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Can BlazePose accurately assess joint angles in outdoor running environments?

Open Access
|Jan 2025

References

  1. Baker, R. (2006). Gait analysis methods in rehabilitation. Journal of NeuroEngineering and Rehabilitation, 3(1), 4. https://doi.org/10.1186/1743-0003-3-4
  2. Balsalobre-Fernández, C., Tejero-González, C. M., Campo-Vecino, J. Del, & Bavaresco, N. (2014). The concurrent validity and reliability of a low-cost, highspeed camera-based method for measuring the flight time of vertical jumps. Journal of Strength and Conditioning Research, 28(2), 528–533. https://doi.org/10.1519/JSC.0b013e318299a52e
  3. Bazarevsky, V., Grishchenko, I., Raveendran, K., Zhu, T., Zhang, F., & Grundmann, M. (2020). BlazePose: Ondevice Real-time Body Pose tracking (p. 10204). arXiv. https://doi.org/10.48550/arXiv.2006.10204
  4. Buck, P., Morrey, B. F., & Chao, E. Y. (1987). The optimum position of arthrodesis of the ankle. A gait study of the knee and ankle. Journal of Bone & Joint Surgery, 69(7), 1052. https://journals.lww.com/jbjsjournal/abstract/1987/69070/the_optimum_position_of_arthrodesis_of_the_ankle_.14.aspx
  5. Cao, Z., Hidalgo, G., Simon, T., Wei, S.-E., & Sheikh, Y. (2021). OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(1), 172–186. https://doi.org/10.1109/TPAMI.2019.2929257
  6. Chung, M.-J., & Wang, M.-J. J. (2010). The change of gait parameters during walking at different percentage of preferred walking speed for healthy adults aged 20–60 years. Gait & Posture, 31(1), 131–135. https://doi.org/10.1016/j.gaitpost.2009.09.013
  7. Cronin, N. J. (2021). Using deep neural networks for kinematic analysis: Challenges and opportunities. Journal of Biomechanics, 123, 110460. https://doi.org/10.1016/j.jbiomech.2021.110460
  8. Dingenen, B., Malliaras, P., Janssen, T., Ceyssens, L., Vanelderen, R., & Barton, C. J. (2019). Two-dimensional video analysis can discriminate differences in running kinematics between recreational runners with and without running-related knee injury. Physical Therapy in Sport, 38, 184–191. https://doi.org/10.1016/j.ptsp.2019.05.008
  9. Dingenen, B., Staes, F., Vanelderen, R., Ceyssens, L., Malliaras, P., Barton, C. J., & Deschamps, K. (2020). Subclassification of recreational runners with a runningrelated injury based on running kinematics evaluated with marker-based two-dimensional video analysis. Physical Therapy in Sport, 44, 99–106. https://doi.org/10.1016/j.ptsp.2020.04.032
  10. Falbriard, M., Meyer, F., Mariani, B., Millet, G. P., & Aminian, K. (2018). Accurate Estimation of Running Temporal Parameters Using Foot-Worn Inertial Sensors. Frontiers in Physiology, 9. https://doi.org/10.3389/fphys.2018.00610
  11. Folland, J. P., Allen, S. J., Black, M. I., Handsaker, J. C., & Forrester, S. E. (2017). Running Technique is an Important Component of Running Economy and Performance. Medicine and Science in Sports and Exercise, 49(7), 1412–1423. https://doi.org/10.1249/MSS.0000000000001245
  12. Francis, P., Whatman, C., Sheerin, K., Hume, P., & Johnson, M. I. (2019). The Proportion of Lower Limb Running Injuries by Gender, Anatomical Location and Specific Pathology: A Systematic Review. Journal of Sports Science & Medicine, 18(1), 21–31. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370968/
  13. Gajdosik, R. L., & Bohannon, R. W. (1987). Clinical measurement of range of motion. Review of goniometry emphasizing reliability and validity. Physical Therapy, 67(12), 1867–1872. https://doi.org/10.1093/ptj/67.12.1867
  14. Hensley, C. P., Millican, D., Hamilton, N., Yang, A., Lee, J., & Chang, A. H. (2020). Video-Based Motion Analysis Use: A National Survey of Orthopedic Physical Therapists. Physical Therapy, 100(10), 1759–1770. https://doi.org/10.1093/ptj/pzaa125
  15. Itokazu, M. (2022). Reliability and accuracy of 2D lower limb joint angles during a standing-up motion for markerless motion analysis software using deep learning. Medicine in Novel Technology and Devices, 16, 100188. https://doi.org/10.1016/j.medntd.2022.100188
  16. Keller, V. T., Outerleys, J. B., Kanko, R. M., Laende, E. K., & Deluzio, K. J. (2022). Clothing condition does not affect meaningful clinical interpretation in markerless motion capture. Journal of Biomechanics, 141(1), 111182. https://doi.org/10.1016/j.jbiomech.2022.111182
  17. Littrell, M. E., Chang, Y.-H., & Selgrade, B. P. (2018). Development and Assessment of a Low-Cost Clinical Gait Analysis System. Journal of Applied Biomechanics, 34(6), 503–508. https://doi.org/10.1123/jab.2017-0370
