Power Spectral Distribution Analysis Of Rr Intervals In Ecg Under Normal And Different Diseases

ABSTRACT

Analysis on spectral distribution of beat to beat (RR intervals) in Electrocardiography (ECG) signal became an important tool in biomedical signal processing for studying heart rate variability (HRV). Heart signals allow for a comprehensive analysis of the heart. Electrocardiography uses electrodes to measure the electrical activity of the heart. Extracting ECG signals is a non invasive process that opens the door to new possibilities for the application of advanced signals processing and data analysis techniques in the diagnosis of heart diseases.

In this dissertation the analysis on the spectral distribution (SD) of RR under different conditions has been done from Normal as well diseased ECG data to find the features on their Power spectral density curves. Two mathematical approaches, Periodogram and Autoregressive (AR) modeling methods are used to calculate PSD curves of the analyzed data. Correlative coefficient method is chosen to find the relationship between two PSD curves of Periodogram and AR modeling method for evaluating the consistence of two PSD methods. The results show that the two methods are consistent. Then, SDs of RR for Normal and diseases ECG data was calculated and analyzed. The experimental results showed that there are differences between SDs of RR of Normal and diseases ECG data. There is also a difference between SDs of RR of different heart diseases. These new findings probably have a role in guiding diagnosis of different heart diseases.