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The Sleep Revolution project: the concept and objectives

The Sleep Revolution project: the concept and objectives
The Sleep Revolution project: the concept and objectives

Obstructive sleep apnea is linked to severe health consequences such as hypertension, daytime sleepiness, and cardiovascular disease. Nearly a billion people are estimated to have obstructive sleep apnea with a substantial economic burden. However, the current diagnostic parameter of obstructive sleep apnea, the apnea–hypopnea index, correlates poorly with related comorbidities and symptoms. Obstructive sleep apnea severity is measured by counting respiratory events, while other physiologically relevant consequences are ignored. Furthermore, as the clinical methods for analysing polysomnographic signals are outdated, laborious, and expensive, most patients with obstructive sleep apnea remain undiagnosed. Therefore, more personalised diagnostic approaches are urgently needed. The Sleep Revolution, funded by the European Union's Horizon 2020 Research and Innovation Programme, aims to tackle these shortcomings by developing machine learning tools to better estimate obstructive sleep apnea severity and phenotypes. This allows for improved personalised treatment options, including increased patient participation. Also, implementing these tools will alleviate the costs and increase the availability of sleep studies by decreasing manual scoring labour. Finally, the project aims to design a digital platform that functions as a bridge between researchers, patients, and clinicians, with an electronic sleep diary, objective cognitive tests, and questionnaires in a mobile application. These ambitious goals will be achieved through extensive collaboration between 39 centres, including expertise from sleep medicine, computer science, and industry and by utilising tens of thousands of retrospectively and prospectively collected sleep recordings. With the commitment of the European Sleep Research Society and Assembly of National Sleep Societies, the Sleep Revolution has the unique possibility to create new standardised guidelines for sleep medicine.

apnea–hypopnea index, costs, digital management platform, e-health, exercise, lifestyles, machine learning, mobile application, neurocognitive tests, P4 medicine, participatory, patient-reported outcome measures, polysomnography, self-applied home testing, sleep diary, sleep revolution, telemedicine
0962-1105
Arnardottir, Erna S.
9bfbbe32-8214-47a9-86ba-43be85458830
Islind, Anna Sigridur
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Óskarsdóttir, María
d159ed8f-9dd3-4ff3-8b00-d43579ab71be
Ólafsdóttir, Kristín A.
bc19e9e1-b89f-4d77-b5cb-782af3af3437
August, Elias
bfc9e819-064c-41cd-bac0-ac46a4de935f
Jónasdóttir, Lára
1c5e1a93-c051-4952-a7ea-3f2d37269fb8
Hrubos-Strøm, Harald
944cd356-78df-4daf-855f-004ebb306b23
Saavedra, Jose M.
9d081037-3b92-40fe-974a-5f4bb55da8e9
Grote, Ludger
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Hedner, Jan
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Höskuldsson, Sveinbjörn
17aaf3c0-e29d-4224-a5c6-54b29b02b2ae
Ágústsson, Jón Skírnir
1f0f5bd0-e2f4-47d8-89ab-01048cf88313
Jóhannsdóttir, Kamilla Rún
5854a6d6-6df4-4a36-aa8d-76ed4da0319d
McNicholas, Walter T.
c2dbbc15-2729-4f7b-8b33-6ff029313e29
Pevernagie, Dirk
fc662b55-509a-4aee-9217-86dcc3cc1e6b
Sund, Reijo
d4d39bb0-3982-496a-938c-c3113e00023e
Töyräs, Juha
d12501f8-5b0f-46cd-95f1-7c8f178b2312
Leppänen, Timo
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Sleep Revolution
Arnardottir, Erna S.
9bfbbe32-8214-47a9-86ba-43be85458830
Islind, Anna Sigridur
46e6353f-a1b6-4628-916c-18e817695d03
Óskarsdóttir, María
d159ed8f-9dd3-4ff3-8b00-d43579ab71be
Ólafsdóttir, Kristín A.
bc19e9e1-b89f-4d77-b5cb-782af3af3437
August, Elias
bfc9e819-064c-41cd-bac0-ac46a4de935f
Jónasdóttir, Lára
1c5e1a93-c051-4952-a7ea-3f2d37269fb8
Hrubos-Strøm, Harald
944cd356-78df-4daf-855f-004ebb306b23
Saavedra, Jose M.
9d081037-3b92-40fe-974a-5f4bb55da8e9
Grote, Ludger
0dd25ae3-4333-4d15-b572-292bc1c7e788
Hedner, Jan
172eb4b2-abf1-423b-8a8c-cf031e93fbe4
Höskuldsson, Sveinbjörn
17aaf3c0-e29d-4224-a5c6-54b29b02b2ae
Ágústsson, Jón Skírnir
1f0f5bd0-e2f4-47d8-89ab-01048cf88313
Jóhannsdóttir, Kamilla Rún
5854a6d6-6df4-4a36-aa8d-76ed4da0319d
McNicholas, Walter T.
c2dbbc15-2729-4f7b-8b33-6ff029313e29
Pevernagie, Dirk
fc662b55-509a-4aee-9217-86dcc3cc1e6b
Sund, Reijo
d4d39bb0-3982-496a-938c-c3113e00023e
Töyräs, Juha
d12501f8-5b0f-46cd-95f1-7c8f178b2312
Leppänen, Timo
823b7fba-368c-4ebd-8bef-538e3829d725

