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The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging
STUDY OBJECTIVES: The development of ambulatory technologies capable of monitoring brain activity during sleep longitudinally is critical for advancing sleep science. The aim of this study was to assess the signal acquisition and the performance of the automatic sleep staging algorithms of a reduced...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751170/ https://www.ncbi.nlm.nih.gov/pubmed/32433768 http://dx.doi.org/10.1093/sleep/zsaa097 |
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author | Arnal, Pierrick J Thorey, Valentin Debellemaniere, Eden Ballard, Michael E Bou Hernandez, Albert Guillot, Antoine Jourde, Hugo Harris, Mason Guillard, Mathias Van Beers, Pascal Chennaoui, Mounir Sauvet, Fabien |
author_facet | Arnal, Pierrick J Thorey, Valentin Debellemaniere, Eden Ballard, Michael E Bou Hernandez, Albert Guillot, Antoine Jourde, Hugo Harris, Mason Guillard, Mathias Van Beers, Pascal Chennaoui, Mounir Sauvet, Fabien |
author_sort | Arnal, Pierrick J |
collection | PubMed |
description | STUDY OBJECTIVES: The development of ambulatory technologies capable of monitoring brain activity during sleep longitudinally is critical for advancing sleep science. The aim of this study was to assess the signal acquisition and the performance of the automatic sleep staging algorithms of a reduced-montage dry-electroencephalographic (EEG) device (Dreem headband, DH) compared to the gold-standard polysomnography (PSG) scored by five sleep experts. METHODS: A total of 25 subjects who completed an overnight sleep study at a sleep center while wearing both a PSG and the DH simultaneously have been included in the analysis. We assessed (1) similarity of measured EEG brain waves between the DH and the PSG; (2) the heart rate, breathing frequency, and respiration rate variability (RRV) agreement between the DH and the PSG; and (3) the performance of the DH’s automatic sleep staging according to American Academy of Sleep Medicine guidelines versus PSG sleep experts manual scoring. RESULTS: The mean percentage error between the EEG signals acquired by the DH and those from the PSG for the monitoring of α was 15 ± 3.5%, 16 ± 4.3% for β, 16 ± 6.1% for λ, and 10 ± 1.4% for θ frequencies during sleep. The mean absolute error for heart rate, breathing frequency, and RRV was 1.2 ± 0.5 bpm, 0.3 ± 0.2 cpm, and 3.2 ± 0.6%, respectively. Automatic sleep staging reached an overall accuracy of 83.5 ± 6.4% (F1 score: 83.8 ± 6.3) for the DH to be compared with an average of 86.4 ± 8.0% (F1 score: 86.3 ± 7.4) for the 5 sleep experts. CONCLUSIONS: These results demonstrate the capacity of the DH to both monitor sleep-related physiological signals and process them accurately into sleep stages. This device paves the way for, large-scale, longitudinal sleep studies. CLINICAL TRIAL REGISTRATION: NCT03725943. |
format | Online Article Text |
id | pubmed-7751170 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-77511702020-12-29 The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging Arnal, Pierrick J Thorey, Valentin Debellemaniere, Eden Ballard, Michael E Bou Hernandez, Albert Guillot, Antoine Jourde, Hugo Harris, Mason Guillard, Mathias Van Beers, Pascal Chennaoui, Mounir Sauvet, Fabien Sleep Sleep, Health and Disease STUDY OBJECTIVES: The development of ambulatory technologies capable of monitoring brain activity during sleep longitudinally is critical for advancing sleep science. The aim of this study was to assess the signal acquisition and the performance of the automatic sleep staging algorithms of a reduced-montage dry-electroencephalographic (EEG) device (Dreem headband, DH) compared to the gold-standard polysomnography (PSG) scored by five sleep experts. METHODS: A total of 25 subjects who completed an overnight sleep study at a sleep center while wearing both a PSG and the DH simultaneously have been included in the analysis. We assessed (1) similarity of measured EEG brain waves between the DH and the PSG; (2) the heart rate, breathing frequency, and respiration rate variability (RRV) agreement between the DH and the PSG; and (3) the performance of the DH’s automatic sleep staging according to American Academy of Sleep Medicine guidelines versus PSG sleep experts manual scoring. RESULTS: The mean percentage error between the EEG signals acquired by the DH and those from the PSG for the monitoring of α was 15 ± 3.5%, 16 ± 4.3% for β, 16 ± 6.1% for λ, and 10 ± 1.4% for θ frequencies during sleep. The mean absolute error for heart rate, breathing frequency, and RRV was 1.2 ± 0.5 bpm, 0.3 ± 0.2 cpm, and 3.2 ± 0.6%, respectively. Automatic sleep staging reached an overall accuracy of 83.5 ± 6.4% (F1 score: 83.8 ± 6.3) for the DH to be compared with an average of 86.4 ± 8.0% (F1 score: 86.3 ± 7.4) for the 5 sleep experts. CONCLUSIONS: These results demonstrate the capacity of the DH to both monitor sleep-related physiological signals and process them accurately into sleep stages. This device paves the way for, large-scale, longitudinal sleep studies. CLINICAL TRIAL REGISTRATION: NCT03725943. Oxford University Press 2020-05-20 /pmc/articles/PMC7751170/ /pubmed/32433768 http://dx.doi.org/10.1093/sleep/zsaa097 Text en © Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Sleep, Health and Disease Arnal, Pierrick J Thorey, Valentin Debellemaniere, Eden Ballard, Michael E Bou Hernandez, Albert Guillot, Antoine Jourde, Hugo Harris, Mason Guillard, Mathias Van Beers, Pascal Chennaoui, Mounir Sauvet, Fabien The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging |
title | The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging |
title_full | The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging |
title_fullStr | The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging |
title_full_unstemmed | The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging |
title_short | The Dreem Headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging |
title_sort | dreem headband compared to polysomnography for electroencephalographic signal acquisition and sleep staging |
topic | Sleep, Health and Disease |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751170/ https://www.ncbi.nlm.nih.gov/pubmed/32433768 http://dx.doi.org/10.1093/sleep/zsaa097 |
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