for physiotherapy and telemedicine scenarios. Beyond pose estimation, the proposed method is able to compute angles between joints, enabling analysis of body alignment and posture. The proposed approach is built upon a customized skeleton with 25 anatomical keypoints and a dataset composed of over 150,000 annotated and augmented images derived from multiple open-source datasets. Experimental results demonstrate the effectiveness of the proposed method, achieving a mAP@50 of 0.58 for keypoint localization and 0.98 for object detection. Moreover, we demonstrate several real-world practical use cases in evaluating exercise correctness and identifying postural deviations by exploiting the proposed method, confirming that the proposed method can represent a promising approach for automated motion analysis, with potential impact on digital health, rehabilitation support, and remote patient care.<\/jats:p>","DOI":"10.3390\/jimaging12040157","type":"journal-article","created":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T08:58:48Z","timestamp":1775465928000},"page":"157","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Method for Human Pose Estimation and Joint Angle Computation Through Deep Learning"],"prefix":"10.3390","volume":"12","author":[{"given":"Ludovica","family":"Ciardiello","sequence":"first","affiliation":[{"name":"Department of Medicine and Health Sciences \u201cVincenzo Tiberio\u201d, University of Molise, 86100 Campobasso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0130-8727","authenticated-orcid":false,"given":"Patrizia","family":"Agnello","sequence":"additional","affiliation":[{"name":"Istituto Nazionale per l\u2019Assicurazione Contro gli Infortuni sul Lavoro, 00144 Roma, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marta","family":"Petyx","sequence":"additional","affiliation":[{"name":"Istituto Nazionale per l\u2019Assicurazione Contro gli Infortuni sul Lavoro, 00144 Roma, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabio","family":"Martinelli","sequence":"additional","affiliation":[{"name":"Institute for High Performance Computing and Networking, National Research Council of Italy (CNR), 87036 Rende, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mario","family":"Cesarelli","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Sannio, 82100 Benevento, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonella","family":"Santone","sequence":"additional","affiliation":[{"name":"Department of Medicine and Health Sciences \u201cVincenzo Tiberio\u201d, University of Molise, 86100 Campobasso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9425-1657","authenticated-orcid":false,"given":"Francesco","family":"Mercaldo","sequence":"additional","affiliation":[{"name":"Department of Medicine and Health Sciences \u201cVincenzo Tiberio\u201d, University of Molise, 86100 Campobasso, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1007\/s00530-022-00980-0","article-title":"A comprehensive survey on human pose estimation approaches","volume":"29","author":"Dubey","year":"2023","journal-title":"Multimed. 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