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Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring

INTRODUCTION: Polysomnography (PSG) is the primary tool for sleep monitoring and the diagnosis of sleep disorders. Recent advances in signal analysis make it possible to reveal more information from this rich data source. Furthermore, many innovative sleep monitoring techniques are being developed t...

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Autores principales: van Gilst, Merel M, van Dijk, Johannes P, Krijn, Roy, Hoondert, Bertram, Fonseca, Pedro, van Sloun, Ruud J G, Arsenali, Bruno, Vandenbussche, Nele, Pillen, Sigrid, Maass, Henning, van den Heuvel, Leonie, Haakma, Reinder, Leufkens, Tim R, Lauwerijssen, Coen, Bergmans, Jan W M, Pevernagie, Dirk, Overeem, Sebastiaan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886950/
https://www.ncbi.nlm.nih.gov/pubmed/31772091
http://dx.doi.org/10.1136/bmjopen-2019-030996
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author van Gilst, Merel M
van Dijk, Johannes P
Krijn, Roy
Hoondert, Bertram
Fonseca, Pedro
van Sloun, Ruud J G
Arsenali, Bruno
Vandenbussche, Nele
Pillen, Sigrid
Maass, Henning
van den Heuvel, Leonie
Haakma, Reinder
Leufkens, Tim R
Lauwerijssen, Coen
Bergmans, Jan W M
Pevernagie, Dirk
Overeem, Sebastiaan
author_facet van Gilst, Merel M
van Dijk, Johannes P
Krijn, Roy
Hoondert, Bertram
Fonseca, Pedro
van Sloun, Ruud J G
Arsenali, Bruno
Vandenbussche, Nele
Pillen, Sigrid
Maass, Henning
van den Heuvel, Leonie
Haakma, Reinder
Leufkens, Tim R
Lauwerijssen, Coen
Bergmans, Jan W M
Pevernagie, Dirk
Overeem, Sebastiaan
author_sort van Gilst, Merel M
collection PubMed
description INTRODUCTION: Polysomnography (PSG) is the primary tool for sleep monitoring and the diagnosis of sleep disorders. Recent advances in signal analysis make it possible to reveal more information from this rich data source. Furthermore, many innovative sleep monitoring techniques are being developed that are less obtrusive, easier to use over long time periods and in the home situation. Here, we describe the methods of the Sleep and Obstructive Sleep Apnoea Monitoring with Non-Invasive Applications (SOMNIA) project, yielding a database combining clinical PSG with advanced unobtrusive sleep monitoring modalities in a large cohort of patients with various sleep disorders. The SOMNIA database will facilitate the validation and assessment of the diagnostic value of the new techniques, as well as the development of additional indices and biomarkers derived from new and/or traditional sleep monitoring methods. METHODS AND ANALYSIS: We aim to include at least 2100 subjects (both adults and children) with a variety of sleep disorders who undergo a PSG as part of standard clinical care in a dedicated sleep centre. Full-video PSG will be performed according to the standards of the American Academy of Sleep Medicine. Each recording will be supplemented with one or more new monitoring systems, including wrist-worn photoplethysmography and actigraphy, pressure sensing mattresses, multimicrophone recording of respiratory sounds including snoring, suprasternal pressure monitoring and multielectrode electromyography of the diaphragm. ETHICS AND DISSEMINATION: The study was reviewed by the medical ethical committee of the Maxima Medical Center (Eindhoven, the Netherlands, File no: N16.074). All subjects provide informed consent before participation. The SOMNIA database is built to facilitate future research in sleep medicine. Data from the completed SOMNIA database will be made available for collaboration with researchers outside the institute.
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spelling pubmed-68869502019-12-04 Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring van Gilst, Merel M van Dijk, Johannes P Krijn, Roy Hoondert, Bertram Fonseca, Pedro van Sloun, Ruud J G Arsenali, Bruno Vandenbussche, Nele Pillen, Sigrid Maass, Henning van den Heuvel, Leonie Haakma, Reinder Leufkens, Tim R Lauwerijssen, Coen Bergmans, Jan W M Pevernagie, Dirk Overeem, Sebastiaan BMJ Open Research Methods INTRODUCTION: Polysomnography (PSG) is the primary tool for sleep monitoring and the diagnosis of sleep disorders. Recent advances in signal analysis make it possible to reveal more information from this rich data source. Furthermore, many innovative sleep monitoring techniques are being developed that are less obtrusive, easier to use over long time periods and in the home situation. Here, we describe the methods of the Sleep and Obstructive Sleep Apnoea Monitoring with Non-Invasive Applications (SOMNIA) project, yielding a database combining clinical PSG with advanced unobtrusive sleep monitoring modalities in a large cohort of patients with various sleep disorders. The SOMNIA database will facilitate the validation and assessment of the diagnostic value of the new techniques, as well as the development of additional indices and biomarkers derived from new and/or traditional sleep monitoring methods. METHODS AND ANALYSIS: We aim to include at least 2100 subjects (both adults and children) with a variety of sleep disorders who undergo a PSG as part of standard clinical care in a dedicated sleep centre. Full-video PSG will be performed according to the standards of the American Academy of Sleep Medicine. Each recording will be supplemented with one or more new monitoring systems, including wrist-worn photoplethysmography and actigraphy, pressure sensing mattresses, multimicrophone recording of respiratory sounds including snoring, suprasternal pressure monitoring and multielectrode electromyography of the diaphragm. ETHICS AND DISSEMINATION: The study was reviewed by the medical ethical committee of the Maxima Medical Center (Eindhoven, the Netherlands, File no: N16.074). All subjects provide informed consent before participation. The SOMNIA database is built to facilitate future research in sleep medicine. Data from the completed SOMNIA database will be made available for collaboration with researchers outside the institute. BMJ Publishing Group 2019-11-25 /pmc/articles/PMC6886950/ /pubmed/31772091 http://dx.doi.org/10.1136/bmjopen-2019-030996 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Research Methods
van Gilst, Merel M
van Dijk, Johannes P
Krijn, Roy
Hoondert, Bertram
Fonseca, Pedro
van Sloun, Ruud J G
Arsenali, Bruno
Vandenbussche, Nele
Pillen, Sigrid
Maass, Henning
van den Heuvel, Leonie
Haakma, Reinder
Leufkens, Tim R
Lauwerijssen, Coen
Bergmans, Jan W M
Pevernagie, Dirk
Overeem, Sebastiaan
Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
title Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
title_full Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
title_fullStr Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
title_full_unstemmed Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
title_short Protocol of the SOMNIA project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
title_sort protocol of the somnia project: an observational study to create a neurophysiological database for advanced clinical sleep monitoring
topic Research Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886950/
https://www.ncbi.nlm.nih.gov/pubmed/31772091
http://dx.doi.org/10.1136/bmjopen-2019-030996
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