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Emerging Trends in Technological Innovation First IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2010, Costa de Caparica, Portugal, February 22-24, 2010 |
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Conference papers
A Contribution for the Automatic Sleep Classification Based on the Itakura-Saito Spectral Distance
Abstract : Sleep staging is a crucial step before the scoring
the sleep apnoea, in subjects that are tested for this condition. These
patients undergo a whole night polysomnography recording that includes
EEG, EOG, ECG, EMG and respiratory signals. Sleep staging refers to the
quantification of its depth. Despite the commercial sleep software being
able to stage the sleep, there is a general lack of confidence amongst
health practitioners of these machine results. Generally the sleep
scoring is done over the visual inspection of the overnight patient EEG
recording, which takes the attention of an expert medical practitioner
over a couple of hours. This contributes to a waiting list of two years
for patients of the Portuguese Health Service. In this work we have used
a spectral comparison method called Itakura distance to be able to make
a distinction between sleepy and awake epochs in a night EEG recording,
therefore automatically doing the staging. We have used the data from 20
patients of Hospital Pulido Valente, which had been previously visually
expert scored. Our technique results were promising, in a way that
Itakura distance can, by itself, distinguish with a good degree of
certainty the N2, N3 and awake states. Pre-processing stages for
artefact reduction and baseline removal using Wavelets were
applied.
Cited literature [9 references]
https://hal.inria.fr/hal-01060761
Contributor : Hal Ifip <>
Submitted on : Friday, November 17, 2017 - 5:05:38 PM
Last modification on : Wednesday, November 29, 2017 - 11:39:34 AM
Long-term archiving on: : Sunday, February 18, 2018 - 5:11:09 PM
Contributor : Hal Ifip <>
Submitted on : Friday, November 17, 2017 - 5:05:38 PM
Last modification on : Wednesday, November 29, 2017 - 11:39:34 AM
Long-term archiving on: : Sunday, February 18, 2018 - 5:11:09 PM
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