  18. Lu, Z., Nazari, G., MacDermid, J. C., Modarresi, S., & Killip, S. (2020). Measurement Properties of a 2-Dimensional Movement Analysis System: A Systematic Review and Meta-analysis. Archives of Physical Medicine and Rehabilitation, 101(9), 1603–1627. https://doi.org/10.1016/j.apmr.2020.02.011
  19. Mathis, A., Schneider, S., Lauer, J., & Mathis, M. W. (2020). A Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives. Neuron, 108(1), 44–65. https://doi.org/10.1016/j.neuron.2020.09.017
  20. Mathunny, J. J., Karthik, V., Devaraj, A., & Hari Krishnan, S. (2021). Reliability of Kinovea software in measuring spatial parameters associated with perturbation training. 2021 International Conference on Computational Performance Evaluation (ComPE), 750–754. https://doi.org/10.1109/ComPE53109.2021.9752118
  21. Neal, B. S., Lack, S. D., Barton, C. J., Birn-Jeffery, A., Miller, S., & Morrissey, D. (2020). Is markerless, smart phone recorded two-dimensional video a clinically useful measure of relevant lower limb kinematics in runners with patellofemoral pain? A validity and reliability study. Physical Therapy in Sport: Official Journal of the Association of Chartered Physiotherapists in Sports Medicine, 43, 36–42. https://doi.org/10.1016/j.ptsp.2020.02.004
  22. Needham, L., Evans, M., Cosker, D. P., Wade, L., McGuigan, P. M., Bilzon, J. L., & Colyer, S. L. (2021). The accuracy of several pose estimation methods for 3D joint centre localisation. Scientific Reports, 11(1), 20673. https://doi.org/10.1038/s41598-021-00212-x
  23. Ota, M., Tateuchi, H., Hashiguchi, T., Kato, T., Ogino, Y., Yamagata, M., & Ichihashi, N. (2020). Verification of reliability and validity of motion analysis systems during bilateral squat using human pose tracking algorithm. Gait and Posture, 80(November 2019), 62–67. https://doi.org/10.1016/j.gaitpost.2020.05.027
  24. Phinyomark, A., Osis, S., Hettinga, B. A., & Ferber, R. (2015). Kinematic gait patterns in healthy runners: A hierarchical cluster analysis. Journal of Biomechanics, 48(14), 3897–3904. https://doi.org/10.1016/j.jbiomech.2015.09.025
  25. Puig-divı, A., Escalona-marfil, C., Padulle´s-Riu, J. M., Busquets, A., Padulle´s-Chando, X., & Marcos-ruiz, D. (2019). Validity and reliability of the Kinovea program in obtaining angles and distances using coordinates in 4 perspectives. PLOS One, Icc, 1–14. https://doi.org/10.1371/journal.pone.0216448
  26. Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012). NIH Image to ImageJ: 25 years of image analysis. Nature Methods, 9(7), 671–675. https://doi.org/10.1038/nmeth.2089
  27. Simon, S. R. (2004). Quantification of human motion: gait analysis-benefits and limitations to its application to clinical problems. Journal of Biomechanics, 37(12), 1869–1880. https://doi.org/10.1016/j.jbiomech.2004.02.047
  28. Souza, R. B. (2016). An Evidence-Based Videotaped Running Biomechanics Analysis. Physical Medicine and Rehabilitation Clinics of North America, 27(1), 217–236. https://doi.org/10.1016/j.pmr.2015.08.006
  29. Stephens, J., Bostjancic, M., & Koskulitz, T. (2019). A Study on Parallax Error in Video Analysis. The Physics Teacher, 57(3), 193–195. https://doi.org/10.1119/1.5092485
  30. Taunton, J. E., Ryan, M. B., Clement, D. B., McKenzie, D. C., Lloyd-Smith, D. R., & Zumbo, B. D. (2002). A retrospective case-control analysis of 2002 running injuries. British Journal of Sports Medicine, 36(2), 95–101. https://doi.org/10.1136/bjsm.36.2.95
  31. van der Kruk, E., & Reijne, M. M. (2018). Accuracy of human motion capture systems for sport applications; state-of-the-art review. European Journal of Sport Science, 18(6), 806–819. https://doi.org/10.1080/17461391.2018.1463397
  32. WorldMedical Association Declaration ofHelsinki Ethical Principles for Medical Research Involving Human Subjects. (2013). JAMA, 310(20), 2191. https://doi.org/10.1001/jama.2013.281053
  33. Zhou, H., & Hu, H. (2008). Human motion tracking for rehabilitation-A survey. Biomedical Signal Processing and Control, 3(1), 1–18. https://doi.org/10.1016/j.bspc.2007.09.001
  34. Zult, T., Allsop, J., Tabernero, J., & Pardhan, S. (2019). A low-cost 2-D video system can accurately and reliably assess adaptive gait kinematics in healthy and low vision subjects. Scientific Reports, 9(1), 1–11. https://doi.org/10.1038/s41598-019-54913-5
Language: English
Page range: 13 - 25
Submitted on: Jul 17, 2024
Accepted on: Dec 16, 2024
Published on: Jan 30, 2025
Published by: University of Physical Education in Warsaw
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Hari Krishnan Srinivasan, Jaison Jacob Mathunny, Ashokkumar Devaraj, Hemantajit Gogoi, Karuppasamy Govindasamy, Varshini Karthik, published by University of Physical Education in Warsaw
This work is licensed under the Creative Commons Attribution 4.0 License.