Deep learning assisting clinicians to diagnose insomnia

Sleep analysis suffers from a lack of automated monitoring and diagnostic tools. Therefore, the results of this study are promising, because using deep learning on EEG they were able to accurately differentiate between 42 insomniac patients and 41 healthy controls. A set of 57 EEG features was extracted from a maximum of two EEG channels and the algorithm achieved an overall discrimination accuracy of 92% and 86% between two groups using two and one EEG channels respectively. (Read more)


Posted on 10 feb 2017

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Abstract Book available

 The complete Abstract Book for the Zurich 2018 Meeting is available now

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Final Program

The final program for the IPEG Meeting November 21st-25th in Zurich is ready for download HERE

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Preliminary Programm ZURICH IPEG Meeting 2018

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