{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T12:22:39Z","timestamp":1773750159501,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T00:00:00Z","timestamp":1702425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"JSPS KAKENHI","award":["JP20K19317"],"award-info":[{"award-number":["JP20K19317"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accuracy validation of gait analysis using pose estimation with artificial intelligence (AI) remains inadequate, particularly in objective assessments of absolute error and similarity of waveform patterns. This study aimed to clarify objective measures for absolute error and waveform pattern similarity in gait analysis using pose estimation AI (OpenPose). Additionally, we investigated the feasibility of simultaneous measuring both lower limbs using a single camera from one side. We compared motion analysis data from pose estimation AI using video footage that was synchronized with a three-dimensional motion analysis device. The comparisons involved mean absolute error (MAE) and the coefficient of multiple correlation (CMC) to compare the waveform pattern similarity. The MAE ranged from 2.3 to 3.1\u00b0 on the camera side and from 3.1 to 4.1\u00b0 on the opposite side, with slightly higher accuracy on the camera side. Moreover, the CMC ranged from 0.936 to 0.994 on the camera side and from 0.890 to 0.988 on the opposite side, indicating a \u201cvery good to excellent\u201d waveform similarity. Gait analysis using a single camera revealed that the precision on both sides was sufficiently robust for clinical evaluation, while measurement accuracy was slightly superior on the camera side.<\/jats:p>","DOI":"10.3390\/s23249799","type":"journal-article","created":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T12:00:37Z","timestamp":1702468837000},"page":"9799","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Validity of AI-Based Gait Analysis for Simultaneous Measurement of Bilateral Lower Limb Kinematics Using a Single Video Camera"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0980-4147","authenticated-orcid":false,"given":"Takumi","family":"Ino","sequence":"first","affiliation":[{"name":"Graduate School of Health Sciences, Hokkaido University, Sapporo 0600812, Japan"},{"name":"Department of Physical Therapy, Faculty of Health Sciences, Hokkaido University of Science, Sapporo 0068585, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4663-598X","authenticated-orcid":false,"given":"Mina","family":"Samukawa","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0174-7416","authenticated-orcid":false,"given":"Tomoya","family":"Ishida","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan"}]},{"given":"Naofumi","family":"Wada","sequence":"additional","affiliation":[{"name":"Department of Information and Computer Science, Faculty of Engineering, Hokkaido University of Science, Sapporo 0068585, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1942-7798","authenticated-orcid":false,"given":"Yuta","family":"Koshino","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan"}]},{"given":"Satoshi","family":"Kasahara","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan"}]},{"given":"Harukazu","family":"Tohyama","sequence":"additional","affiliation":[{"name":"Faculty of Health Sciences, Hokkaido University, Sapporo 0600812, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","article-title":"OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields","volume":"43","author":"Cao","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_2","first-page":"7605","article-title":"Towards balance assessment using Openpose","volume":"2021","author":"Li","year":"2021","journal-title":"Annu. Int. Conf. IEEE Eng. Med. Biol. Soc."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Sato, K., Nagashima, Y., Mano, T., Iwata, A., and Toda, T. (2019). Quantifying normal and parkinsonian gait features from home movies: Practical application of a deep learning-based 2D pose estimator. PLoS ONE, 14.","DOI":"10.1101\/782367"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6132","DOI":"10.1038\/s41598-023-32893-x","article-title":"Pose estimation and motion analysis of ski jumpers based on ECA-HRNet","volume":"13","author":"Bao","year":"2023","journal-title":"Sci. Rep."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Haberkamp, L.D., Garcia, M.C., and Bazett-Jones, D.M. (2022). Validity of an artificial intelligence, human pose estimation model for measuring single-leg squat kinematics. J. Biomech., 144.","DOI":"10.1016\/j.jbiomech.2022.111333"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1238134","DOI":"10.3389\/fresc.2023.1238134","article-title":"Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system","volume":"4","author":"Menychtas","year":"2023","journal-title":"Front. Rehabil. