Using the wavelet packet transform in automatic sleep analysis
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The unavailability of an accurate and robust automatic sleep analyzer has hindered sleep researchers in understanding sleep and its effects. During the last few decades, different EEG signal processing techniques have been applied to develop an automated sleep stage classification system. In this paper we will discuss the innovative spectral analysis techniques, specifically time-frequency techniques, which have been applied to sleep staging with some success. In this paper we will discuss the application of the wavelet packet (WP) transform on sleep EEG for the detection of sleep spindles. The results obtained from our study will be presented and the suitability of the WP transform for the identification of sleep spindles discussed. © 2009 Springer Berlin Heidelberg.
author list (cited authors)
Ahmed, B., & Tafreshi, R.