{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T06:34:55Z","timestamp":1784097295969,"version":"3.55.0"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T00:00:00Z","timestamp":1771891200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T00:00:00Z","timestamp":1771891200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1007\/s11517-026-03524-0","type":"journal-article","created":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T05:11:14Z","timestamp":1771909874000},"page":"1489-1504","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Application of a spatiotemporal distribution-based multidimensional gait feature algorithm in KOA gait assessment"],"prefix":"10.1007","volume":"64","author":[{"given":"Yuzhe","family":"Tan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhijie","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zilong","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0544-4714","authenticated-orcid":false,"given":"Haicheng","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"XingZhou","family":"Du","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyi","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yitong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,24]]},"reference":[{"key":"3524_CR1","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/6231406","volume":"2021","author":"L Zhang","year":"2021","unstructured":"Zhang L, Liu G, Han B, Yan Y, Fei J, Ma J, Zhang Y (2021) A comparison of dynamic and static hip-knee-ankle angle during gait in knee osteoarthritis patients and healthy individuals. Appl Bionics Biomech 2021:6231406. https:\/\/doi.org\/10.1155\/2021\/6231406","journal-title":"Appl Bionics Biomech"},{"key":"3524_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2025.112881","volume":"190","author":"FA Moura","year":"2025","unstructured":"Moura FA, Pelegrinelli ARM, Catelli DS, Lamontagne M, Torres RS (2025) Knee osteoarthritis prediction from gait kinematics: exploring the potential of deep neural networks and transfer learning methods for time series classification. J Biomech 190:112881. https:\/\/doi.org\/10.1016\/j.jbiomech.2025.112881","journal-title":"J Biomech"},{"key":"3524_CR3","doi-asserted-by":"publisher","first-page":"412","DOI":"10.1109\/TNSRE.2024.3352004","volume":"32","author":"H Tian","year":"2024","unstructured":"Tian H, Li H, Jiang W, Ma X, Li X, Wu H, Li Y (2024) Cross-spatiotemporal graph convolution networks for skeleton-based parkinsonian gait MDS-UPDRS score estimation. IEEE Trans Neural Syst Rehabil Eng 32:412\u2013421. https:\/\/doi.org\/10.1109\/TNSRE.2024.3352004","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"3524_CR4","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-30352-1","volume":"13","author":"Y Saiki","year":"2023","unstructured":"Saiki Y, Kajino Y, Ojima T et al (2023) Reliability and validity of OpenPose for measuring hip-knee-ankle angle in patients with knee osteoarthritis. Sci Rep 13:3297. https:\/\/doi.org\/10.1038\/s41598-023-30352-1","journal-title":"Sci Rep"},{"key":"3524_CR5","doi-asserted-by":"publisher","DOI":"10.7717\/peerj-cs.2843","volume":"11","author":"Y Lee","year":"2025","unstructured":"Lee Y, Kim J (2025) ROM-pose: restoring occluded mask image for 2D human pose estimation. PeerJ Comput Sci 11:e2843. https:\/\/doi.org\/10.7717\/peerj-cs.2843","journal-title":"PeerJ Comput Sci"},{"key":"3524_CR6","doi-asserted-by":"publisher","first-page":"1309","DOI":"10.1109\/TIFS.2023.3236181","volume":"18","author":"C Xu","year":"2023","unstructured":"Xu C, Makihara Y, Li X, Yagi Y (2023) Occlusion-aware human mesh model-based gait recognition. IEEE Trans Inf Forensics Secur 18:1309\u20131321. https:\/\/doi.org\/10.1109\/TIFS.2023.3236181","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"3524_CR7","doi-asserted-by":"publisher","first-page":"12106","DOI":"10.1007\/s11227-023-05143-0","volume":"79","author":"C Meng","year":"2023","unstructured":"Meng C, He X, Tan Z, Luan L (2023) Gait recognition based on 3D human body reconstruction and multi-granular feature fusion. J Supercomput 79:12106\u201312125. https:\/\/doi.org\/10.1007\/s11227-023-05143-0","journal-title":"J Supercomput"},{"key":"3524_CR8","doi-asserted-by":"publisher","unstructured":"Koleini F, Saleem MU, Wang P et al (2025) BioPose: biomechanically-accurate 3D pose estimation from monocular videos. IEEE Trans Pattern Anal Mach Intell 