ArticleScientific data2023
Three-Dimensional Motion Capture Data of a Movement Screen from 183 Athletes.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- Virtual reality-assisted neuromuscular training effects on agility performance and injury prevention in basketball athletes: a controlled laboratory experiment.Scientific reports · 2026Trial
- ViT-ConvGAN: a hybrid model for spatiotemporal action recognition using video transformer and 3D CNN.Scientific reports · 2026Article
- EdgeFuser: A tightly coupled adaptive framework for real-time athlete group analytics.iScience · 2026Article
- Advanced utilization of motion decomposition and visualization technology in gymnastics education.Frontiers in psychology · 2026Article
- Identifying functional movement deficits in mild to moderate adolescent idiopathic scoliosis: a cross-sectional study.Frontiers in pediatrics · 2026Article
- Whole-body optical marker and ground reaction force data of healthy humans performing non-cyclic activities.Scientific data · 2025Article
- Motion capture data of six jump-landings, fatigued and non-fatigued, after anterior cruciate ligament injury.Scientific data · 2025Article
- Effects of various static calibration postures on knee mechanics during locomotor tasks using statistical parametric mapping analysis.Scientific reports · 2025Article
- Similarity Index Values in Fuzzy Logic and the Support Vector Machine Method Applied to the Identification of Changes in Movement Patterns During Biceps-Curl Weight-Lifting Exercise.Journal of functional morphology and kinesiology · 2025Article
- Motion Capture Technology in Sports Scenarios: A Survey.Sensors (Basel, Switzerland) · 2024Review
- Three-Dimensional Motion Capture Data of a Movement Screen from 183 Athletes.Scientific data · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Movement screens are widely used to identify aberrant movement patterns in hopes of decreasing risk of injury, identifying talent, and/or improving performance. Motion capture data can provide quantitative, objective feedback regarding movement patterns. The dataset contains three-dimensional (3D) motion capture data of 183 athletes performing mobility tests (ankle, back bend, crossover adduction, crossover rotation, elbows, head, hip turn, scorpion, shoulder abduction, shoulder azimuth, shoulder rotation, side bends, side lunges and trunk rotation) and stability tests (drop jump, hop down, L-cut, lunge, rotary stability, step down and T-balance) bilaterally (where applicable), the athletes' injury history, and demographics. All data were collected at 120 Hz or 480 Hz using an 8-camera Raptor-E motion capture system with 45 passive reflective markers. A total of 5,493 trials were pre-processed and included in .c3d and .mat formats. This dataset will enable researchers and end users to explore movement patterns of athletes of varying demographics from different sports and competition levels; develop objective movement assessment tools; and gain new insights into the relationships between movement patterns and 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.