Research On The Identification Of Motion Fatigue Degree Based On The Variation Of Heart Rate Variability

In recent years,with the improvement of people’s living standards,people pay more attention to their own health,sports is the best way to keep healthy.But when people exercise,they often do not know the degree of their sports fatigue,most people are feeling to exercise.Biological science and sports science thinks the body is in severe fatigue,the body’s resistance to fall,it is likely to cause damage to the body’s organs.Therefore,for the athletes,real-time understanding of their sports fatigue at the time of the movement is very necessary.The purpose of this study is to use the existing physiological signals of wearable devices,and analyze the effective indicators of the fatigue of human movement Then train a can intelligent identification model of human motion fatigue,so as to facilitate movement are real-time understanding of their exercise fatigue,guiding the movement of the people more healthy movement.The main research of this thesis is to discriminate the body motion fatigue by using the heart rate variability.Firstly,the pulse wave signal of the human body is acquired by the wearable device,and the pulse wave signal is removed and the baseline drift is removed,so the pulse signal is obtained.Then respectively pulse signal in time domain,frequency domain,the nonlinear angle extract indicators of heart rate variability,by studying these parameters change with exercise fatigue and finally to find a can obviously judged valid indicators of the level of sports fatigue.In the above parameters based on the proposed method to distinguish the amplitude and slope.Finally,the discriminant parameter training a discriminative model used here is support vector machine(SVM)is a machine learning method,and the kernel function of SVM classification model is improved,from a single kernel function is improved into the mixed kernel function,to further enhance the classification model.After the model training is formed,the user can only use the input data,and the model can automatically give the movement fatigue state of the sports person.On the basis of theory,the above technology is realized and the software is developed,and the health system of B/S is realised.In this thesis,the exercise fatigue state of human body is effectively distinguished by using the heart rate variability.Users only need to enter real-time motion data,you can easily and quickly know the fatigue state of their movement,so as to decide the next step of the fitness program.It is important for people to keep physical health and prevent unnecessary damage caused by excessive fatigue.