2. https:\/\/doi.org\/10.1109\/WACV61041.2025.00617","DOI":"10.1109\/WACV61041.2025.00617"},{"key":"3524_CR9","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-80237-w","volume":"11","author":"JH Park","year":"2021","unstructured":"Park JH, Lee H, Cho JS et al (2021) Effects of knee osteoarthritis severity on inter-joint coordination and gait variability as measured by hip-knee cyclograms. Sci Rep 11:1789. https:\/\/doi.org\/10.1038\/s41598-020-80237-w","journal-title":"Sci Rep"},{"key":"3524_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.msard.2022.103741","volume":"60","author":"M Pau","year":"2022","unstructured":"Pau M, Leban B, Massa D et al (2022) Inter-joint coordination during gait in people with multiple sclerosis: a focus on the effect of disability. Mult Scler Relat Disord 60:103741. https:\/\/doi.org\/10.1016\/j.msard.2022.103741","journal-title":"Mult Scler Relat Disord"},{"key":"3524_CR11","doi-asserted-by":"publisher","first-page":"3257","DOI":"10.1016\/j.csbj.2022.06.022","volume":"20","author":"M Zanin","year":"2022","unstructured":"Zanin M, Olivares F, Pulido-Valdeolivas I, Rausell E, Gomez-Andres D (2022) Gait analysis under the lens of statistical physics. Comput Struct Biotechnol J 20:3257\u20133267. https:\/\/doi.org\/10.1016\/j.csbj.2022.06.022","journal-title":"Comput Struct Biotechnol J"},{"key":"3524_CR12","doi-asserted-by":"publisher","first-page":"24","DOI":"10.5103\/KJSB.2021.31.1.24","volume":"31","author":"P Dinesh","year":"2021","unstructured":"Dinesh P (2021) Calculation and comparison of maximum Lyapunov exponent in different direction: an approach to human gait stability. Korean J Appl Biomech 31:24\u201329. https:\/\/doi.org\/10.5103\/KJSB.2021.31.1.24","journal-title":"Korean J Appl Biomech"},{"key":"3524_CR13","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1109\/CVPR52733.2024.00132","volume-title":"Proc IEEE Conf Comput Vis pattern Recognit (CVPR) 2024","author":"SK Dwivedi","year":"2024","unstructured":"Dwivedi SK, Sun Y, Patel P, Feng Y, Black MJ (2024) Tokenhmr: advancing human mesh recovery with a tokenized pose representation. In: Proc IEEE Conf Comput Vis pattern Recognit (CVPR) 2024, pp 1323\u20131333. https:\/\/doi.org\/10.1109\/CVPR52733.2024.00132"},{"key":"3524_CR14","doi-asserted-by":"publisher","first-page":"174","DOI":"10.17706\/IJCEE.2018.10.3.174-186","volume":"10","author":"AS Al-Fahoum","year":"2018","unstructured":"Al-Fahoum AS, Abadir MS (2018) Design of a modified Madgwick filter for quaternion-based orientation estimation using AHRS. Int J Comput Electr Eng 10:174\u2013186. https:\/\/doi.org\/10.17706\/IJCEE.2018.10.3.174-186","journal-title":"Int J Comput Electr Eng"},{"key":"3524_CR15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3618381","volume":"42","author":"M Keller","year":"2023","unstructured":"Keller M, Werling K, Shin S et al (2023) From skin to skeleton: towards biomechanically accurate 3d digital humans. ACM Trans Graph 42:1\u201312. https:\/\/doi.org\/10.1145\/3618381","journal-title":"ACM Trans Graph"},{"key":"3524_CR16","doi-asserted-by":"publisher","DOI":"10.1186\/s12984-024-01416-8","volume":"21","author":"K Saegner","year":"2024","unstructured":"Saegner K, Romijnders R, Hansen C et al (2024) Inter-joint coordination with and without dopaminergic medication in Parkinson\u2019s disease: a case-control study. J Neuroeng Rehabil 21:118. https:\/\/doi.org\/10.1186\/s12984-024-01416-8","journal-title":"J Neuroeng Rehabil"},{"key":"3524_CR17","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1016\/j.jbiomech.2018.03.015","volume":"72","author":"JA Longworth","year":"2018","unstructured":"Longworth JA, Chlosta S, Foucher KC (2018) Inter-joint coordination of kinematics and kinetics before and after total hip arthroplasty compared to asymptomatic subjects. J Biomech 72:180\u2013186. https:\/\/doi.org\/10.1016\/j.jbiomech.2018.03.015","journal-title":"J Biomech"},{"key":"3524_CR18","doi-asserted-by":"publisher","DOI":"10.1101\/2024.12.02.24318001","author":"P Terrier","year":"2024","unstructured":"Terrier P (2024) From stability to complexity: a systematic review protocol on long-term divergence exponents in gait analysis. medRxiv. https:\/\/doi.org\/10.1101\/2024.12.02.24318001","journal-title":"medRxiv"},{"key":"3524_CR19","doi-asserted-by":"publisher","first-page":"11026","DOI":"10.3390\/app142311026","volume":"14","author":"A Mohammadzadeh Gonabadi","year":"2024","unstructured":"Mohammadzadeh Gonabadi A, Fallahtafti F, Burnfield JM (2024) How gait nonlinearities in individuals without