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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.
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.
||self-organizing maps, neural gas, sleep spindles, EEG
||Faculty of Technology, Research Groups in Informatics
||Data processing, computer science, computer systems
Estévez, Pablo A. ; Zilleruelo-Ramos, Ricardo ; Hernández, Rodrigo ; Causa, Leonardo ; Held, Claudio M. (2007) Sleep Spindle Detection by Using Merge Neural Gas.