{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T23:39:36Z","timestamp":1792366776271,"version":"4.4.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T00:00:00Z","timestamp":1784246400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T00:00:00Z","timestamp":1792368000000},"content-version":"vor","delay-in-days":94,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"Tianjin Metrology Technology Project","award":["2025TJMT026"],"award-info":[{"award-number":["2025TJMT026"]}]},{"name":"Natural Science Foundation of Tianjin Municipality","award":["S25YB01177"],"award-info":[{"award-number":["S25YB01177"]}]},{"name":"Tianjin Hospital Foundation","award":["TJYYQ2408"],"award-info":[{"award-number":["TJYYQ2408"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-026-62913-5","type":"journal-article","created":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T04:24:45Z","timestamp":1784262285000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Keypoint detection and functional evaluation of human lower limbs based on YOLOv8 and HRNet"],"prefix":"10.1038","volume":"16","author":[{"given":"Tao","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yichi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0702-9925","authenticated-orcid":false,"given":"Wen","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dezhi","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanmin","family":"Bu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruoying","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiwen","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,17]]},"reference":[{"key":"62913_CR1","doi-asserted-by":"crossref","unstructured":"Maillefert, J. F. et al. Laterally elevated wedged insoles in the treatment of medial knee osteoarthritis: a prospective randomized controlled study.Osteoarthritis Cartilage, 9: 738e45. (2001).","DOI":"10.1053\/joca.2001.0470"},{"key":"62913_CR2","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1111\/j.1600-0838.2006.00544.x","volume":"17","author":"AB Bremander","year":"2007","unstructured":"Bremander, A. B., Dahl, L. L. & Roos, E. M. Validity and reliability of functional performance tests in meniscectomized patients with or without knee osteoarthritis. Scand. J. Med. Sci. Sports. 17, 120\u2013127 (2007).","journal-title":"Scand. J. Med. Sci. Sports"},{"issue":"9","key":"62913_CR3","first-page":"232596711455098","volume":"2","author":"MB Naimark","year":"2014","unstructured":"Naimark, M. B. et al. Knee function assessment in patients with meniscus injury: a preliminary study of reproducibility, response to treatment, and correlation with patient-reported questionnaire outcomes.The Orthopaedic. J. Sports Med. 2 (9), 2325967114550987 (2014).","journal-title":"J. Sports Med."},{"key":"62913_CR4","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1007\/s10067-008-1021-y","volume":"28","author":"R Gandhi","year":"2009","unstructured":"Gandhi, R. et al. Relationship between self-reported and performance- based tests in a hip and knee joint replacement population. Clin. Rheumatol. 28, 253\u2013257 (2009).","journal-title":"Clin. Rheumatol."},{"key":"62913_CR5","doi-asserted-by":"publisher","first-page":"839","DOI":"10.1016\/j.arthro.2007.02.005","volume":"23","author":"K Crawford","year":"2007","unstructured":"Crawford, K. et al. Reliability, validity, and responsiveness of the IKDC score for meniscus injuries of the knee. Arthroscopy 23, 839\u2013844 (2007).","journal-title":"Arthroscopy"},{"key":"62913_CR6","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1097\/00005768-200301000-00025","volume":"35","author":"G Kervio","year":"2003","unstructured":"Kervio, G., Carre, F. & Ville, N. S. Reliability and intensity of the six-minute walk test in healthy elderly subjects. Med. Sci. Sports Exerc. 35, 169\u2013174 (2003).","journal-title":"Med. Sci. Sports Exerc."