EEG α Wave Analysis Of The Walking Athletes In Function-specific Homeostasis

Homeostasis was one of the classic concepts of physiology and exercisephysiology, but the lack of characterization methods hindered its extensive application.Liu Cheng-yi and others developed this theory as the Function-specific Homeostasis(FSH), and established the Homeostasis Theory of Exercise Training(HTET). FSHwas negative feedback mechanism that to maintain function sufficiently and steadily,has many characteristics including simple, economical and easy for quantitative study.The quality of FSH included functional complexity and the stability of functioning.Two qualities complement each other. The major FSH of players was Sport-specificHomeostasis(SpSH)which maintain athletic performance Sufficiently and steadily.Athletic performance of the game Characterized the functional complexity, thecoefficient of variation(CV) of results in different locations and at different timescharacterized the stability of functioning. Better athletic performance, lower the CV ofcompetition results, higher the quality of SpSH. In this paper, characterizationmethods of electroencephalogram(EEG) in SpSH was researched.The data of athletes’ EEG α wave band could analysised with order parameterand information entropy. On this basis, this paper used principal component analysis(PCA), with the CV characterized the stability of SpSH, extracted competitive statusinformation of walking athletes’ EEG combined with the stepwise discriminant. Theresearch found that the dominant frequency of the elite athletes was10Hz, the orderparameter level(OPL) could characterize SpSH,which supported the theorycompatibility between order parameter and HTET. This paper also found some of theadvantage brain regions of elite athletes according to the principal componet(PC)PC2and PC3which could characterize SpSH, so provided a theoretical basis.Background and Objective: The aim of this study was to investigate thecharacteristics of EEG α waves of walking athletes at different levels so as to find theEEG characteristics of SpSH.Study Design/Materials and Methods: The EEG data of56samples of5elitewalking athletes at the different training stages were assessed with the AdvancedTraining Control Monitoring. Their SpSH information was analyzed with principalcomponent analysis and order parameter theory.Results: The average EEG signal of elite athletes was higher in10Hz than thatof normal athletes, but lower in8,9and11Hz that of normal athletes, respectively. Some of the advantage brain regions were consistent with previous studies, but othersshould be further investigated. The information entropy of elite athletes was lowerthan that of normal athletes. The higher the order parameter level, the lower theinformation entropy. The SpSH quality of elite athletes was higher than that of normalathletes.Conclusions: The order parameter (dominant frequency at10Hz) of athletes’EEG α wave may represent the SpSH quality.