Detrended fluctuation analysis and spectral analysis of heart rate variability for sleep stage and sleep apnea identification

Abstract

In a systematic study we compared the performance of spectral analysis and detrended fluctuation analysis (DFA) to discriminate sleep stages and sleep apnea. We investigated 14 healthy subjects, 33 patients with moderate, and 31 patients with severe sleep apnea with polysomnography. Discriminance analysis was used on a person and sleep stage basis to determine the best method for the separation of sleep stages and sleep apnea severity. Using spectral parameters 69.7% of the apnea severity assignments and 54.6% of the sleep stage assignments were correct, while using scaling analysis these numbers increased to 74.4% and 85.0%, respectively. Changes in heart rate variability are better quantified by scaling analysis than by spectral analysis. 1. Introduction Sleep as the absence of wakefulness and the missing ability to react on external stimuli is regarded as a unbiased test situation for the autonomic nervous system [1]. Sleep is not just a constant state controlled by metabolic needs for the body being at rest. Instead sleep consists of different well defined sleep stages which follow a well structured temporal order in normal restorative sleep. Heart rate and heart rate variability vary with the sleep stages, and their normal variability is affected in sleep disorders. It has been shown that autonomic activity changes from waking to sleep. Big differences were found between non-REM and REM sleep [2]. Sympathetic tone drops progressively from wakefulness over sleep stage 1 to 4. In contrast REM sleep was characterized by increased sympathetic tone [3]. Parasympathetic tone increases from wakefulness to non-REM sleep. Periods of wakefulness during sleep were found to have an intermediate position between non-REM and REM sleep [4]. Sleep apnea affects heart rate variability during sleep described as cyclical variation of heart rate [5]. The recording of cyclical variation of heart rate together with snoring has been used in order to detect obstructive sleep apnea with ambulatory recording devices [6]. It can be assumed that the cyclical variation of heart rate can be detected by spectral analysis if the appropriate frequency range is investigated. The pattern of bradycardia and tachycardia during apnea has been attributed to an effective parasympathetic control of heart rate during sleep [7] interrupted by sympathetic activation accompanying the intermittent apnea-terminating arousals. Spectral analysis of heart rate variability is well established and provides a quantitative evaluation of sympathetic and parasympathetic activation of the heartbeat [8]. Three major oscillatory components were identified. The physiological interpretation of the very-low-frequency (VLF) component (< 0.04 Hz) is still discussed, the low-frequency (LF) component (0.04-0.15 Hz) reflects baroreflex sympathetic control of blood pressure, and the high-frequency (HF) component (0.15-0.4 Hz) reflects respiratory rhythm and is believed to be related to parasympathetic control of heart rate [9]. Detrended fluctuation analysis (DFA) method ha...

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