Journal article

Validation of 'Somnivore', a Machine Learning Algorithm for Automated Scoring and Analysis of Polysomnography Data

Giancarlo Allocca, Sherie Ma, Davide Martelli, Matteo Cerri, Flavia Del Vecchio, Stefano Bastianini, Giovanna Zoccoli, Roberto Amici, Stephen R Morairty, Anne E Aulsebrook, Shaun Blackburn, John A Lesku, Niels C Rattenborg, Alexei L Vyssotski, Emma Wams, Kate Porcherer, Katharina Wulff, Russell Foster, Julia KM Chan, Christian L Nicholas Show all

Frontiers in Neuroscience | Frontiers Media | Published : 2019

Abstract

Manual scoring of polysomnography data is labor-intensive and time-consuming, and most existing software does not account for subjective differences and user variability. Therefore, we evaluated a supervised machine learning algorithm, SomnivoreTM, for automated wake–sleep stage classification. We designed an algorithm that extracts features from various input channels, following a brief session of manual scoring, and provides automated wake-sleep stage classification for each recording. For algorithm validation, polysomnography data was obtained from independent laboratories, and include normal, cognitively-impaired, and alcohol-treated human subjects (total n = 52), narcoleptic mice and dr..

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Grants

Awarded by Ministero dell' Universita e della Ricerca Scientifica (MIUR)


Awarded by Australian Research Council


Awarded by National Institute for Health Research (NIHR) Oxford Biomedical Research Centre


Awarded by National Health and Medical Research Council (NHMRC) Australia Project


Funding Acknowledgements

This research was supported by an Australian International Postgraduate Research Scholarship, the Ministero dell' Universita e della Ricerca Scientifica (MIUR) Project Grant 2008FY7K9S, Australian Research Council Grant DE140101075, Max Planck Society, University of Zurich, Wellcome Trust Strategic Award, National Institute for Health Research (NIHR) Oxford Biomedical Research Centre grants A90305 and A92181, National Health and Medical Research Council (NHMRC) Australia Project Grant APP1012195, the Australasian Sleep Association, an Australian Postgraduate Award, and the Australia and New Zealand Banking Group Limited (ANZ) Trustees Foundation. The funding institutes played no role in the design and conduct of the study; no role in the collection, management, analysis, or interpretation of data; and no role in the preparation, review, or approval of the manuscript.