ArticleSensors (Basel, Switzerland)2024
Validation of Automated Countermovement Vertical Jump Analysis: Markerless Pose Estimation vs. 3D Marker-Based Motion Capture System.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy and Validity of 3D Markerless Motion Capture Compared to Marker-Based Systems for Lower-Limb Biomechanical Assessment: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Agreement between markerless and marker-based motion capture for knee kinematics and kinetics during functional activities in knee osteoarthritis.Osteoarthritis and cartilage open · 2026Article
- A smart monocular vision metrology system based on computer for standing long jump.Scientific reports · 2026Article
- A real time action scoring system for movement analysis and feedback in physical therapy using human pose estimation.Scientific reports · 2025Article
- From Laboratory to Field: Concurrent Validity of Kinovea's Linear Kinematics Tracking Tool for Semi-Automated Countermovement Jump Analysis.Sensors (Basel, Switzerland) · 2025Article
- Validity and Reliability of a Novel AI-Based System in Athletic Performance Assessment: The Case of DeepSport.Sensors (Basel, Switzerland) · 2025Article
- Motion Capture Technologies for Athletic Performance Enhancement and Injury Risk Assessment: A Review for Multi-Sport Organizations.Sensors (Basel, Switzerland) · 2025Review
- Anterior Cruciate Ligament Return to Play: "A Framework for Decision Making".Journal of clinical medicine · 2025Article
- Advancing Field-Based Vertical Jump Analysis: Markerless Pose Estimation vs. Force Plates.Life (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
7 authors.
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Abstract
This study aimed to validate the automated temporal analysis of countermovement vertical jump (CMJ) using MMPose, a markerless pose estimation framework, by comparing it with the gold-standard 3D marker-based motion capture system. Twelve participants performed five CMJ trials, which were simultaneously recorded using the marker-based system and two smartphone cameras capturing both sides of the body. Key kinematic points, including center of mass (CoM) and toe trajectories, were analyzed to determine jump phases and temporal variables. The agreement between methods was assessed using Bland-Altman analysis, root mean square error (RMSE), and Pearson's correlation coefficient (r), while consistency was evaluated via intraclass correlation coefficient (ICC 3,1) and two-way repeated-measures ANOVA. Cohen's effect size (d) quantified the practical significance of differences. Results showed strong agreement (r > 0.98) with minimal bias and narrow limits of agreement for most variables. The markerless system slightly overestimated jump height and CoM vertical velocity, but ICC values (ICC > 0.91) confirmed strong reliability. Cohen's d values were near zero, indicating trivial differences, and no variability due to recording side was observed. Overall, MMPose proved to be a reliable alternative for in-field CMJ analysis, supporting its broader application in sports and rehabilitation settings.
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