Feasibility of a Markerless Motion Capture System for Estimating Ground Reaction Forces During Vertical Jump and Landing Tasks
DOI:
https://doi.org/10.12775/JEHS.2026.93.73559Keywords
OpenCap; markerless motion capture; ground reaction force; vertical jump; landingAbstract
Background: Vertical ground reaction force is an important kinetic variable for evaluating the biomechanical characteristics of vertical jump and landing tasks and is widely used in performance assessment and injury-risk screening.
Aim: To investigate the feasibility of the OpenCap markerless motion capture system for estimating vertical GRF during vertical jump and landing tasks.
Material and methods: Eighteen physical education students participated in this study. Kinematic data were collected using OpenCap, and vertical GRF was estimated from whole-body center-of-mass acceleration based on Newton's second law. Estimated GRF was compared with force plate measurements. Phase duration, peak force, mean force, and impulse variables were extracted. Pearson correlation and Bland-Altman analyses were used to assess validity.
Results: Strong correlations were observed between OpenCap-estimated and force plate-measured GRF variables. Temporal, impulse, and mean force variables showed moderate-to-very high correlations (r = 0.62–0.94). Bland-Altman analysis indicated biases below 5% for temporal and impulse variables, while biases for propulsive-phase mean and peak force ranged from 5% to 15%. However, peak landing force showed a bias exceeding 40%, indicating substantial underestimation.
Conclusions: OpenCap provides a feasible method for estimating vertical GRF during vertical jump and landing tasks and may support large-scale movement assessment. However, peak landing force is substantially underestimated and should be interpreted with caution.
References
Barker, L. A., Harry, J. R. & Mercer, J. A. (2018). Relationships between countermovement jump ground reaction forces and jump height, reactive strength index, and jump time. Journal of Strength & Conditioning Research, 32(1), 248–268. https://doi.org/10.1519/JSC.0000000000002160
Bates, N. A., Ford, K. R., Myer, G. D. & Hewett, T. E. (2013). Impact differences in ground reaction force and center of mass between the first and second landing phases of a drop vertical jump and their implications for injury risk assessment. Journal of Biomechanics, 46(7), 1237–1241. https://doi.org/10.1016/j.jbiomech.2013.02.024
Bobbert, M. F., Schamhardt, H. C. & Nigg, B. M. (1991). Calculation of vertical ground reaction force estimates during running from positional data. Journal of Biomechanics, 24(12), 1095–1105. https://doi.org/10.1016/0021-9290(91)90002-5
Cheng, X., Jiao, Y., Meiring, R. M., Sheng, B. & Zhang, Y. (2025). Reliability and validity of current computer vision based motion capture systems in gait analysis: a systematic review. Gait and Posture, 120, 150–160. https://doi.org/10.1016/j.gaitpost.2025.04.016
FENG Ru, YANG Chen, LI Hanjun, & LIU Hui. (2021). Application of Machine‐Learning in Predicting Ground Reaction Force of Human Motion: A Review. Journal of Data Acquisition and Processing, 36(4), 639–647. https://doi.org/10.16337/j.1004-9037.2021.04.002
Halson, S. L. (2014). Monitoring training load to understand fatigue in athletes. Sports Medicine, 44 Suppl 2(Suppl 2), S139-147. https://doi.org/10.1007/s40279-014-0253-z
Huang, Y.-T., Chen, S.-H., Chen, C.-Y., Wang, S.-M., Wu, P.-Y., Lai, D.-M. & Hsu, W.-L. (2025). Evaluating degenerative lumbar disease with markerless 3D motion capture: reliability and validity in sit-to-stand test. Sensors, 25(10), 3122. https://doi.org/10.3390/s25103122
Ishikawa, M. & Komi, P. V. (2004). Effects of different dropping intensities on fascicle and tendinous tissue behavior during stretch-shortening cycle exercise. Journal of Applied Physiology, 96(3), 848–852. https://doi.org/10.1152/japplphysiol.00948.2003
