Quantitative EEG in sports: performance level estimation of professional female soccer players

Tharawadeepimuk, Kittichai; Wongsawat, Yodchanan

doi:10.1007/s13755-021-00144-w

Cited by 7 publications

(4 citation statements)

References 58 publications

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“…Silva et al (2022) revealed that the electronic game they played by generating a competitive ambiance greatly impacted the testosterone and cortisol levels of undergraduate students. In another research, Tharawadeepimuk and Wongsawat (2021) stated that contests in which a competitive ambiance is generated impact the players psycho physiologically. They analyzed the studies on electronic sports.…”

Section: Resultsmentioning

confidence: 99%

“…The prevalence of electronic sports (E-sports), the media coverage rate, and the entity of spectators and participants have risen considerably over the past years. Consequently, scientific studies over the subject of electronic sports started to attract popularity (Tharawadeepimuk & Wongsawat, 2021). New e-sports studies predictably define e-sport games as a commonly played in a team-level pf individual competitive way with amateur-level and professional rating tools.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the impact of electronic sports on anxiety and biochemical factors of players

Ayhan¹

2022

Rev. Invest. Univ. Quindío

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An obvious characteristic of computer games is stress, competition, and physiological alterations in the body. It is regarded as an important subject including those factors in e-sports, getting progressively popular in the digital era. The psychological and physiological impacts of e-sports, conducted in a competitive ambiance, on the body and mind over the course of competitions are not yet known. The aim of the paper is determining the impacts of players performing in e-sports games on some biochemical and hormonal factors shaped in the body during the game. In the group of research, there are twenty electronic sports volunteer players playing in e-sports games. Samples are gathered from the players in the study thirty minutes before and after electronic sports games. Given the results, it is concluded that e-sports players' ACTH, cortisol, and testosterone levels rose substantially.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of the impact of electronic sports on anxiety and biochemical factors of players

Ayhan¹

2022

Rev. Invest. Univ. Quindío

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“…[39]. Relationships between biological, training, and physical variables in the expression of performance in lay runners were considered in the paper [40]. In many papers showed a correlation between biological parameters and fatigue.…”

Section: Measuring Fatigue Current Stagementioning

confidence: 99%

Review of Neural Networks in the EEG Signal Recognition

Rakhmatulin¹

2020

Preprint

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In the last decade, unprecedented progress in the development of neural networks influenced dozens of different industries, among which are signal processing for the electroencephalography process (EEG). Electroencephalography, even though it appeared in the first half of the 20th century, to this day didn’t change the physical principles of operation. But the signal processing technique due to the use of neural networks progressed significantly in this area. Evidence for this can serve that for the past 5 years more than 1000 publications on the topic of using machine learning have been published in popular libraries. Many different models of neural networks complicate the process of understanding the real situation in this area. In this manuscript, we provided the most comprehensive overview of research where were used neural networks for EEG signal processing.

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“…Tharawadeepimuk and Wongsawat (2021) used the brain topographic map (absolute force) and brain connectivity (coherence and amplitude asymmetry) to analyze the psychological factors when doing sports. They evaluated athletes' performance in competition through noninvasive quantitative EEG [8]. Bieru et al (2021) used EEG to record the brain activity of 12 judo athletes and 11 volleyball athletes during hand flexor contraction and relaxation, which helps coaches evaluate the training effect of athletes [9].…”

Section: Introductionmentioning

confidence: 99%

Athletes’ State Monitoring under Data Mining and Random Forest

2022

Journal of Sensors

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The study aims to train athletes to be in top form and at their best in the competition. Based on the relevant theoretical research, archers are taken as the research subjects, the characteristics of archery are analyzed, and the electroencephalogram (EEG) features of the athletes in different stages of precompetition training are monitored. And the athletes’ competitive state monitoring model based on random forest (RF) is implemented and tested. The experimental results show that the athletes’ dominant frequency of brain band α, EEG entropy, central fatigue index, excitation inhibition index, and cerebral state index in precompetition training is significantly different from those in training ( P < 0.05 ).The monitoring model implemented classifies athletes’ competitive states. Compared with the support vector machine (SVM) classification model, its classification accuracy is higher than 90%. The overall classification accuracy is 89.74%, more significant than SVM. The research provides a reference for monitoring athletes’ competitive states and helps them regulate their states in real time.

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Quantitative EEG in sports: performance level estimation of professional female soccer players

Cited by 7 publications

References 58 publications

Analysis of the impact of electronic sports on anxiety and biochemical factors of players

Analysis of the impact of electronic sports on anxiety and biochemical factors of players

Review of Neural Networks in the EEG Signal Recognition

Athletes’ State Monitoring under Data Mining and Random Forest

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