known pathology describe metabolic cost during walking using artificial neural network and multiple linear regression. Appl Sci 14:11026. https:\/\/doi.org\/10.3390\/app142311026","journal-title":"Appl Sci"},{"key":"3524_CR20","doi-asserted-by":"publisher","DOI":"10.3389\/fbioe.2025.1645162","volume":"13","author":"Y Tan","year":"2025","unstructured":"Tan Y, Wang Z, Wu Y, Wei H, Zhao J, Jiao Y, Wang Y (2025) Application of multidimensional gait feature fusion algorithm in gait assessment for patients with knee osteoarthritis. Front Bioeng Biotechnol 13:1645162. https:\/\/doi.org\/10.3389\/fbioe.2025.1645162","journal-title":"Front Bioeng Biotechnol"},{"key":"3524_CR21","doi-asserted-by":"publisher","first-page":"844","DOI":"10.1016\/j.ard.2025.01.012","volume":"84","author":"JS Rockel","year":"2025","unstructured":"Rockel JS, Sharma D, Espin-Garcia O et al (2025) Deep learning\u2013based clustering for endotyping and post-arthroplasty response classification using knee osteoarthritis multiomic data. Ann Rheum Dis 84:844\u2013855. https:\/\/doi.org\/10.1016\/j.ard.2025.01.012","journal-title":"Ann Rheum Dis"},{"key":"3524_CR22","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1008935","volume":"17","author":"J Stenum","year":"2021","unstructured":"Stenum J, Rossi C, Roemmich RT (2021) Two-dimensional video-based analysis of human gait using pose estimation. PLoS Comput Biol 17:e1008935. https:\/\/doi.org\/10.1371\/journal.pcbi.1008935","journal-title":"PLoS Comput Biol"},{"key":"3524_CR23","doi-asserted-by":"publisher","unstructured":"Hulleck AA, Menon PP, Dowling N et al (2023) Accuracy of computer vision-based pose estimation algorithms in predicting joint kinematics during gait. Res Sq. https:\/\/doi.org\/10.21203\/rs.3.rs-3239200\/v1","DOI":"10.21203\/rs.3.rs-3239200\/v1"},{"key":"3524_CR24","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2024.3391908","author":"AA Hulleck","year":"2024","unstructured":"Hulleck AA, Alshehhi A, El Rich M et al (2024) BlazePose-Seq2Seq: leveraging regular RGB cameras for robust gait assessment. IEEE Trans Neural Syst Rehabil Eng. https:\/\/doi.org\/10.1109\/TNSRE.2024.3391908","journal-title":"IEEE Trans Neural Syst Rehabil Eng"},{"key":"3524_CR25","doi-asserted-by":"publisher","first-page":"5355","DOI":"10.1109\/CVPR52734.2025.00504","volume-title":"Proc IEEE Conf Comput Vis pattern Recognit (CVPR) 2025","author":"Y Xia","year":"2025","unstructured":"Xia Y, Zhou X, Vouga E, Huang Q, Pavlakos G (2025) Reconstructing humans with a biomechanically accurate skeleton. In: Proc IEEE Conf Comput Vis pattern Recognit (CVPR) 2025, pp 5355\u20135365. https:\/\/doi.org\/10.1109\/CVPR52734.2025.00504"},{"key":"3524_CR26","doi-asserted-by":"publisher","first-page":"38","DOI":"10.3758\/s13428-024-02546-6","volume":"57","author":"A Koul","year":"2025","unstructured":"Koul A, Atesh A, Novembre G (2025) How accurately can we estimate spontaneous body kinematics from video recordings? Effect of movement amplitude on OpenPose accuracy. Behav Res Methods 57:38. https:\/\/doi.org\/10.3758\/s13428-024-02546-6","journal-title":"Behav Res Methods"},{"key":"3524_CR27","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1016\/j.joca.2021.10.010","volume":"30","author":"N D\u2019Souza","year":"2022","unstructured":"D\u2019Souza N, Collins NJ, Vicenzino B, Crossley KM, Wrigley TV, Hinman RS et al (2022) Are biomechanics during gait associated with the structural disease onset and progression of lower limb osteoarthritis? A systematic review and meta-analysis. Osteoarthr Cartil 30:381\u2013394. https:\/\/doi.org\/10.1016\/j.joca.2021.10.010","journal-title":"Osteoarthr Cartil"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-026-03524-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11517-026-03524-0","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-026-03524-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T09:49:45Z","timestamp":1777283385000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11517-026-03524-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2,24]]},"references-count":27,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["3524"],"URL":"https:\/\/doi.org\/10.1007\/s11517-026-03524-0","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,2,24]]},"assertion":[{"value":"4 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 January 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 February 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}