Kirby, T. J., McBride, J. M., Haines, T. L. & Dayne, A. M. (2011). Relative net vertical impulse determines jumping performance. Journal of Applied Biomechanics, 27(3), 207–214. https://doi.org/10.1123/jab.27.3.207
Lima, Y. L., Collings, T., Hall, M., Bourne, M. N. & Diamond, L. E. (2024). Validity and reliability of trunk and lower-limb kinematics during squatting, hopping, jumping and side-stepping using OpenCap markerless motion capture application. Journal of Sports Sciences, 42(19), 1847–1858. https://doi.org/10.1080/02640414.2024.2415233
Markovic, G., Dizdar, D., Jukic, I. & Cardinale, M. (2004). Reliability and factorial validity of squat and countermovement jump tests. Journal of Strength & Conditioning Research, 18(3), 551–555. https://doi.org/10.1519/1533-4287(2004)18<551:RAFVOS>2.0.CO;2
Martin Bland, J. & Altman, DouglasG. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, 327(8476), 307–310. https://doi.org/10.1016/S0140-6736(86)90837-8
Mylonas, V., Chalitsios, C. & Nikodelis, T. (2023). Validation of a portable wireless force platform system to measure ground reaction forces during various tasks. International Journal of Sports Physical Therapy, 18(6), 1283–1289. https://doi.org/10.26603/001c.89261
Niu, W., Feng, T., Jiang, C. & Zhang, M. (2014). Peak vertical ground reaction force during two-leg landing: a systematic review and mathematical modeling. Biomed Research International, 2014, 126860. https://doi.org/10.1155/2014/126860
Peng, Y., Wang, W., Wang, L., Zhou, H., Chen, Z., Zhang, Q. & Li, G. (2024). Smartphone videos-driven musculoskeletal multibody dynamics modelling workflow to estimate the lower limb joint contact forces and ground reaction forces. Medical and Biological Engineering and Computing, 62(12), 3841–3853. https://doi.org/10.1007/s11517-024-03171-3
Ryan, W., Harrison, A. & Hayes, K. (2006). Functional data analysis of knee joint kinematics in the vertical jump. Sports Biomechanics, 5(1), 121–138. https://doi.org/10.1080/14763141.2006.9628228
Thornton, H. R., Delaney, J. A., Duthie, G. M. & Dascombe, B. J. (2019). Developing athlete monitoring systems in team sports: data analysis and visualization. International Journal of Sports Physiology and Performance, 14(6), 698–705. https://doi.org/10.1123/ijspp.2018-0169
Thorpe, R. T., Atkinson, G., Drust, B. & Gregson, W. (2017). Monitoring fatigue status in elite team-sport athletes: implications for practice. International Journal of Sports Physiology and Performance, 12(Suppl 2), S227–S234. https://doi.org/10.1123/ijspp.2016-0434
Uhlrich, S. D., Falisse, A., Kidziński, Ł., Muccini, J., Ko, M., Chaudhari, A. S., Hicks, J. L. & Delp, S. L. (2023). OpenCap: human movement dynamics from smartphone videos. PLOS Computational Biology, 19(10), e1011462. https://doi.org/10.1371/journal.pcbi.1011462
Verheul, J., Robinson, M. A. & Burton, S. (2024). Jumping towards field-based ground reaction force estimation and assessment with OpenCap. Journal of Biomechanics, 166, 112044. https://doi.org/10.1016/j.jbiomech.2024.112044
Xu, J.-J., Xu, Y., Shi, P.-F., Shao, A., Pan, J.-T., Ren, X.-P., Wang, S.-J., Zhou, Y.-W., Jiang, L.-P. & Yang, Q.-N. (2025). Quantifying gait compensation in knee osteoarthritis using smartphone-based motion capture (OpenCap). Frontiers in Sports and Active Living, 7, 1674133. https://doi.org/10.3389/fspor.2025.1674133
You, J., Lin, Z. & Zhang, B. (2026). Estimation of vertical ground reaction forces during vertical jumping in children using OpenCap. Sensors, 26(11), 3375. https://doi.org/10.3390/s26113375
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 JiongYi You, Zhicheng Lin, Baifa Zhang

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The periodical offers access to content in the Open Access system under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0
Stats
Number of views and downloads: 6
Number of citations: 0