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% .
