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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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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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. |
format | Online Article Text |
id | pubmed-6886950 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
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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