Processing of ECG and Breathing Signals to Study the Correlation of Respiration Waveform Time Intervals with HF and LF Powers of Heart Rate Variability

The aim of this paper is to present a designed software platform for the processing of electrocardiographic (ECG) and breathing signals in order to study the correlation of respiration waveform time intervals with high frequency (HF) and low frequency (LF) powers of heart rate variability (HRV). The software was tested with signals from 5 minutes recordings, including respiration paces of 12, 9, and 6 breaths per minute. Wavelet based software was used to locate the R waves of an ECG signal, in order to obtain a tachogram used to calculate parameters of HRV. Special software was developed to process breathing signals to identify defined points of the respiration waveforms and to calculate their time intervals to study the correlation of these time intervals with HF and LF powers of HRV. These powers are traditionally associated with parasympathetic and sympathetic activity, respectively. The paper presents a description of the developed signal processing software and the obtained test results.