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An Athletic Training Analysis System Research Based on Physiological Computation

An Athletic Training Analysis System Research Based on Physiological Computation

Ding Xiong, Lu Yan, Peng Qiong
Copyright: © 2018 |Volume: 13 |Issue: 2 |Pages: 14
ISSN: 1555-3396|EISSN: 1555-340X|EISBN13: 9781522542995|DOI: 10.4018/IJHISI.2018040104
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MLA

Xiong, Ding, et al. "An Athletic Training Analysis System Research Based on Physiological Computation." IJHISI vol.13, no.2 2018: pp.54-67. http://doi.org/10.4018/IJHISI.2018040104

APA

Xiong, D., Yan, L., & Qiong, P. (2018). An Athletic Training Analysis System Research Based on Physiological Computation. International Journal of Healthcare Information Systems and Informatics (IJHISI), 13(2), 54-67. http://doi.org/10.4018/IJHISI.2018040104

Chicago

Xiong, Ding, Lu Yan, and Peng Qiong. "An Athletic Training Analysis System Research Based on Physiological Computation," International Journal of Healthcare Information Systems and Informatics (IJHISI) 13, no.2: 54-67. http://doi.org/10.4018/IJHISI.2018040104

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Abstract

This article is about how physiological status data is more important for athlete support training and competition. The Physiological Plan system is designed and implemented in this article, and the system is divided into the hardware layer, the data processing layer, the algorithm layer and the interface layer. The hardware layer adopts the Berkeley Tricorder platform. The data processing layer integrates the data of each sensor on the adapter mode. The algorithm layer includes a filtering algorithm, a peak detection algorithm and an Outlier detection algorithm. At the interface level, the coach interacts with the athlete, and the results are presented to the coach. In the system, the ECG, EMG and 3D acceleration of the athletes can be collected and analyzed at the same time, and the resultant data analysis are fed back to the coaches, these can solve problems in the athletes' physical data which cannot be collected and analyzed in real time. The experimental results show that the system can effectively assist the coaches in monitoring and analyzing the state of the athletes during training and competition.

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