The Fusion Method Base On The Relationship Between Ecg Signal And Ulse Signal

With the ceaseless development of human society, people’s living standardsgradually improved and spurred to greater demands on the quality of life and health.However, engaging in mental work for a long time, lack of sleep or emotionaldistress, fatigue and irregular life can cause internal function disorder,cardiovascular disorders and unusual glandular secretion. This could affect thepeople’s normal life seriously. Physiological signal is used to determine the healthstatus in the modern medicine. However, the single signal (ECG, pulse, etc.) waspoor to discriminate the body’s physiological state changes. Proceeding fromsimultaneous analysis of two kinds of physiological signals and exploring thecorrelation between human physiological signals, this paper presents a fusionanalysis method based on ECG and pulse signals. The main works were shown asfollowing:(1) The ECG and pulse signals were acquired synchronously before and after thefatigue experiment through the data acquisition system.(2) Preprocess ECG and pulse signal with the appropriate filter, and eliminate thebaseline drift with the frequency50Hz and EMG interference. Then we can obtainaccurate waveforms.(3) The characteristics of the R-wave, T wave, the peak value and the tidal wavepeak of the pulse signals were analyzed. The t test was used to evaluate thesignificance level of each characteristic changes and the significance level are allp<0.01. The R-R intervals and P-P intervals could be extracted from the ECG andthe pulse signals. Analysis the change before and after the visual fatigue experimentin the time domain and frequency domain feature extraction. The mean interval ofHRV and PRV characteristics, SDDN, very low frequency (VLF), low frequency(LF), high frequency (HF), the relative spectral distribution (LF/HF) and correlationwere analyzed under the same experimental state and the different experimentalstates respectively, The t test results have demonstrated each feature has statisticalsignificance p<0.01.Finally, the characteristics of the ECG and pulse were used to analyze thehuman physiological property. The results have shown that there is correlationproperty between HRV/PRV and Autonomic Nerve in VDT Fatigue. Comparingdifferent information fusion methods and using feature fusion to analyze the VDT Fatigue, the accuracy rate of classification reaches up to100%by using SupportVector Machine for the combination features of ECG and pulse wave signals, whichsurpassed the accuracy rate classified by one kind of biomedical signal.The results have shown that ECG and pulse signal in the human body are veryclosely related characteristics. Not only the ECG and the pulse signals can reflect thefatigue state, but also the correlation between ECG and pulse signals have bettereffect on the research and analysis of the fatigue state.