Measures of LLE of heart rate in different frequency bands: a possible measure of relative vagal and sympathetic activity

Abstract

In this study, we investigated spectral measures and measures of nonlinear dynamics and chaos of heart rate (HR) time series in 10 normal controls and 10 patients with panic disorder (a condition associated with anxiety) during awake and sleep periods and 28 normal control subjects and 42 age-matched patients with panic disorder, in supine and standing postures. We obtained minimum embedding dimension (MED) and largest Lyapunov exponent (LLE) of unfiltered (UF) and filtered HR time series. We digitally filtered the series into very low-frequency series (VLF: <0.04 Hz ) using a low-pass filter, low-frequency series (LF: 0.04– 0.15 Hz ) using a band-pass filter and high-frequency (HF: 0.15– 0.5 Hz ) series using a high-pass filter. MED quantifies system's complexity and LLE, chaos and predictability. During sleep, there was a significant increase in LLE of UF and HF series in normal subjects. There was also a highly significant increase in LLE ( p<0.00001) in standing posture, due mainly to an increase in LLE-LF. In fact, there was a significant decrease in LLE-HF during standing posture. There was a significant decrease in LF/HF ratios of LLE during sleep ( p=0.003). While there was a highly significant increase in spectral LF/HF ratio up on standing, there was a less significant increase in the ratio of LLE (LF/HF). During sleep and supine posture, though LF/HF ratios of spectral power did not differ significantly between controls and patients with panic disorder, the ratio of LLE (LF/HF) was very significantly higher in patients ( p=0.0005), probably reflecting higher relative sympathetic activity. HF-LLE was also significantly lower in patients with panic disorder. The ratio of LLE (LF/UF) was also significantly higher ( p=0.00001) in patients with panic disorder. In other words, the net contribution of LLE-LF to the UF series was significantly more in patients with anxiety. These findings throw new light on the contribution of various frequencies in a given time series toward the UF set of data and the importance of using band analysis of nonlinear measures. These may be used as more effective clinical tools to investigate certain aspects of autonomic function such as sympathovagal interaction in addition to the most commonly used spectral powers in different bands and spectral LF/HF ratio.