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DOI: 10.1371/journal.pone.0159356
论文题名:
Development of a Kinect Software Tool to Classify Movements during Active Video Gaming
作者: Michael Rosenberg; Ashleigh L. Thornton; Brendan S. Lay; Brodie Ward; David Nathan; Daniel Hunt; Rebecca Braham
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2016
发表日期: 2016-7-21
卷: 11, 期:7
语种: 英语
英文关键词: Games ; Video games ; Children ; Musculoskeletal system ; Joints (anatomy) ; Human mobility ; Physical activity ; Software tools
英文摘要: While it has been established that using full body motion to play active video games results in increased levels of energy expenditure, there is little information on the classification of human movement during active video game play in relationship to fundamental movement skills. The aim of this study was to validate software utilising Kinect sensor motion capture technology to recognise fundamental movement skills (FMS), during active video game play. Two human assessors rated jumping and side-stepping and these assessments were compared to the Kinect Action Recognition Tool (KART), to establish a level of agreement and determine the number of movements completed during five minutes of active video game play, for 43 children (m = 12 years 7 months ± 1 year 6 months). During five minutes of active video game play, inter-rater reliability, when examining the two human raters, was found to be higher for the jump (r = 0.94, p < .01) than the sidestep (r = 0.87, p < .01), although both were excellent. Excellent reliability was also found between human raters and the KART system for the jump (r = 0.84, p, .01) and moderate reliability for sidestep (r = 0.6983, p < .01) during game play, demonstrating that both humans and KART had higher agreement for jumps than sidesteps in the game play condition. The results of the study provide confidence that the Kinect sensor can be used to count the number of jumps and sidestep during five minutes of active video game play with a similar level of accuracy as human raters. However, in contrast to humans, the KART system required a fraction of the time to analyse and tabulate the results.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0159356&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/23565
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: School of Sport Science, Exercise and Health, University of Western Australia, M408 35 Stirling Highway, Crawley, WA, Australia 6009;School of Sport Science, Exercise and Health, University of Western Australia, M408 35 Stirling Highway, Crawley, WA, Australia 6009;School of Sport Science, Exercise and Health, University of Western Australia, M408 35 Stirling Highway, Crawley, WA, Australia 6009;School of Sport Science, Exercise and Health, University of Western Australia, M408 35 Stirling Highway, Crawley, WA, Australia 6009;School of Sport Science, Exercise and Health, University of Western Australia, M408 35 Stirling Highway, Crawley, WA, Australia 6009;School of Sport Science, Exercise and Health, University of Western Australia, M408 35 Stirling Highway, Crawley, WA, Australia 6009;School of Sport Science, Exercise and Health, University of Western Australia, M408 35 Stirling Highway, Crawley, WA, Australia 6009

Recommended Citation:
Michael Rosenberg,Ashleigh L. Thornton,Brendan S. Lay,et al. Development of a Kinect Software Tool to Classify Movements during Active Video Gaming[J]. PLOS ONE,2016-01-01,11(7)
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