Sleep and Wake Classification With ECG and Respiratory Effort Signals

Abstract

We describe a method for the online classification of sleep/wake states based on cardiorespiratory signals produced by wearable sensors. The method was conceived in view of its applicability to a wearable sleepiness monitoring device. The method uses a fast Fourier transform as the main feature extraction tool and a feedforward artificial neural network as… (More)
DOI: 10.1109/TBCAS.2008.2008817

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@article{Karlen2009SleepAW, title={Sleep and Wake Classification With ECG and Respiratory Effort Signals}, author={Walter Karlen and Claudio Mattiussi and Dario Floreano}, journal={IEEE Transactions on Biomedical Circuits and Systems}, year={2009}, volume={3}, pages={71-78} }