Correlation Between HRV And PRV For Sleep Apnea Patients

With the rapid pace of modern life,a variety of sleep disorders arises,which has gradually become a prominent common public health problems.People pay more and more attention.According to the World Health Organization epidemiological survey,about 1/3 of people around the world have sleep disorders.Sleep disorders all in our country are as high as 38.2%,with an estimated population of 1.3 billion,500 million people are suffering sleep problems.At present,in China,there are as many as 80 species of sleep disorders,of which sleep apnea syndrome accounted for about 60-70%.In 1970s,the Stanford University applied polysomnography in patients with sleep apnea syndrome as the sleep monitoring.The sleep center as a special diagnosis and treatment of sleep disorders was set up.According to the 2007 American Academy of Sleep Medicine,the sleep is divided into N1 sleep,N2 sleep,N3 sleep and rapid eye movement(REM).Each stage has its unique brain signals and different physiological reactions and it is very meaningflul to study the characteristics of each sleep stages and the differences and correlations between them.In the past few decades,the heart rate variability(HRV)from electrocardiogram has become a very useful tool for clinical diagnosis.Heart rate variability is a useful method for evaluating cardiac autonomic function.The measurement of heart rate variability has been used to reflect the interaction of the sympathetic vagal index.But ECG needs at least three lead electrodes,and is often applied to the chest,delaying the signal detection records.While the pulse detection usually only needs one sensor in the finger or earlobe,with cost-effectiveness and direct usability.In the past research,the question of whether the pulse rate-variability(PRV)extracted from the pulse can replace the heart rate variability is still controversial.In this paper,the pulse rate variability and heart rate variability extracted from the sleep apnea patients during different sleep stages were analyzed using statistical principle,proving that the HRV can replace PRV.The main work includes the following aspects:1)Carrying on the accurate classification of sleep stages.The sleep stages were divided into REM sleep stages(REM)and non REM(NREM),which was divided into N1 sleep,N2 sleep,N3 sleep.In the different sleep stages,ECG and pulse signal fragments were selected including sleep apnea events respectively.2)Determining the peak point of ECG and pulse signals.For ECG,R wave peak of QRS wave extracted and the peak value of the pulse signal is selected in a period.RR interval and PP interval time series in order were saved for the future research analysis.3)Extracting HRV and PRV indices from the RR interval and PP interval time series.We aimed to investigate whether PRV extracted from finger pulse could substitute HRV from ECG during different sleep stages by analyzing the common time-domain,frequency-domain and non-linear variability indices and thus to better understand how the sleep stages affect the HRV and PRV indices for sleep apnea patients.