Automatic identification of Cyclic Alternating Pattern (CAP) sequences based on the Teager Energy Operator

The Cyclic Alternating Pattern (CAP) is a periodic cerebral activity prevalent during Non-Rapid Eye Movement (NREM) sleep-stages. The CAP is composed by A-phases that are related to a change in amplitude, frequency or both from the background activity epochs, called B-phases. Depending on the type of increase the A-phase could be classified as A1, A2 or A3 subtype. This paper proposes the usage of the Teager Energy Operator (TEO) to analyze the amplitude changes in the different frequency-bands to detect A-phases subtypes. The TEO classification performance is compared with the performance of a state-of-the art EEG feature, applied previously for CAP scoring and referred as the macro-micro structure descriptor (MMSD). In general, the TEO is the best feature and the improved results were obtained in the delta band for the A1 and A2 sub-types. More precisely, a sensitivity and specificity of 80.31% and 82.93% were obtained for the A1 subtype, respectively. A2 phases were detected with 76.96% of sensitivity and 73.22% of specificity. The two features detected A3 subtype with approximately the same sensitivity (approx. 70%) and specificity (approx. 75%), however the results were improved by considering the highest frequency band. These results are consistent with the frequency content of the different sub-phases.