Refinement of an ECG-Based Approach for Detecting Awakenings in a Study on Aircraft Noise-Induced Sleep Disturbance

摘要

Nighttime aircraft noise may disturb the sleep of those living near airports. The most sensitive method for measuring this impact is electroencephalogram (EEG) based polysomnography to measure cortical awakenings. However, this approach is expensive to implement in a field study as trained individuals are needed for both data collection and visually identifying when awakenings occur. An alternative more cost effective approach is to use the electrocardiogram (ECG) to measure heart rate. An algorithm was previously developed which automatically identifies increases in heart rate associated with cortical arousals. In order to improve agreement between awakenings identified visually using EEG and automatically using ECG, refinements have been made to the ECG algorithm. These include using actigraphy (measurements of body movements) to identify additional awakenings and an algorithm for identifying sleep onset and offset based on heart rate and movement has been added. Chance-corrected agreement in awakening detection between the refined algorithm and two independent visual scorings of polysomnography data was near perfect relative to conventional standards (kappa value higher than 0.8). Therefore due to its low cost and high sensitivity in identifying awakenings, this ECG-based approach could be a useful method for examining sleep disturbance around airports.