Sports person psychological behaviour signal analysis during Thfeir activity session

IF 1.5 Q2 COMPUTER SCIENCE, THEORY & METHODS International Journal of Fuzzy Logic and Intelligent Systems Pub Date : 2021-05-26 DOI:10.3233/JIFS-219018
Yu Zhang, P. Kumar, Adhiyaman Manickam
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Abstract

Mental well-being is a significant resource for athletes about their success and growth. Athletes are now facing additional risk factors in mental health in the sporting community, such as heavy workout loads, rough races, and demanding lifestyles. The great difficulty is to diagnose conditions and acquire sport and exercise features that contribute to daily or long-term practice to detrimental emotional reactions. In this paper, the sports activity session monitoring system (SASMS) has been proposed using wearable devices and EEG signal by monitoring the sports person’s heart rate and psychological behaviour. The proposed SASMS mental-health analysis focused on model spectrum forms representing the best results, mental illness, and mental health. The paper’s key conclusions concerned with the athletes’ performance, occupational and personal advancement of athletes in mental health problems, strategies intended to track and sustain athletes’ mental health, and outflow of different mental illness types. This research’s findings provide the basis for implementing actions that promote a healthy emotional state in the sport to enhance activity and fitness.
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运动员运动过程中的心理行为信号分析
心理健康是运动员成功和成长的重要资源。在体育界,运动员现在面临着额外的心理健康风险因素,如繁重的锻炼负荷、艰苦的比赛和苛刻的生活方式。最大的困难是诊断条件,并获得有助于日常或长期练习有害情绪反应的运动和锻炼特征。本文提出了一种利用可穿戴设备和脑电图信号监测运动者心率和心理行为的运动活动时段监测系统(SASMS)。提出的SASMS心理健康分析侧重于代表最佳结果的模型谱形式、心理疾病和心理健康。本文的主要结论涉及运动员的表现、运动员在心理健康问题中的职业和个人进步、运动员心理健康的跟踪和维持策略以及不同类型心理疾病的流出。本研究的发现为在运动中促进健康的情绪状态以增强活动和健身的实施行动提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.80
自引率
23.10%
发文量
31
期刊介绍: The International Journal of Fuzzy Logic and Intelligent Systems (pISSN 1598-2645, eISSN 2093-744X) is published quarterly by the Korean Institute of Intelligent Systems. The official title of the journal is International Journal of Fuzzy Logic and Intelligent Systems and the abbreviated title is Int. J. Fuzzy Log. Intell. Syst. Some, or all, of the articles in the journal are indexed in SCOPUS, Korea Citation Index (KCI), DOI/CrossrRef, DBLP, and Google Scholar. The journal was launched in 2001 and dedicated to the dissemination of well-defined theoretical and empirical studies results that have a potential impact on the realization of intelligent systems based on fuzzy logic and intelligent systems theory. Specific topics include, but are not limited to: a) computational intelligence techniques including fuzzy logic systems, neural networks and evolutionary computation; b) intelligent control, instrumentation and robotics; c) adaptive signal and multimedia processing; d) intelligent information processing including pattern recognition and information processing; e) machine learning and smart systems including data mining and intelligent service practices; f) fuzzy theory and its applications.
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