Sleep Revolution (2022) The Sleep Revolution project: the concept and objectives. Journal of Sleep Research, 31 (4), [e13630]. (doi:10.1111/jsr.13630).

Record type: Review

Abstract

Obstructive sleep apnea is linked to severe health consequences such as hypertension, daytime sleepiness, and cardiovascular disease. Nearly a billion people are estimated to have obstructive sleep apnea with a substantial economic burden. However, the current diagnostic parameter of obstructive sleep apnea, the apnea–hypopnea index, correlates poorly with related comorbidities and symptoms. Obstructive sleep apnea severity is measured by counting respiratory events, while other physiologically relevant consequences are ignored. Furthermore, as the clinical methods for analysing polysomnographic signals are outdated, laborious, and expensive, most patients with obstructive sleep apnea remain undiagnosed. Therefore, more personalised diagnostic approaches are urgently needed. The Sleep Revolution, funded by the European Union's Horizon 2020 Research and Innovation Programme, aims to tackle these shortcomings by developing machine learning tools to better estimate obstructive sleep apnea severity and phenotypes. This allows for improved personalised treatment options, including increased patient participation. Also, implementing these tools will alleviate the costs and increase the availability of sleep studies by decreasing manual scoring labour. Finally, the project aims to design a digital platform that functions as a bridge between researchers, patients, and clinicians, with an electronic sleep diary, objective cognitive tests, and questionnaires in a mobile application. These ambitious goals will be achieved through extensive collaboration between 39 centres, including expertise from sleep medicine, computer science, and industry and by utilising tens of thousands of retrospectively and prospectively collected sleep recordings. With the commitment of the European Sleep Research Society and Assembly of National Sleep Societies, the Sleep Revolution has the unique possibility to create new standardised guidelines for sleep medicine.

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More information

Accepted/In Press date: 19 April 2022
Published date: 30 June 2022
Additional Information: Publisher Copyright: © 2022 European Sleep Research Society.
Keywords: apnea–hypopnea index, costs, digital management platform, e-health, exercise, lifestyles, machine learning, mobile application, neurocognitive tests, P4 medicine, participatory, patient-reported outcome measures, polysomnography, self-applied home testing, sleep diary, sleep revolution, telemedicine

Identifiers

Local EPrints ID: 508382
URI: http://eprints.soton.ac.uk/id/eprint/508382
ISSN: 0962-1105
PURE UUID: 704eadd6-6388-4e08-a0d9-9b42327eea98
ORCID for María Óskarsdóttir: ORCID iD orcid.org/0000-0001-5095-5356

Catalogue record

Date deposited: 20 Jan 2026 17:47
Last modified: 21 Jan 2026 03:11

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Contributors

Author: Erna S. Arnardottir
Author: Anna Sigridur Islind
Author: María Óskarsdóttir ORCID iD
Author: Kristín A. Ólafsdóttir
Author: Elias August
Author: Lára Jónasdóttir
Author: Harald Hrubos-Strøm
Author: Jose M. Saavedra
Author: Ludger Grote
Author: Jan Hedner
Author: Sveinbjörn Höskuldsson
Author: Jón Skírnir Ágústsson
Author: Kamilla Rún Jóhannsdóttir
Author: Walter T. McNicholas
Author: Dirk Pevernagie
Author: Reijo Sund
Author: Juha Töyräs
Author: Timo Leppänen
Corporate Author: Sleep Revolution

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