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Optical motion capture dataset of selected techniques in beginner and advanced Kyokushin karate athletes.
- Source :
- Scientific Data; 1/18/2021, Vol. 8 Issue 1, p1-12, 12p
- Publication Year :
- 2021
-
Abstract
- Human motion capture is commonly used in various fields, including sport, to analyze, understand, and synthesize kinematic and kinetic data. Specialized computer vision and marker-based optical motion capture techniques constitute the gold-standard for accurate and robust human motion capture. The dataset presented consists of recordings of 37 Kyokushin karate athletes of different ages (children, young people, and adults) and skill levels (from 4th dan to 9th kyu) executing the following techniques: reverse lunge punch (Gyaku-Zuki), front kick (Mae-Geri), roundhouse kick (Mawashi-Geri), and spinning back kick (Ushiro-Mawashi-Geri). Each technique was performed approximately three times per recording (i.e., to create a single data file), and under three conditions where participants kicked or punched (i) in the air, (ii) a training shield, or (iii) an opponent. Each participant undertook a minimum of two trials per condition. The data presented was captured using a Vicon optical motion capture system with Plug-In Gait software. Three dimensional trajectories of 39 reflective markers were recorded. The resultant dataset contains a total of 1,411 recordings, with 3,229 single kicks and punches. The recordings are available in C3D file format. The dataset provides the opportunity for kinematic analysis of different combat sport techniques in attacking and defensive situations. Measurement(s) 3D trajectory • joints angle • joints force • joints power • joints moment • body movement coordination trait Technology Type(s) optical motion capture Factor Type(s) age • technique • skill level • condition Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment laboratory environment Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13164848 [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20524463
- Volume :
- 8
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Scientific Data
- Publication Type :
- Academic Journal
- Accession number :
- 148190116
- Full Text :
- https://doi.org/10.1038/s41597-021-00801-5