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Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions

Body movements drop with sleep, and this behavioural signature is widely exploited to infer sleep duration. However, a reduction in body movements may also occur in periods of intense cognitive activity, and the ubiquitous use of smartphones may capture these wakeful periods otherwise hidden in the...

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Autores principales: Borger, Jay N., Huber, Reto, Ghosh, Arko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662846/
https://www.ncbi.nlm.nih.gov/pubmed/31372507
http://dx.doi.org/10.1038/s41746-019-0147-4
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author Borger, Jay N.
Huber, Reto
Ghosh, Arko
author_facet Borger, Jay N.
Huber, Reto
Ghosh, Arko
author_sort Borger, Jay N.
collection PubMed
description Body movements drop with sleep, and this behavioural signature is widely exploited to infer sleep duration. However, a reduction in body movements may also occur in periods of intense cognitive activity, and the ubiquitous use of smartphones may capture these wakeful periods otherwise hidden in the standard measures of sleep. Here, we continuously captured the gross body movements using standard wrist-worn accelerometers to quantify sleep (actigraphy) and logged the timing of the day-to-day touchscreen events (‘tappigraphy’). Using these measures, we addressed how the gross body movements overlap with the cognitively engaging digital behaviour (from n = 79 individuals, accumulating ~1400 nights). We find that smartphone use was distributed across a broad spectrum of physical activity levels, but consistently peaked at rest. We estimated the putative sleep onset and wake-up times from the actigraphy data to find that these times were well correlated to the estimates from tappigraphy (R(2) = 0.9 for sleep-onset time and wake-up time). However, actigraphy overestimated sleep as virtually all of the users used their phones during the putative sleep period. Interestingly, the probability of touches remained greater than zero for ~2 h after the putative sleep onset, and ~2 h before the putative wake-up time. Our findings suggest that touchscreen interactions are widely integrated into modern sleeping habits—surrounding both sleep onset and waking-up periods—yielding a new approach to measuring sleep. Smartphone interactions can be leveraged to update the behavioural signatures of sleep with these peculiarities of modern digital behaviour.
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spelling pubmed-66628462019-08-01 Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions Borger, Jay N. Huber, Reto Ghosh, Arko NPJ Digit Med Article Body movements drop with sleep, and this behavioural signature is widely exploited to infer sleep duration. However, a reduction in body movements may also occur in periods of intense cognitive activity, and the ubiquitous use of smartphones may capture these wakeful periods otherwise hidden in the standard measures of sleep. Here, we continuously captured the gross body movements using standard wrist-worn accelerometers to quantify sleep (actigraphy) and logged the timing of the day-to-day touchscreen events (‘tappigraphy’). Using these measures, we addressed how the gross body movements overlap with the cognitively engaging digital behaviour (from n = 79 individuals, accumulating ~1400 nights). We find that smartphone use was distributed across a broad spectrum of physical activity levels, but consistently peaked at rest. We estimated the putative sleep onset and wake-up times from the actigraphy data to find that these times were well correlated to the estimates from tappigraphy (R(2) = 0.9 for sleep-onset time and wake-up time). However, actigraphy overestimated sleep as virtually all of the users used their phones during the putative sleep period. Interestingly, the probability of touches remained greater than zero for ~2 h after the putative sleep onset, and ~2 h before the putative wake-up time. Our findings suggest that touchscreen interactions are widely integrated into modern sleeping habits—surrounding both sleep onset and waking-up periods—yielding a new approach to measuring sleep. Smartphone interactions can be leveraged to update the behavioural signatures of sleep with these peculiarities of modern digital behaviour. Nature Publishing Group UK 2019-07-29 /pmc/articles/PMC6662846/ /pubmed/31372507 http://dx.doi.org/10.1038/s41746-019-0147-4 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Borger, Jay N.
Huber, Reto
Ghosh, Arko
Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
title Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
title_full Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
title_fullStr Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
title_full_unstemmed Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
title_short Capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
title_sort capturing sleep–wake cycles by using day-to-day smartphone touchscreen interactions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6662846/
https://www.ncbi.nlm.nih.gov/pubmed/31372507
http://dx.doi.org/10.1038/s41746-019-0147-4
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