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Investigation of heart rate variability in major depression patients using wavelet packet transform
Saime Akdemir Akar1, Sadık Kara1, Vedat Bilgiç2
1Institute of Biomedical Engineering, Fatih University, Istanbul 34500, Turkey.
Insights
Major depression patients show altered heart rate variability (HRV) due to autonomic dysfunction. Wavelet-packet transform (WPT) analysis revealed impaired parasympathetic and sympathetic coordination in these patients.
Area of Science:
- Cardiology
- Psychiatry
- Biomedical Engineering
Background:
- Major depression (MD) is linked to increased cardiac risk via autonomic dysfunction.
- Heart rate variability (HRV) analysis offers insights into autonomic control in MD patients.
- Traditional frequency-domain HRV methods (FT, DWT) have limitations with nonstationary signals and frequency band accuracy.
Purpose of the Study:
- To compare frequency-domain HRV features using wavelet-packet transform (WPT) between MD patients and controls.
- To assess sympathovagal balance and band energies (LF, HF) using high-resolution WPT.
Main Methods:
- Employed wavelet-packet transform (WPT) for detailed frequency-domain HRV analysis.
- Analyzed low-frequency (LF) and high-frequency (HF) band energies.
- Calculated the LF/HF ratio to represent sympathovagal balance.
Main Results:
- MD patients exhibited significantly lower HF energy compared to controls.
- Patients showed higher LF energy and an elevated LF/HF ratio.
- These findings indicate impaired coordination between sympathetic and parasympathetic activity.
Conclusions:
- WPT provides high-resolution decomposition for accurate HRV analysis in MD.
- HRV analysis using WPT can effectively assess autonomic dysregulation in major depression.
- Impaired sympathovagal balance is a key feature of autonomic dysfunction in MD patients.
Abstract:
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.
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