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Sleep Spindle Detection by Using Merge Neural Gas

Estévez, Pablo A. ; Zilleruelo-Ramos, Ricardo ; Hernández, Rodrigo ; Causa, Leonardo ; Held, Claudio M.

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Abstract:

In this paper the Merge Neural Gas (MNG) model is applied to detect sleep spindles in EEG. Features are extracted from windows of the EEG by using short time Fourier transform. The total power spectrum is computed in six frequency bands and used as input to the MNG network. The results show that MNG outperforms simple neural gas in correctly detecting sleep spindles. In addition the temporal quantization results as well as sleep trajectories are visualized on two-dimensional maps by using the OVING projection method.

DOI: 10.2390/biecoll-wsom2007-149

Keywords:		self-organizing maps, neural gas, sleep spindles, EEG
Institution:		Faculty of Technology, Research Groups in Informatics
DDC classification:		Data processing, computer science, computer systems

Suggested Citation:

Estévez, Pablo A. ; Zilleruelo-Ramos, Ricardo ; Hernández, Rodrigo ; Causa, Leonardo ; Held, Claudio M. (2007) Sleep Spindle Detection by Using Merge Neural Gas.

URL: http://biecoll.ub.uni-bielefeld.de/volltexte/2007/148

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Latest update: 15 Feb 2011
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