Detecting Electrophysiologic Abnormalities in Chronic Insomnia Using Detrended Fluctuation Analysis

INTRODUCTION Chronic insomnia is a disorder characterized by difficulty initiating or maintaining sleep along with effects on the waking functions such as mood and cognitive function. Chronic insomnia affects nearly 10% of the adult population. Current theoretical models of insomnia focus on homeostatic sleep-wake control mechanisms, hyper-arousal, and rapid eye movement (REM) instability; however, none of these theories have yielded consistent findings. Many studies of insomnia focus on using spectral analysis to identify insomnia-specific characteristics in the sleep EEG, but recent data suggest non-stationary biologic signals such as the EEG and ECG are characterized by long-range (fractal) correlations and therefore require additional analysis techniques to account for this behavior. Fractal analysis methods have been developed to calculate the long-range correlation factor called the fractal dimension. The fractal dimension represents the relative self-similarity or ‘complexity’ of a given signal. Previous Biomedical applications have examined the fractal dimension of: inter-spike-intervals of neuron firing, inter-stride-intervals of human walking, inter-breath-intervals of human respiration, and inter-beat-intervals of the human heart, and is able to differentiate between different pathologic conditions. For the purpose of this study, we chose the Detrended Fluctuation Analysis (DFA) method of calculating the fractal dimension for its recent success in cardiovascular research. The objectives of this project are to compare the fractal dimension of two different sleep states across the night: Non Rapid Eye Movement (NREM) and Rapid Eye Movement (REM) in individuals with insomnia versus healthy individuals; as well as attempting to build a better explanatory model of the disorder.