Characterization of A phases during the Cyclic Alternating Pattern of sleep

ObjectiveThis study aims to identify, starting from a single EEG trace, quantitative distinctive features characterizing the A phases of the Cyclic Alternating Pattern (CAP).MethodsThe C3-A2 or C4-A1 EEG leads of the night recording of eight healthy adult subjects were used for this analysis. CAP was scored by an expert and the portions relative to NREM were selected. Nine descriptors were computed: band descriptors (low delta, high delta, theta, alpha, sigma and beta); Hjorth activity in the low delta and high delta bands; differential variance of the EEG signal. The information content of each descriptor in recognizing the A phases was evaluated through the computation of the ROC curves and the statistics sensitivity, specificity and accuracy.ResultsThe ROC curves show that all the descriptors have a certain significance in characterizing A phases. The average accuracy obtained by thresholding the descriptors ranges from 59.89 (sigma descriptor) to 72.44 (differential EEG variance).ConclusionsThe results show that it is possible to attribute a significant quantitative value to the information content of the descriptors.SignificanceThis study gives a mathematical confirm to the features of CAP generally described qualitatively, and puts the bases for the creation of automatic detection methods.

► A quantitative mathematical characterization of sleep microstructure. ► A study that puts the bases for the implementation of an automatic classifier of the Cyclic Alternating Pattern. ► A novel approach to sleep analysis that gives a mathematical confirmation to the medical literature about CAP.