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Analysis of sympathovagal balance in patients with major depressive disorder using wavelet packet transform

机译:小波包变换患者对重大抑郁症患者的同性化平衡分析

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Elevated rates of cardiac morbidity have been frequently reported in major depressive disorder (MDD) patients as a result of the relationship between autonomic dysfunctions and varied cardiovascular activity. Heart rate variability (HRV) analysis is an important and non-invasive way for assessing the variances in autonomic nervous system activity of MDD patients. In spectral domain, HRV analysis is usually done by either Fourier transformation (FT) or discrete wavelet transformation (DWT) to divide the data into lowfrequency (LF) and high-frequency (HF) bands. However, while FT is not a proper method for non-stationary HRV data, DWT does not exactly produce required frequency ranges of each LF and HF bands. The purpose of the present study is to investigate the spectral HRV measures obtained by wavelet packet transform (WPT) with absolutely excellent approximation to predefined frequency ranges of bands. Eighteen healthy controls and age- and gender-match eighteen patients with MDD were participated in this study. Sympathovagal balance (LF/HF ratio) that reflects the variation of sympathetic and parasympathetic activities was compared between two groups. Individuals with depression had a significantly higher LF/HF ratio. Our findings suggest that dysfunctions in coordination between sympathetic and parasympathetic nervous system activity in MDD patients can be evaluated by WPT based HRV analysis with high resolution decomposition for required LF and HF bands.
机译:由于自主神经功能障碍和变化的心血管活动之间的关系,在主要抑郁症(MDD)患者中经常报告心脏病率的升高。心率变异性(HRV)分析是评估MDD患者的自主神经系统活动中的差异的重要和非侵入性方式。在谱域中,HRV分析通常是由任一傅里叶变换(FT)或离散小波变换(DWT)来完成的数据分割成低频(LF)和高频率(HF)带。然而,虽然FT不是用于非静止HRV数据的适当方法,但DWT不完全产生每个LF和HF频带的所需频率范围。本研究的目的是研究通过小波分组变换(WPT)获得的光谱HRV测量,其与预定义频率范围的绝对优异的近似。在这项研究中参加了十八次健康的控制和年龄和性别匹配的18名MDD患者。在两组之间比较了反映了交感神经和副交感神经活性变异的同性化平衡(LF / HF比率)。具有抑郁症的个体具有显着较高的LF / HF比率。我们的研究结果表明,在MDD患者的交感和副交感神经系统活动之间的协调功能障碍可以通过与所需LF和HF频段高分辨率分解根据WPT HRV分析评估。

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