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% .