NDLI: On separability of A-phases during the cyclic alternating pattern

Content Provider	IEEE Xplore Digital Library
Author	Mendez, M.O. Alba, A. Chouvarda, I. Milioli, G. Grassi, A. Terzano, M.G. Parrino, L.
Copyright Year	2014
Description	Author affiliation: Dept. of Neurology, Univ. of Parma, Parma, Italy (Grassi, A.; Terzano, M.G.; Parrino, L.) \|\| Fac. de Cienc., Zona Univ., San Luis Potosi, Mexico (Mendez, M.O.; Alba, A.) \|\| Lab. of Med. Inf., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece (Chouvarda, I.)
Abstract	A statistical analysis of the separability of EEG A-phases, with respect to basal activity, is presented in this study. A-phases are short central events that build up the Cyclic Alternating Pattern (CAP) during sleep. The CAP is a brain phenomenon which is thought to be related to the construction, destruction and instability of sleep stages dynamics. From the EEG signals, segments obtained around the onset and offset of the A-phases were used to evaluate the separability between A-phases and basal sleep stage oscillations. In addition, a classifier was trained to separate the different A-phase types (A1, A2 and A3). Temporal, energy and complexity measures were used as descriptors for the classifier. The results show a percentage of separation between onset and preceding basal oscillations higher than 85 % for all A-phases types. For Offset separation from following baseline, the accuracy is higher than 80 % but specificity is around 75%. Concerning to A-phase type separation, A1-phase and A3-phase are well separated with accuracy higher than 80, while A1 and A2-phases show a separation lower than 50%. These results encourage the design of automatic classifiers for Onset detection and for separating among A-phases type A1 and A3. On the other hand, the A-phase Offsets present a smooth transition towards the basal sleep stage oscillations, and A2-phases are very similar to A1-phases, suggesting that a high uncertainty may exist during CAP annotation.
Sponsorship	IEEE Eng. Med. Biol. Soc.
Starting Page	2253
Ending Page	2256
File Size	1994386
Page Count	4
File Format	PDF
ISBN	9781424479290
ISSN	1557170X
DOI	10.1109/EMBC.2014.6944068
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sleep Electroencephalography Oscillators Accuracy Complexity theory Standards Classification algorithms
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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