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.