},{"key":"62913_CR7","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1034\/j.1600-0838.2001.110505.x","volume":"11","author":"YC Lin","year":"2001","unstructured":"Lin, Y. C., Davey, R. C. & Cochrane, T. Tests for physical function of the elderly with knee and hip osteoarthritis. Scand. J. Med. Sci. Sports. 11, 280\u2013286 (2001).","journal-title":"Scand. J. Med. Sci. Sports"},{"key":"62913_CR8","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/j.patcog.2018.04.015","volume":"81","author":"JM Carmona","year":"2018","unstructured":"Carmona, J. M. & Climent, J. Human action recognition by means of subtensor projections and dense trajectories. Pattern Recogn. 81, 443\u2013455 (2018).","journal-title":"Pattern Recogn."},{"issue":"1","key":"62913_CR9","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.jvcir.2013.03.001","volume":"25","author":"X Yang","year":"2014","unstructured":"Yang, X. & Tian, Y. Effective 3D action recognition using eigenjoints. J. Vis. Commun. Image Represent. 25 (1), 2\u201311 (2014).","journal-title":"J. Vis. Commun. Image Represent."},{"key":"62913_CR10","doi-asserted-by":"crossref","unstructured":"I.Laptev et al. M.Marszalek,C.SchmidLearning realistic human actions from movies.IEEE Conference on Computer Vision and Pattern Recognition,1\u20138 (2008).","DOI":"10.1109\/CVPR.2008.4587756"},{"key":"62913_CR11","doi-asserted-by":"crossref","unstructured":"Nguyen, P. T. A.Manzanera.Action recognition using bag of features extracted from a beam of trajectories.IEEE International Conference on Image Processing,4354\u20134357 (2013).","DOI":"10.1109\/ICIP.2013.6738897"},{"key":"62913_CR12","unstructured":"Tianming, Y., Zhi, C. & Wenjing, Y. Spatio-temporal two-stream human action recognition model based on video deep learning. J. Comput. Appl., 895\u2013899. (2018)."},{"key":"62913_CR13","doi-asserted-by":"crossref","unstructured":"Cai, Y. et al. Learning delicate local representations for multi-person pose estimation.Computer Vision-ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part III 16. Springer, : 455\u2013472. (2020).","DOI":"10.1007\/978-3-030-58580-8_27"},{"key":"62913_CR14","doi-asserted-by":"crossref","unstructured":"Chen, Y. et al. Cascaded pyramid network for multi-person pose estimation.Proceedings of the IEEE conference on computer vision and pattern recognition. : 7103\u20137112. (2018).","DOI":"10.1109\/CVPR.2018.00742"},{"key":"62913_CR15","doi-asserted-by":"crossref","unstructured":"Yang, W. et al. Learning feature pyramids for human pose estimation. Proceedings of the IEEE International Conference on Computer Vision,2017:1281\u20131290.","DOI":"10.1109\/ICCV.2017.144"},{"key":"62913_CR16","unstructured":"TOMPSON, J. J. et al. Joint training of a convolutional network and a graphical model for human pose estimation.Advances in. Neural Inform. Process. Syst., 2014: 1799\u20131807 ."},{"key":"62913_CR17","doi-asserted-by":"crossref","unstructured":"Insafutdinov, E. et al. Deepercut:A deeper, stronger, and faster multiperson pose estimation model.Computer Vision-ECCV. : 14th European Conference, Amsterdam,The Netherlands,October 11\u201314,2016,Proceedings,Part VI 14.Springer International Publishing,2016:34\u201350. (2016).","DOI":"10.1007\/978-3-319-46466-4_3"},{"key":"62913_CR18","unstructured":"Zhe, C. et al. Real time Multi-person 2D Pose Estimation Using Part Affinity Field.2017 IEEE Conference on Computer Vision and Pattern Recognition(CVP). IEEE, : 131\u2013140. (2017)."},{"key":"62913_CR19","doi-asserted-by":"crossref","unstructured":"A.Newell, C. & Vision (ECCV).Amsterdam,The Netherlands,:483\u2013499. (2016).","DOI":"10.1007\/978-3-319-46484-8_29"},{"key":"62913_CR20","unstructured":"Redmon, J. & Divvala, S. Ross Girshick,et al.You Only Look Once:Unified, Real-Time Object Detection,arXiv preprint arXiv:1506.02640."},{"key":"62913_CR21","doi-asserted-by":"crossref","unstructured":"Xiao, B., Wu, H. & Wei, Y. Simple baselines for human pose estimation and tracking. Proceedings of the European conference on computer vision (ECCV). : 466\u2013481. (2018).","DOI":"10.1007\/978-3-030-01231-1_29"},{"key":"62913_CR22","doi-asserted-by":"crossref","unstructured":"K.Su,D.Yu,Z.Xu, et al.Multi-person pose estimation with enhanced channel-wise and spatial information.Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. :5674\u20135682. (2019).","DOI":"10.1109\/CVPR.2019.00582"},{"key":"62913_CR23","doi-asserted-by":"crossref","unstructured":"U.Rafi, A. et al. Self-supervised keypoint correspondences for multiperson pose estimation and tracking in videos.Computer Vision-ECCV 2020:16th European Conference, Glasgow,UK,August 23\u201328,2020,Proceedings,Part XX16. Springer International Publishing, : 36\u201352. (2020).","DOI":"10.1007\/978-3-030-58565-5_3"},{"key":"62913_CR24","doi-asserted-by":"crossref","unstructured":"LOU, H. et al. DC-YOLOv8: Small-Size Object Detection Algorithm Based on Camera Sensor. Electron. 2023, 12(10): 2323 .","DOI":"10.3390\/electronics12102323"},{"key":"62913_CR25","doi-asserted-by":"crossref","unstructured":"Geng, Z. et al. Bottom-up human pose estimation via disentangled keypoint Regression.Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. : 14676\u201314686. (2021).","DOI":"10.1109\/CVPR46437.2021.01444"},{"key":"62913_CR26","doi-asserted-by":"crossref","unstructured":"Cheng, B. et al. Higherhrnet: Scale-aware representation learning for bottom-up human pose estimation.Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. : 5386\u20135395. (2020).","DOI":"10.1109\/CVPR42600.2020.00543"},{"key":"62913_CR27","doi-asserted-by":"crossref","unstructured":"SHU, Y. & Vision-Based, H. U. L. A. Human Posture Detection Approach for Smart Home Applications. Int. J. Adv. Comput. Sci. Appl. 14 (10), 209\u2013216 (2023).","DOI":"10.14569\/IJACSA.2023.0141023"},{"issue":"11","key":"62913_CR28","doi-asserted-by":"publisher","first-page":"3662","DOI":"10.1109\/JSAC.2023.3310097","volume":"41","author":"JX CHEN","year":"2023","unstructured":"CHEN, J. X. & WANG, W. Digital Twin Empowered Wireless Healthcare Monitoring for Smart Home. IEEE J. Sel. Areas Commun. 41 (11), 3662\u20133676 (2023).","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"62913_CR29","doi-asserted-by":"crossref","unstructured":"Di Wu, N., Sharma, M. & Blumenstein Recent advances in video-based human action recognition using deep learning: A review.2017 International Joint Conference on Neural Networks (IJCNN). IEEE, 2865\u20132872. (2017).","DOI":"10.1109\/IJCNN.2017.7966210"},{"key":"62913_CR30","doi-asserted-by":"crossref","unstructured":"H.Wang A.Kl\u00e4ser,C.Schmid,et al.Dense trajectories and motion boundary descriptors for action recognition[J]. Int. J. Comput. Vis. 2013, 103(1):60\u201379","DOI":"10.1007\/s11263-012-0594-8"},{"issue":"1","key":"62913_CR31","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1109\/JIOT.2016.2628938","volume":"4","author":"I Bisio","year":"2016","unstructured":"Bisio, I. et al. Enabling IoT for In-Home Rehabilitation: Accelerometer Signals Classification Methods for Activity and Movement Recognition. IEEE Internet Things J. 4 (1), 135\u2013146 (2016).","journal-title":"IEEE Internet Things J."},{"key":"62913_CR32","doi-asserted-by":"crossref","unstructured":"Ahmadi, M. et al. Machine learning algorithms for activity recognition in ambulant children and adolescents with cerebral palsy. J. Neuroeng. Rehabilitation 2018, 15(1): 105 .","DOI":"10.1186\/s12984-018-0456-x"},{"key":"62913_CR33","doi-asserted-by":"crossref","unstructured":"Gkioxari, G. et al. Articulated pose estimation using discriminative armlet classifiers.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2013:3342\u20133349.","DOI":"10.1109\/CVPR.2013.429"},{"issue":"1","key":"62913_CR34","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1109\/TII.2018.2839749","volume":"15","author":"A SHAHZAD","year":"2019","unstructured":"SHAHZAD, A. & FallDroid, K. I. M. K. An Automated Smart-Phone-Based Fall Detection System Using Multiple Kernel Learning. IEEE Trans. Industr. Inf. 15 (1), 35\u201344 (2019).","journal-title":"IEEE Trans. Industr. Inf."