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1272038","DOI":"10.3389\/fspor.2023.1272038","article-title":"Extracting proficiency differences and individual characteristics in golfers\u2019 swing using single-video markerless motion analysis","volume":"5","author":"Yamamoto","year":"2023","journal-title":"Front. Sports Act. Living"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"e12995","DOI":"10.7717\/peerj.12995","article-title":"Applications and limitations of current markerless motion capture methods for clinical gait biomechanics","volume":"10","author":"Wade","year":"2022","journal-title":"PeerJ"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2139","DOI":"10.1038\/s41598-022-05812-9","article-title":"Automatic real-time occupational posture evaluation and select corresponding ergonomic assessments","volume":"12","author":"Lin","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Moshayedi, A.J., Uddin, N.M.I., Khan, A.S., Zhu, J., and Emadi Andani, M. (2023). Designing and Developing a Vision-Based System to Investigate the Emotional Effects of News on Short Sleep at Noon: An Experimental Case Study. Sensors, 23.","DOI":"10.3390\/s23208422"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2100511","DOI":"10.1109\/JTEHM.2022.3180231","article-title":"Concurrent Validity of Zeno Instrumented Walkway and Video-Based Gait Features in Adults With Parkinson\u2019s Disease","volume":"10","author":"Sabo","year":"2022","journal-title":"IEEE J. Transl. Eng. Health Med."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1589","DOI":"10.1519\/JSC.0b013e318181a297","article-title":"Relationship between the kinetics and kinematics of a unilateral horizontal drop jump to sprint performance","volume":"22","author":"Holm","year":"2008","journal-title":"J. Strength. Cond. Res."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Needham, L., Evans, M., Cosker, D.P., and Colyer, S.L. (2021). Can Markerless Pose Estimation Algorithms Estimate 3D Mass Centre Positions and Velocities during Linear Sprinting Activities?. Sensors, 21.","DOI":"10.3390\/s21082889"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.autcon.2018.05.033","article-title":"Ergonomic posture recognition using 3D view-invariant features from single ordinary camera","volume":"94","author":"Zhang","year":"2018","journal-title":"Autom. Constr."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.gaitpost.2020.05.027","article-title":"Verification of reliability and validity of motion analysis systems during bilateral squat using human pose tracking algorithm","volume":"80","author":"Ota","year":"2020","journal-title":"Gait Posture"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"17064","DOI":"10.1109\/JSEN.2021.3081188","article-title":"Validation of a 3D Markerless System for Gait Analysis Based on OpenPose and Two RGB Webcams","volume":"21","author":"Taborri","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Liang, S., Zhang, Y., Diao, Y., Li, G., and Zhao, G. (2022). The reliability and validity of gait analysis system using 3D markerless pose estimation algorithms. Front. Bioeng. Biotechnol., 10.","DOI":"10.3389\/fbioe.2022.857975"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Zago, M., Luzzago, M., Marangoni, T., De Cecco, M., Tarabini, M., and Galli, M. (2020). 3D Tracking of Human Motion Using Visual Skeletonization and Stereoscopic Vision. Front. Bioeng. Biotechnol., 8.","DOI":"10.3389\/fbioe.2020.00181"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/j.gaitpost.2021.02.006","article-title":"Verification of validity of gait analysis systems during treadmill walking and running using human pose tracking algorithm","volume":"85","author":"Ota","year":"2021","journal-title":"Gait Posture"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Stenum, J., Rossi, C., and Roemmich, R.T. (2021). Two-dimensional video-based analysis of human gait using pose estimation. PLoS Comput. Biol., 17.","DOI":"10.1371\/journal.pcbi.1008935"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"784865","DOI":"10.3389\/fphys.2021.784865","article-title":"Development of a Robust, Simple, and Affordable Human Gait Analysis System Using Bottom-Up Pose Estimation with a Smartphone Camera","volume":"12","author":"Viswakumar","year":"2021","journal-title":"Front. Physiol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2666","DOI":"10.1109\/TNSRE.2021.3135879","article-title":"Accuracy of Temporo-Spatial and Lower Limb Joint Kinematics Parameters Using OpenPose for Various Gait Patterns With Orthosis","volume":"29","author":"Yamamoto","year":"2021","journal-title":"IEEE Trans. Neural Syst. Rehabil. