Automatic detection of micro-arousals.
In patients suffering from various sleep disorders and some elderly patients, sleep is disturbed with frequent but brief arousal. These events do not cause behavioral awakening, but can lead to excessive day time sleepiness. These brief arousals or microarousals (MAs) can be identified on a standard polysomnogram as a transient abrupt change of frequency, typically in the alpha and extended beta (16-40 Hz) bands. In this paper, we present a novel method to automatically detect MAs. The method is based on using the ideas of segmentation, spectral feature extraction and the identification of EEG epochs containing MA with statistical methods and decisional rules. Full-night EEG recordings from two patients are used to present some initial performance results. For this analysis, the MA events are independently scored by three experienced sleep experts. Results show the method to be promising; however, due to the large inter-scorer variations it may be necessary to tailor the detection threshold to address the varying scorer preferences (address the sensitivity/specificity tradeoffs).
Agarwal
Rajeev
R
Department of Electrical and Computer Engineering, Concordia University, 1455 de Maisonneuve Blvd. West, Montreal, Quebec, Canada, H3G 1M8, Stellate, 376 Victoria Ave. Montreal, Canada, H3Z 1C3. Email: ragarwal@stellate.com.