},{"key":"62913_CR35","first-page":"422","volume":"2010","author":"B Sapp","year":"2010","unstructured":"Sapp, B., Jordan, C. & Taskar, B. Adaptive pose priors for pictorial structures. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. 2010, 422\u2013429 (2010).","journal-title":"IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit."},{"key":"62913_CR36","doi-asserted-by":"crossref","unstructured":"YIN, Y. et al. Research on Fall Detection Algorithm for the Elderly Living Alone Based on YOLO.2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT). IEEE, : 403\u2013408 (2021).","DOI":"10.1109\/ICESIT53460.2021.9696459"},{"key":"62913_CR37","doi-asserted-by":"crossref","unstructured":"K.Sun,B.Xiao,D.Liu, et al.Deep high-resolution representation learning for human pose estimation.Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. :5693\u20135703. (2019).","DOI":"10.1109\/CVPR.2019.00584"},{"key":"62913_CR38","doi-asserted-by":"crossref","unstructured":"ZHANG, X. et al. Dense Spatial-Temporal Graph Convolutional Network Based on Lightweight OpenPose for Detecting Falls Vol. 77, 47\u201361 (Tech Science, 2023). 1.","DOI":"10.32604\/cmc.2023.042561"},{"key":"62913_CR39","doi-asserted-by":"crossref","unstructured":"CAO, Z. et al. Realtime Multi-Person 2d Pose Estimation Using Part Affinity Fields.Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. : 7291\u20137299. (2017).","DOI":"10.1109\/CVPR.2017.143"},{"key":"62913_CR40","doi-asserted-by":"crossref","unstructured":"MA, N. et al. Shufflenetv2: Practical Guidelines for Efficient CNN Architecture Design.Proceedings of the European Conference on Computer Vision (ECCV). : 116\u2013131. (2018).","DOI":"10.1007\/978-3-030-01264-9_8"},{"key":"62913_CR41","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.exger.2018.08.006","volume":"112","author":"J Alcazar","year":"2018","unstructured":"Alcazar, J. et al. The sit-to-stand muscle power test: An easy, inexpensive and portable procedure to assess muscle power in older people. Exp. Gerontol. 112, 38\u201343 (2018).","journal-title":"Exp. Gerontol."},{"key":"62913_CR42","doi-asserted-by":"publisher","first-page":"112565","DOI":"10.1016\/j.jbiomech.2025.112565","volume":"182","author":"H Liu","year":"2025","unstructured":"Liu, H. et al. Mechanical modeling of the dynamic response of the knee joint angle in the evaluation of muscle nerve response and energy consumption. J. Biomech. 182, 112565 (2025).","journal-title":"J. Biomech."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-62913-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-62913-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-62913-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,18]],"date-time":"2026-10-18T22:49:08Z","timestamp":1792363748000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-026-62913-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,17]]},"references-count":42,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["62913"],"URL":"https:\/\/doi.org\/10.1038\/s41598-026-62913-5","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,17]]},"assertion":[{"value":"5 December 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 July 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The study was approved by the Institutional Ethical Review Board of Tianjin Hospital Tianjin University (No. TJYY-2025-YLS-325) and conducted in accordance with the Ethical Guidelines for Epidemiological Research by the Chinese Government, as well as the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All study participants provided written informed consent prior to completing and submitting the survey.","order":2,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Before recording the test videos, the project team obtained patient permission to publicly publish images from the knee joint function tests.","order":3,"name":"Ethics","label":"Consent to publish","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"32730"}}