ArticleBehavior research methods2025
How accurately can we estimate spontaneous body kinematics from video recordings? Effect of movement amplitude on OpenPose accuracy.
Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- IMU- and Vision-Based Measurement Techniques for Joint Kinematics: A Narrative Review.Sensors (Basel, Switzerland) · 2026Review
- Inverse Dynamics Meets Markerless Motion Capture during Standing: Concurrent Validation of Center of Mass and Center of Pressure Estimations.Annals of biomedical engineering · 2026Article
- Quantitative Assessment of Lower-Limb Multi-joint Synergy in Knee Osteoarthritis by Integrating Spatiotemporal Dual-Topology Features Under the HSMR Framework.Annals of biomedical engineering · 2026Article
- Application of a spatiotemporal distribution-based multidimensional gait feature algorithm in KOA gait assessment.Medical & biological engineering & computing · 2026Article
- Artificial Intelligence-Enhanced Flexible Sensors for Human Motion and Posture Sensing.Sensors (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Estimating how the human body moves in space and time-body kinematics-has important applications for industry, healthcare, and several research fields. Gold-standard methodologies capturing body kinematics are expensive and impractical for naturalistic recordings as they rely on infrared-reflective wearables and bulky instrumentation. To overcome these limitations, several algorithms have been developed to extract body kinematics from plain video recordings. This comes with a drop in accuracy, which however has not been clearly quantified. To fill this knowledge gap, we analysed a dataset comprising 46 human participants exhibiting spontaneous movements of varying amplitude. Body kinematics were estimated using OpenPose (video-based) and Vicon (infrared-based) motion capture systems simultaneously. OpenPose accuracy was assessed using Vicon estimates as ground truth. We report that OpenPose accuracy is overall moderate and varies substantially across participants and body parts. This is explained by variability in movement amplitude. OpenPose estimates are weak for low-amplitude movements. Conversely, large-amplitude movements (i.e., > ~ 10 cm) yield highly accurate estimates. The relationship between accuracy and movement amplitude is not linear (but mostly exponential or power) and relatively robust to camera-body distance. Together, these results dissect the limits of video-based motion capture and provide useful guidelines for future studies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.