Research On Heart Rate Variability Of Mental Fatigue Induced By Sleep Deprivation

With the rapid development of society and the increasing pressure on life,fatigue has become a normal state in many people’s lives,and it has also become an important cause of physical illness and various accidents.How to quickly and effectively detect the fatigue state of the human body is the basis for protecting human health and an important link to prevent losses caused by fatigue.Traditional fatigue detection is based on the electrocardiogram(ECG)signal,which requires long-term wearing of electrodes,which is difficult to meet the requirements of daily fatigue detection.Therefore,finding a simple and effective unbounded fatigue detection method has become an urgent problem.In this study,based on the analysis of fatigue detection and heart rate variability(HRV),a fatigue detection method based on cardiac shock(BCG)signals is proposed.This method uses sleep deprivation as the fatigue model and BCG signals as the evaluation criteria.The signal acquisition system and the analysis of the changes in HRV indicators under different fatigue conditions provide a more objective evaluation standard for unbounded fatigue detection in daily life.The contents of this study are as follows:1.The research background and significance of the subject are introduced.The research status of fatigue testing at home and abroad is summarized from the two aspects of BCG signal and HRV.The main research content and innovation of this experiment are described.2.Design of BCG signal acquisition system.The principle of BCG signal is introduced.According to the characteristics of BCG signal,a piezoelectric thin film sensor is selected to design a signal acquisition system,which mainly includes a signal acquisition module,a signal processing module and a signal transmission module.3.Research on Noise Reduction of BCG Signal Based on CEEMDAN-PE.Due to the large amount of noise in the collected BCG signal,according to the noise source,combined with the advantages of the complete set of empirical mode decomposition(CEEMDAN)and permutation entropy(PE)algorithms of adaptive noise,a CEEMDAN-PE-based signal noise reduction is proposed Method,and compare the algorithm in this paper with wavelet transform method and empirical mode decomposition(EMD)method,and discuss the advantages and disadvantages of the noise reduction algorithm based on the results.4.Fatigue detection analysis based on HRV.This paper introduces the time domain analysis,frequency domain analysis and non-linear analysis methods of HRV,selects sleep deprivation as a model to induce fatigue,observes the changes of HRV in sitting and lying positions during 24 hours of sleep deprivation,and analyzes various conditions under different fatigue states differences in indicators.This paper uses the BCG signal acquisition system and CEEMDAN-PE algorithm to denoise the BCG signal,and then designs sleep deprivation experiments to collect data and calculate the HRV index of sitting and lying BCG signals under different fatigue states.The results show that BCG signals can become objective indicators of fatigue assessment,and changes in HRV indicators can effectively reflect human fatigue.