An Application Research About Biofeedback Technology In Monitoring Exercise-induced Fatigue

Objective: the exercise-induce fatigue is called that the body can not support in ahorizontal level or a high-strength basis. And there is always a hotspot in movementphysiology, which is enriching and improving the exercise-induce fatigue diagnosticmethods. However, the sidedness and limitations of current fatigue monitoring tools isbecoming increasingly prominent, even fettering the scientific process of the athletictraining while contemporary sports is quickly upgrading level. What’s more, can bethe biofeedback technology (BT) which combines heart rate variability (HRV),surface electromyography (sEMG), skin conductance (SC), electroencephalogram(EEG) and other technology applied to the diagnosis of exercise-induced fatigue? Canit be able to effectively relieve the highlighted chronic that the currently fatiguemonitoring tools have? Can it be truly used to catch the central nervous system fatigue,peripheral fatigue includes cardiac fatigue in real-time assessment? Can it be ability toeffectively establish sports-fatigue timing diagram which is used to determine thesequence of various types of fatigue occurrence? Unfortunately, the relevant argumentsabroad and home is still relatively scarce at present. The BT, therefore, will have beenintroduced to the surveillance of exercise-induced fatigue by this research. The mainpurpose of this paper is to explore the value and curve variation of the technologycomposite index (HRV, sEMG, SC, EEG) when athletes suffering sports fatigue, andto clarify the possible relationship and timing characteristics between the centralnervous system fatigue with the peripheral fatigue including cardiac fatigue.Meanwhile the value of the effect that that technology may bring will also have beendemonstrated. All this is to provide new support for the theory and practice of thesports fatigue monitoring.Method：16physical education college athletes of the sports institute have beenrandomly divided into male group (M group) and female group (F group). To achieveprogressively fatigue statue even to completely exhaustive, the classic Bruce Protocolwith seven increasing intensity and treadmill exercise way have been used. And thereaction, instantly maximum HR (heart rate), and rating of perceived exertion (RPE)also have been jointly applied in order to determine the production of fatigue. What’smore, the characteristics and variation of biofeedback technology index have beenmeasured by self-controlled and gender contrast when athletes were during exercise or reached fatigue. Exercise-induced fatigue timing feature maps, at the same time,would have been systematically builded.Result：（1）When athletes were struggling in fatigue, the HRV index was significantlydecreasing. But the standard deviation(SDNN),standard deviation of thedifferences(SDSD),root mean square of successive differences(RMSSD),thepercentage of all adjacent NN distances that differ＞50ms from each other(PNN50) asthe HRV time-domain index, the LF power values, HF power values,LF\HF asfrequency-domain indexes and absolute sinus arrhythmia(SAa) were seeing a risetrend. As well as the root mean square amplitude(IEMG)and integratedelectromyography(RMS)as amplitude of the sEMG biofeedback index were appearingto raise, the frequency index mean power frequency(MPF),median frequency(MF)was decline. The male’s value of skin conductance level (SCL) which is a SCbiofeedback index was experiencing a process of continuous decline, while thefemale’s was increasing. However, the α, β, SMR and θ wave power spectrum as EEGbiofeedback index were going to rise.（2）two main trends that can be definedasâ… andâ…¡type were shown by BT composite index curves. In spite of HRVâ… typecurve demonstrated a periodically changes, â…¡type was a numeric range and amagnitude swells. While the sEMGâ… curve had changes which were shock stableperiodâ†'rapid rise stageâ†'shock stationary phase, andâ…¡ type was only a significantincrease in extent. Due to the baseline differences of SCL which is a SC biofeedbacktechnical indicator,8μs become an important basis for classification. The ones that arehigher than8μs are divided into high baseline levels group (H group) as the belowones are in low class (L group). Female athletes with low baseline levels appearedmore significant double peaks phenomenon, but the males’ changed amplitude sharplywhen exercise-induced fatigue was coming. However, the females’ curves with highlevel were roughly divided into four stages which were shock riseâ†'rapid riseâ†'rapiddeclineâ†'refractory, but the males’ had a change with refractoryâ†'rapid riseâ†'rapiddeclineâ†'shock rise. Although SCL diverse, EEG curves still showed two types. Thethree peaks phenomenon and a significant increase in the volatility has witnessed itstwo the main changes.（3）The timing characteristics map relying on BT was showingan order which is heart muscle(HRV)â†'skeletal muscle (sEMG)â†'electroencephalogram（EEG）.Conclusion：（1）There were a series of significant regular changes.The HRVindices,for example, experienced a significantly decreased process when the athleteswere suffering in exercise-induced fatigue. But the HRV time-domain indexes (SDNN, SDSD, RMSSD and PNN50), frequency-domain indexes (LF power values, HFpower value, LF\HF) and SAa rose. At this time the SCL value of M groupdecreased, the F’s rose. What’s more, the EEG wave power values (α wave, β wave,SMR wave, θ wave) went up.(2) The BT composite index curves were mainlycharacterized by two types of current. And the fatigue curves also exhibited a range ofcharacteristic diversifications. The curve’s value magnitude or fluctuation interval, forinstance, increased. Or the curve showed a sharply up and down tendency, even mademanifestations that composed by four-cycle diversification or three peaks.(3) Thefeatures and regular changes of biofeedback technology composite index in fatiguemay be used for monitoring fatigues which involve CNS fatigue, peripheral fatigueand cardiac fatigue, even depicting a procedure characterized diagram for sports CNSfatigue and peripheral fatigue. And in this chart an order was presented which ismyocardium(HRV)â†'skeletal muscle (sEMG)â†'brain (EEG).(4)The BT whichmonitor exercise-induced fatigue may create a lot of values just like more scientific,more timeliness, high systematic, non-invasive and easy to grasp.