Automatic detection of spindles and K-complexes in sleep EEG using switching multiple models

Abstract

This work investigates the use of switching linear Gaussian state space models for the segmentation and automatic labelling of Stage 2 sleep EEG data characterised by spindles and K-complexes. The advantage of this approach is that it offers a unified framework of detecting multiple transient events within background EEG data. Specifically for the… (More)
DOI: 10.1016/j.bspc.2014.01.010

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@article{Camilleri2014AutomaticDO, title={Automatic detection of spindles and K-complexes in sleep EEG using switching multiple models}, author={Tracey A. Camilleri and Kenneth P. Camilleri and Simon G. Fabri}, journal={Biomed. Signal Proc. and Control}, year={2014}, volume={10}, pages={117-127} }