Research on the Application of Facial Expression Recognition Model Based on BP Neural Network in the Assessment of Sports Fatigue of Young Athletes

This article explores the importance of evaluating and intervening in sports fatigue among adolescent athletes, and proposes using a BP neural network facial expression recognition model to automatically assess fatigue status. A facial expression recognition model was constructed by studying the correlation between facial expressions and fatigue through literature review and mathematical statistics.Compared with the traditional evaluation method, this model can make the coach more objectively grasp the athletes’ emotion and fatigue state, and provide data support for it. Although the research is preliminary, with the accumulation of data, the accuracy of the model will improve, which will contribute to safe training. This method is convenient, non-invasive, and has theoretical and practical value, which helps to monitor exercise fatigue and improve health and performance.

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Publication Details

Published
2024-12-13
DOI
https://doi.org/10.1109/tcs64526.2024.11025270
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Research on the Application of Facial Expression Recognition Model Based on BP Neural Network in the Assessment of Sports Fatigue of Young Athletes

Yicong Jin, Gongbo Wei, Si-Min Huang, Shih T. Liang et al.
Advanced Sensor and Control Systems
article

Research on the Application of Facial Expression Recognition Model Based on BP Neural Network in the Assessment of Sports Fatigue of Young Athletes

Yicong Jin, Gongbo Wei, Si-Min Huang, Shih T. Liang, Mingyuan Zhao, Qingfa Dou
article en

Abstract

This article explores the importance of evaluating and intervening in sports fatigue among adolescent athletes, and proposes using a BP neural network facial expression recognition model to automatically assess fatigue status. A facial expression recognition model was constructed by studying the correlation between facial expressions and fatigue through literature review and mathematical statistics.Compared with the traditional evaluation method, this model can make the coach more objectively grasp the athletes’ emotion and fatigue state, and provide data support for it. Although the research is preliminary, with the accumulation of data, the accuracy of the model will improve, which will contribute to safe training. This method is convenient, non-invasive, and has theoretical and practical value, which helps to monitor exercise fatigue and improve health and performance.

Harbin University (CN), Zhaoqing University (CN)
Ministry of Education
Gender equality
Openalex Percentile: Top 62%
Advanced Sensor and Control Systems
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Research on the Application of Facial Expression Recognition Model Based on BP Neural Network in the Assessment of Sports Fatigue of Young Athletes — Yicong Jin, Gongbo Wei, et al. · (2024) | TGRS Research Map | TGRS