Investigation of heart rate variability in major depression patients using wavelet packet transform.

Studies conducted in major depression (MD) patients have reported a high risk of cardiac morbidity as a result of the relationship between changed cardiovascular activity (CA) and autonomic dysfunctions. The investigation of heart rate variability (HRV) gives valuable idea about variances in autonomic CA of MD patients. To get this knowledge, frequency-domain HRV analysis is frequently performed using Fourier transformation (FT) or discrete-wavelet transformation (DWT) to decompose the data into high-frequency (HF) and low-frequency (LF) bands. Nevertheless, it has been reported that the FT is not useful for nonstationary HRV signals and the DWT does not ensure required frequency boundaries of each band. This study aims to compare the frequency-domain HRV features using wavelet-packet-transform (WPT) with absolutely excellent approximation to required band ranges between the controls and patients. In addition to LF and HF band energies, sympathovagal balance that indicates the variation of sympathetic and parasympathetic activities were compared between two groups. Patients had a significantly lower HF energy, higher values of LF energy and higher LF/HF ratio. Our results recommend that impairments in coordination between parasympathetic and sympathetic behavior in MD patients can be assessed by HRV analysis using WPT with high resolution decomposition for needed bands.