ArticleJournal of athletic training2021
Validation of a Commercially Available Markerless Motion-Capture System for Trunk and Lower Extremity Kinematics During a Jump-Landing Assessment.
Article in Journal of athletic training, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- 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
- Bridging postural biomechanics and knee arthroplasty success.Arthroplasty (London, England) · 2026Review
- Comparison of hip and knee range of motion measurements using Azure Kinect and a digital goniometer in elite female weightlifters.Scientific reports · 2026Article
- Video-Based Motion Capture Smartphone Apps for Testing Human Motor Performance Skills: Scoping Review.JMIR mHealth and uHealth · 2026Article
- Article
- Can OpenCap deliver valid and reliable kinematic data for motion analysis? A systematic review and three-level meta-analysis.Biology of sport · 2026Review
- Comparison of Jump-Landing Biomechanics during and after Fatigue: Investigation on the Optimal Timing of Screenings under Fatigue.Journal of human kinetics · 2025Article
- Open Source, Open Science: Development of OpenLESS as the Automated Landing Error Scoring System.Journal of athletic training · 2025Article
- Advancing Field-Based Vertical Jump Analysis: Markerless Pose Estimation vs. Force Plates.Life (Basel, Switzerland) · 2024Article
- AI-smartphone markerless motion capturing of hip, knee, and ankle joint kinematics during countermovement jumps.European journal of sport science · 2024Article
- Model variations for tracking the trunk during sports testing in a motion capture lab.Frontiers in sports and active living · 2024Article
- Ubiquitous Computing in Sports and Physical Activity-Recent Trends and Developments.Sensors (Basel, Switzerland) · 2022Article
- Validity of the frame subtraction method in dynamic postural stability.BMC sports science, medicine & rehabilitation · 2022Article
- Automated Landing Error Scoring System Performance and the Risk of Bone Stress Injury in Military Trainees.Journal of athletic training · 2022Article
- Think outside the box: Incorporating secondary cognitive tasks into return to sport testing after ACL reconstruction.Frontiers in sports and active living · 2022Review
- A SWOT Analysis of Portable and Low-Cost Markerless Motion Capture Systems to Assess Lower-Limb Musculoskeletal Kinematics in Sport.Frontiers in sports and active living · 2021Review
- The Relationship between Landing Error Scoring System Performance and Injury in Female Collegiate Athletes.International journal of sports physical therapy · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
contextField-based, portable motion-capture systems can be used to help identify individuals at greater risk of lower extremity injury. Microsoft Kinect-based markerless motion-capture systems meet these requirements; however, until recently, these systems were generally not automated, required substantial data postprocessing, and were not commercially available.
objectiveTo validate the kinematic measures of a commercially available markerless motion-capture system.
designDescriptive laboratory study.
settingLaboratory. PATIENTS OR OTHER
participantsA total of 20 healthy, physically active university students (10 males, 10 females; age = 20.50 ± 2.78 years, height = 170.36 ± 9.82 cm, mass = 68.38 ± 10.07 kg, body mass index = 23.50 ± 2.40 kg/m2). INTERVENTION(S): Participants completed 5 jump-landing trials. Kinematic data were simultaneously recorded using Kinect-based markerless and stereophotogrammetric motion-capture systems. MAIN OUTCOME MEASURE(S): Sagittal- and frontal-plane trunk, hip-joint, and knee-joint angles were identified at initial ground contact of the jump landing (IC), for the maximum joint angle during the landing phase of the initial landing (MAX), and for the joint-angle displacement from IC to MAX (DSP). Outliers were removed, and data were averaged across trials. We used intraclass correlation coefficients (ICCs [2,1]) to assess intersystem reliability and the paired-samples t test to examine mean differences (α ≤ .05).
resultsAgreement existed between the systems (ICC range = -1.52 to 0.96; ICC average = 0.58), with 75.00% (n = 24/32) of the measures being validated (P ≤ .05). Agreement was better for sagittal- (ICC average = 0.84) than frontal- (ICC average = 0.35) plane measures. Agreement was best for MAX (ICC average = 0.77) compared with IC (ICC average = 0.56) and DSP (ICC average = 0.41) measures. Pairwise comparisons identified differences for 18.75% (6/32) of the measures. Fewer differences were observed for sagittal- (0.00%; 0/15) than for frontal- (35.29%; 6/17) plane measures. Between-systems differences were equivalent for MAX (18.18%; 2/11), DSP (18.18%; 2/11), and IC (20.00%; 2/10) measures. The markerless system underestimated sagittal-plane measures (86.67%; 13/15) and overestimated frontal-plane measures (76.47%; 13/17). No trends were observed for overestimating or underestimating IC, MAX, or DSP measures.
conclusionsModerate agreement existed between markerless and stereophotogrammetric motion-capture systems. Better agreement existed for larger (eg, sagittal-plane, MAX) than for smaller (eg, frontal-plane, IC) joint angles. The DSP angles had the worst agreement. Markerless motion-capture systems may help clinicians identify individuals at greater risk of lower extremity injury.
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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.