Effectiveness of Sleep Apnea Detection Based on One vs. Two Symmetrical EEG Channels

Typically, two symmetrical EEG channels are recorded during polysomnography (PSG). As a rule, only the recommended channel is used for sleep stage scoring or sleep apnea detection, and the other for backup. Concurrently, there are many works demonstrating the asymmetry in brain activity. The aim of this work was to compare the accuracy of sleep apnea detection with the use of features obtained from one (C3-A2 or C4-A1) versus these two symmetrical EEG channels. To this end, the relevant data from the PhysioBank database (25 whole-night PSGs) were used. The same methodology of feature extraction and selection was applied for one and combined EEG channels. Automated classification was performed using the k-nearest neighbors algorithm (kNN) with k = 12 and cityblock metric for the three classes of EEG epochs, representing normal breathing, obstructive apnea and hypopnea, and central apnea and hypopnea. The accuracy of kNN-based classification was 63.8 %, 64.3 % and 70.3 % for C3-A2, C4-A1 and both EEG channels, respectively. The statistical tests have indicated that the accuracy of classification based on two combined symmetrical EEG channels is significantly higher compared to the single-channel cases.