{"title":"运动员运动过程中的心理行为信号分析","authors":"Yu Zhang, P. Kumar, Adhiyaman Manickam","doi":"10.3233/JIFS-219018","DOIUrl":null,"url":null,"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.","PeriodicalId":44705,"journal":{"name":"International Journal of Fuzzy Logic and Intelligent Systems","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2021-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sports person psychological behaviour signal analysis during Thfeir activity session\",\"authors\":\"Yu Zhang, P. Kumar, Adhiyaman Manickam\",\"doi\":\"10.3233/JIFS-219018\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":44705,\"journal\":{\"name\":\"International Journal of Fuzzy Logic and Intelligent Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2021-05-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Fuzzy Logic and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/JIFS-219018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy Logic and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/JIFS-219018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Sports person psychological behaviour signal analysis during Thfeir activity session
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.
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.