Accuracy of Kinovea software in estimating body segment movements during falls captured on standard video: Effects of fall direction, camera perspective and video calibration technique
Open accessAbstract
Falls are a major cause of unintentional injuries. Understanding the movements of the body during falls is important to the design of fall prevention and management strategies, including exercise programs, mobility aids, fall detectors, protective gear, and safer environments. Video footage of real-life falls is increasingly available, and may be used with digitization software to extract kinematic features of falls. We examined the validity of this approach by conducting laboratory falling experiments, and comparing linear and angular positions and velocities measured from 3D motion capture to estimates from Kinovea 2D digitization software based on standard surveillance video (30 Hz, 640x480 pixels). We also examined how Kinovea accuracy depended on fall direction, camera angle, filtering cut-off frequency, and calibration technique. For a camera oriented perpendicular to the plane of the fall (90 degrees), Kinovea position data filtered at 10 Hz, and video calibration using a 2D grid, mean root mean square errors were 0.050 m or 9% of the signal amplitude and 0.22 m/s (7%) for vertical position and velocity, and 0.035 m (6%) and 0.16 m/s (7%) for horizontal position and velocity. Errors in angular measures averaged over 2-fold higher in sideways than forward or backward falls, due to out-of-plane movement of the knees and elbows. Errors in horizontal velocity were 2.5-fold higher for a 30 than 90 degree camera angle, and 1.6-fold higher for calibration using participants’ height (1D) instead of a 2D grid. When compared to 10 Hz, filtering at 3 Hz caused velocity errors to increase 1.4-fold. Our results demonstrate that Kinovea can be applied to 30 Hz video to measure linear positions and velocities to within 9% accuracy. Lower accuracy was observed for angular kinematics of the upper and lower limb in sideways falls, and for horizontal measures from 30 degree cameras or 1D height-based calibration.
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Positioning the head near the edges of the camera's field of view may have increased errors due to parallax or spherical lens distortion compared to segments located closer to the center of the frame.
“positioning the head near the edges of the camera’s field of view may have increased errors due to parallax or spherical lens distortion compared to the segments located closer to the center of the frame (e.g., pelvis and knee) [48,57].”
From Intra-Rater and Test–Retest Reliability of Kinovea for the Kinematic Analysis of Squatting in Healthy Active Women (2026) · cites this paper as [57]
The Discussion (page not available in our copy) says uncorrected camera lens distortion may have affected measurements, particularly for body parts at the edges of the video image. It does not specifically identify the head, compare it with the pelvis or knee near the frame center, or name parallax or spherical lens distortion as the cause. (LLM, conf=0.84)
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Wang, P., Xu, Y., Li, Y., Chen, C., & Hidayat, R. (2026) · Frontiers in Sports and Active Living · doi:10.3389/fspor.2026.1834844
Dehghan, P., Azadi, A., Karton, C., Clouthier, A., & Hoshizaki, T. B. (2026) · Sports Engineering · doi:10.1007/s12283-026-00559-2
Michaels, R., Ehrlich, J., Mei, Y., Son, J., Robinovitch, S. N., Sosnoff, J. J., & Moon, Y. (2026) · PLoS ONE · doi:10.1371/journal.pone.0335108
Self-citationPuh, U., Čelofiga, N., & Deutsch, J. E. (2026) · JMIR Serious Games · doi:10.2196/88179 · Cited by 1 · see citing works
3D kinematics of human falls: evaluating opencap and SAM3D body against inertial motion capture
Ferrari, D., Regazzoni, D., Rizzi, C., & Vitali, A. (2026) · International Journal on Interactive Design and Manufacturing (IJIDeM) · doi:10.1007/s12008-026-02653-y
- Authors
- Shishov, N., Elabd, K., Komisar, V., Chong, H., & Robinovitch, S. N.
- Affiliations
- Simon Fraser University (CA)
- University of British Columbia (CA)
- Corresponding author
- Shishov, Nataliya
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2021-10-25
- Volume
- 16
- Issue
- 10
- Pages
- e0258923
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC8544843
- OpenAlex
- W3209806666
- Cited by
- 42
- References
- 52
- Citations by year
- 2026: 11 · 2025: 11 · 2024: 5 · 2023: 8 · 2022: 7
- FWCI
- 9.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Summit (Simon Fraser University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Summit (Simon Fraser University) (submittedVersion, cc-by)
- Funders
- Canadian Institutes of Health Research (AMG-100487, TIR-103945, TEI-138295, Community Support Travel Award 164472, Community Support Travel Award 164465)
- AGE-WELL (AW CRP 2015-WP5.2, AWCRP-2020-04, Graduate Student Award in Technology and Aging, Postdoctoral Awards in Technology and Aging)
- Simon Fraser University (Graduate Dean’s Entrance Scholarship)
- Michael Smith Foundation for Health Research (18481)
- Topics
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Physical Sciences › Engineering › Biomedical Engineering › Sports Dynamics and Biomechanics
- Physical Sciences › Engineering › Biomedical Engineering › Lower Extremity Biomechanics and Pathologies
- Keywords
- Kinovea, fall direction, camera angles, measurement accuracy, fall prevention, angular kinematics
- MeSH terms
- Accidental Falls, Adult, Biomechanical Phenomena, Female, Humans, Male, Movement, Software, Video Recording, Young Adult
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