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Pubmed for Handhelds
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Journal Abstract Search
373 related items for PubMed ID: 33891585
21. The reliability and validity of gait analysis system using 3D markerless pose estimation algorithms. Liang S, Zhang Y, Diao Y, Li G, Zhao G. Front Bioeng Biotechnol; 2022; 10():857975. PubMed ID: 36032709 [Abstract] [Full Text] [Related]
23. Evaluation of 3D Markerless Motion Capture Accuracy Using OpenPose With Multiple Video Cameras. Nakano N, Sakura T, Ueda K, Omura L, Kimura A, Iino Y, Fukashiro S, Yoshioka S. Front Sports Act Living; 2020; 2():50. PubMed ID: 33345042 [Abstract] [Full Text] [Related]
32. Comparison of Azure Kinect overground gait spatiotemporal parameters to marker based optical motion capture. Guess TM, Bliss R, Hall JB, Kiselica AM. Gait Posture; 2022 Jul; 96():130-136. PubMed ID: 35635988 [Abstract] [Full Text] [Related]
33. A novel dataset and deep learning-based approach for marker-less motion capture during gait. Vafadar S, Skalli W, Bonnet-Lebrun A, Khalifé M, Renaudin M, Hamza A, Gajny L. Gait Posture; 2021 May; 86():70-76. PubMed ID: 33711613 [Abstract] [Full Text] [Related]
37. Validity of artificial intelligence-based markerless motion capture system for clinical gait analysis: Spatiotemporal results in healthy adults and adults with Parkinson's disease. Ripic Z, Signorile JF, Best TM, Jacobs KA, Nienhuis M, Whitelaw C, Moenning C, Eltoukhy M. J Biomech; 2023 Jun; 155():111645. PubMed ID: 37216895 [Abstract] [Full Text] [Related]
38. Verification of gait analysis method fusing camera-based pose estimation and an IMU sensor in various gait conditions. Yamamoto M, Shimatani K, Ishige Y, Takemura H. Sci Rep; 2022 Oct 21; 12(1):17719. PubMed ID: 36271241 [Abstract] [Full Text] [Related]
40. A comparison of three-dimensional kinematics between markerless and marker-based motion capture in overground gait. Ripic Z, Nienhuis M, Signorile JF, Best TM, Jacobs KA, Eltoukhy M. J Biomech; 2023 Oct 21; 159():111793. PubMed ID: 37725886 [Abstract] [Full Text] [Related] Page: [Previous] [Next] [New Search]