Heart Beat Rate Variability Analysis Using Statistical Methods

Abstract

Heart Rate Variability (HRV) Represent one of the most promising markers which represent anon invasive way of measuring autonomic nervous system(ANS), it describes the variation over time of both instantaneous heart rate and the interval between consecutive heart beats. Previously traditional methods had been used for calculating heart beat as using hand with time , and after the appearance of the new method and devices those depend on computer program the HRV analysis become more easier and more accurate, thus this is the primary purpose of use the statistical methods to analyze HRV using Mat lab program. New method has been proposed to analyze HRV using statistical methods by using the matlab program. HRV analysis was divided into four phases ,in the first phase a pre processing was done to remove power line interference and the base line wander using second order IIR notch filter "pole-zero placement" and fourth order chebyshev band pass filter "bilinear transformation" respectively. Secondly, discrete wavelet transformation was applied on ECG signals as one of the robust features ,which were subsequently used for next phase. The third phase detection of R peak and RR interval were calculated from the wavelet vector, different statistical features were calculated as an input for classification phase. Finally, classifier was designed to differentiate between normality and abnormality. Results obtained from this work are acceptable when compare it with previous studies results and result in the same data base, the accuracy of this work represent 95% .