Analysis Of Heart Rate Variability Signals Based On Multi-scale Basic Scale Entropy And Detrended Fluctuation Analysis Methods

Heart play an important role in our life, people’s health and life are threatened heart disease, ECG (Electrocardiograph) reflect the heart’s electrical activity, and detect the function of the heart. As a way of research, HRV which is abstracted by ECG is used to appraise the activity of autonomic nerves, and the method has been a hotspot of study for non-invasively detection technology of ECG which is widely used nearly two decades.Heart is a complex nonlinear system, and HRV signal dynamic system of human body is a typical chaotic dynamic system, so the research on nonlinear of HRV signal can obtain more applications and closer to heart system than linear. More representative methods are power law analysis and entropy methods. Airline pilots, medical staffs, policemen on duty and many others are at reversed sleep with the development of society, while these people noting the health of heart, and also realize the effect of reversed sleep on health. So, the reach on the variation of heartbeats at reversed sleep has been a hotspot of study.The main work and innovation of the thesis could be summarized as follows:(1) In order to overcome the shortcoming of basic-scale entropy to analyze low frequency information of signal basing its single scale. Multi-scale base-scale entropy (MBE) is proposed on this basis. Chaotic mapping adding different signal-to-noise ratios is used for validating an object, then it is compared to the results which are obtained using MBE method, so MBE method has better capability of anti-noise and more suitable to analyze nonlinear signal.(2) DFA method developed maturely and used widely, the data of people under four different physiologic or pathologic conditions is obtained by DFA and MBE methods, and analyzing the changing HRV under different health state using the two methods to prove its application. Long range correlation of HRV in two groups (healthy elders and CHF patients) at the day and the night is analyzing by the method of DFA, and analyzing the impact of the day and the night on fluctuation of heart rate, the results show that the heart at the night is weaker than the day which indicated that the latent danger for heart at the night is higher than the day.(3) HRV signal has been analyzed using DFA and MBE methods at reversed sleep. ECG at reverse sleep is explored in comparison with normal daily. The results at reverse sleep showed that mean value of (scaling exponent) at normal state is bigger than at reversed state in experiment. The value of at sleep state is smaller than at waking state. The impact on HRV signals of sleep state in reversed sleep is bigger than in normal daily by analyzing the results of the MBE and DFA curves at sleep state and waking state. The above conclusions show that reversed sleep will weaken the long correlation of internal mechanism and have a bad effect on complexity of the human body itself. Especially the negative impact on HRV signals of sleep state in reversed schedule is obvious.