Research And Application Of Motion Fatigue Grading System Based On Multi-parameter

Sports are always with us,as big as the earth,small to pulse beat,people's research on it has never stopped,the body movement is dominated by the brain,and the fatigue of the brain can also be reflected on the limbs.There is an inseparable relationship between them.As long as exercise produces fatigue,the difference is the degree of fatigue,the right amount of exercise helps people release work stress and improve the quality of life,while excessive exercise may cause damage to the body.The rationality and scientificity of "quantity" is the focus of this research.The specific work contents are as follows:1.Reading a large amount of literature,it is found that there are two main types of subjective and objective evaluations of exercise fatigue.The advantages of the former are simple and fast,the disadvantages are too subjective and fuzzy,and subject to the subjective emotion of the evaluator;the latter is mainly through the detection of changes in various physiological parameters in the body after exercise,such as lactic acid,brain electricity,etc.Such an evaluation method has high precision,and the disadvantage is that the timeliness is poor,and special testing equipment and medical knowledge reserves are required.Faced with the above problems,this paper combines the advantages of subjective evaluation and objective evaluation,and integrates multiple parameter indexes such as RPE value,heart rate,respiration rate,riding speed,pedaling frequency and heart rate variability to evaluate fatigue.2.Designing fatigue classification model,endurance assessment experiment,riding experiment and collecting experimental data.A three-level evaluation model of sports fatigue is designed,which includes 10 three-level indicators,3 second-level indicators and1 target indicator.Firstly,30 subjects were divided into four groups by exercise endurance assessment experiment.Secondly,Ironman tacx T2060 virtual intelligent bicycling platform system is used to monitor the parameters of speed,power and trampling frequency.Meanwhile,Zephyr BioHarness portable chest belt detection device is used to monitor the cyclist's movement heart rate and respiratory rate,And analyze the heart rate variability.3.Data analysis and verification of fatigue model.According to the changes of heart rate in 30 subjects,they were divided into four states: relaxed,mild fatigue,moderate fatigue and severe fatigue.The fuzzy comprehensive analytic hierarchy process was usedto analyze the experimental data.Determine the weights and membership of the indicators at all levels,the weight of the exercise indicators is about 61.06%,the physiological indicators account for about 26.07%,accounting for 10.32%,combined with the subjective fatigue scale to evaluate the fatigue state of the subjects.In order to further verify the correctness of the fatigue grading model,time domain analysis,frequency domain analysis and nonlinear analysis and simulation experiments were carried out from the perspective of heart rate variability.The results show that the multi-parameter-based exercise fatigue grading model can accurately classify the fatigue state of the subject.