ArticleJournal of sports science & medicine2024
Validity and Reliability of OpenPose-Based Motion Analysis in Measuring Knee Valgus during Drop Vertical Jump Test.
Article in Journal of sports science & medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Validations and applications of markerless motion capture using OpenCap: a scoping review.Frontiers in digital health · 2026Pooled it
- The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms.Journal of evaluation in clinical practice · 2026Review
- Comparison of KAFO and AFO for extension thrust pattern after stroke: a randomized N-of-1 trial.Journal of physical therapy science · 2026Article
- Motion Analysis Technologies for ACL Injury Prevention: From Laboratory Assessment to Field-Based Clinical Screening.Journal of clinical medicine · 2026Review
- Assessment of dynamic knee angle deviations in the frontal plane in physiotherapy clinical practice: intra- and inter-rater reliability of an application and agreement with two AI-models.BMC musculoskeletal disorders · 2026Article
- Quality over quantity: joint group dance strengthens schoolchildren's social connections and wellbeing.Frontiers in cognition · 2026Article
- Lightweight deep learning technology for high quality development and intelligent transformation of sports under DeepLabV3 CSP Darknet53 model.Scientific reports · 2025Article
- OpenCap vs. LESS: Sport-Specific Profiling of Dynamic Knee Valgus.Journal of clinical medicine · 2025Article
- duet: An R package for dyadic analysis of motion data generated by OpenPose.Behavior research methods · 2025Article
- Validation of the Comprehensive Augmented Reality Testing Platform to Quantify Parkinson's Disease Fine Motor Performance.Journal of clinical medicine · 2025Article
- Influence of the Camera Viewing Angle on OpenPose Validity in Motion Analysis.Sensors (Basel, Switzerland) · 2025Article
- Commercial vision sensors and AI-based pose estimation frameworks for markerless motion analysis in sports and exercises: a mini review.Frontiers in physiology · 2025Review
- Between-Day Reliability of Kinematic Variables Using Markerless Motion Capture for Single-Leg Squat and Single-Leg Landing Tasks.International journal of sports physical therapy · 2025Article
Corrections and comments
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7 authors.
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Abstract
OpenPose-based motion analysis (OpenPose-MA), utilizing deep learning methods, has emerged as a compelling technique for estimating human motion. It addresses the drawbacks associated with conventional three-dimensional motion analysis (3D-MA) and human visual detection-based motion analysis (Human-MA), including costly equipment, time-consuming analysis, and restricted experimental settings. This study aims to assess the precision of OpenPose-MA in comparison to Human-MA, using 3D-MA as the reference standard. The study involved a cohort of 21 young and healthy adults. OpenPose-MA employed the OpenPose algorithm, a deep learning-based open-source two-dimensional (2D) pose estimation method. Human-MA was conducted by a skilled physiotherapist. The knee valgus angle during a drop vertical jump task was computed by OpenPose-MA and Human-MA using the same frontal-plane video image, with 3D-MA serving as the reference standard. Various metrics were utilized to assess the reproducibility, accuracy and similarity of the knee valgus angle between the different methods, including the intraclass correlation coefficient (ICC) (1, 3), mean absolute error (MAE), coefficient of multiple correlation (CMC) for waveform pattern similarity, and Pearson's correlation coefficients (OpenPose-MA vs. 3D-MA, Human-MA vs. 3D-MA). Unpaired t-tests were conducted to compare MAEs and CMCs between OpenPose-MA and Human-MA. The ICCs (1,3) for OpenPose-MA, Human-MA, and 3D-MA demonstrated excellent reproducibility in the DVJ trial. No significant difference between OpenPose-MA and Human-MA was observed in terms of the MAEs (OpenPose: 2.4° [95%CI: 1.9-3.0°], Human: 3.2° [95%CI: 2.1-4.4°]) or CMCs (OpenPose: 0.83 [range: 0.99-0.53], Human: 0.87 [range: 0.24-0.98]) of knee valgus angles. The Pearson's correlation coefficients of OpenPose-MA and Human-MA relative to that of 3D-MA were 0.97 and 0.98, respectively. This study demonstrated that OpenPose-MA achieved satisfactory reproducibility, accuracy and exhibited waveform similarity comparable to 3D-MA, similar to Human-MA. Both OpenPose-MA and Human-MA showed a strong correlation with 3D-MA in terms of knee valgus angle excursion.
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