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Methods of analysis of electroencephalogram (EEG) signals using artificial neural networks are presented, as well as subsequent methods of detection of obstructive sleep apnoea (OSA). The methods of detection described are based on post-processing sleep state probabilities obtained with a 10-6-4 multi-layer perceptron. Results show periodic changes in sleep states highly correlated with changes in blood oxygen saturation.

Original publication

DOI

10.1049/cp:19950594

Type

Journal article

Journal

IEE Conference Publication

Publication Date

01/01/1995

Pages

427 - 432