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.3758\/BRM.41.4.1149","article-title":"Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses","volume":"41","author":"Faul","year":"2009","journal-title":"Behav. Res. Methods"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"175","DOI":"10.3758\/BF03193146","article-title":"G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences","volume":"39","author":"Faul","year":"2007","journal-title":"Behav. Res. Methods"},{"key":"ref_25","unstructured":"Cao, Z., Hidalgo Martinez, G., Simon, T., Wei, S.-E., and Sheikh, Y.A. (2019). OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields. arXiv."},{"key":"ref_26","unstructured":"(2023, December 11). Plug-In Gait Reference Guide\u2014Nexus Documentation, Vicon Documentation. Available online: https:\/\/docs.vicon.com\/display\/Nexus210\/Plug-in+Gait+Reference+Guide."},{"key":"ref_27","unstructured":"Fleiss, J.L. (1986). The Design and Analysis of Clinical Experiments, Wiley."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1080\/14763141.2019.1671486","article-title":"Validation of a new inertial measurement unit system based on different dynamic movements for future in-field applications","volume":"21","author":"Bessone","year":"2022","journal-title":"Sports Biomech."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.gaitpost.2008.09.003","article-title":"The reliability of three-dimensional kinematic gait measurements: A systematic review","volume":"29","author":"McGinley","year":"2009","journal-title":"Gait Posture"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"540","DOI":"10.1016\/j.gaitpost.2010.02.009","article-title":"A new formulation of the coefficient of multiple correlation to assess the similarity of waveforms measured synchronously by different motion analysis protocols","volume":"31","author":"Ferrari","year":"2010","journal-title":"Gait Posture"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11517-009-0544-y","article-title":"First in vivo assessment of \u201cOutwalk\u201d: A novel protocol for clinical gait analysis based on inertial and magnetic sensors","volume":"48","author":"Ferrari","year":"2010","journal-title":"Med. Biol. Eng. Comput."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Ishida, T., and Samukawa, M. (2023). Validity and Reliability of a Wearable Goniometer Sensor Controlled by a Mobile Application for Measuring Knee Flexion\/Extension Angle during the Gait Cycle. Sensors, 23.","DOI":"10.3390\/s23063266"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Rivera, B., Cano, C., Luis, I., and Elias, D.A. (2022). A 3D-Printed Knee Wearable Goniometer with a Mobile-App Interface for Measuring Range of Motion and Monitoring Activities. Sensors, 22.","DOI":"10.3390\/s22030763"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.jbiomech.2017.03.015","article-title":"Measuring joint kinematics of treadmill walking and running: Comparison between an inertial sensor based system and a camera-based system","volume":"57","author":"Nuesch","year":"2017","journal-title":"J. Biomech."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Shuai, Z., Dong, A., Liu, H., and Cui, Y. (2022). Reliability and Validity of an Inertial Measurement System to Quantify Lower Extremity Joint Angle in Functional Movements. Sensors, 22.","DOI":"10.3390\/s22030863"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Pourtabib, J., and Hull, M.L. (2023). Joint Coordinate System Using Functional Axes Achieves Clinically Meaningful Kinematics of the Tibiofemoral Joint as Compared to the International Society of Biomechanics Recommendation. J. Biomech. Eng., 145.","DOI":"10.1115\/1.4056654"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.gaitpost.2022.01.017","article-title":"Relationship between the locomotive syndrome and kinetic and kinematic parameters during static standing and level walking","volume":"93","author":"Nishizawa","year":"2022","journal-title":"Gait Posture"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Saito, Y., Ishida, T., Kataoka, Y., Takeda, R., Tadano, S., Suzuki, T., Nakamura, K., Nakata, A., Osuka, S., and Yamada, S. (2022). Evaluation of gait characteristics in subjects with locomotive syndrome using wearable gait sensors. BMC Musculoskelet. Disord., 23.","DOI":"10.1186\/s12891-022-05411-9"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Martini, E., Boldo, M., Aldegheri, S., Vale, N., Filippetti, M., Smania, N., Bertucco, M., Picelli, A., and Bombieri, N. (2022). Enabling Gait Analysis in the Telemedicine Practice through Portable and Accurate 3D Human Pose Estimation. Comput. Methods Programs Biomed., 225.","DOI":"10.1016\/j.cmpb.2022.107016"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/24\/9799\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:37:58Z","timestamp":1760132278000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/24\/9799"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,13]]},"references-count":39,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["s23249799"],"URL":"https:\/\/doi.org\/10.3390\/s23249799","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,13]]}}}