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

NPJ Digital Medicine
Jay N BorgerArko Ghosh

Abstract

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 (R2 = 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 ...Continue Reading

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Citations

Mar 29, 2020·NPJ Digital Medicine·Ignacio Perez-PozueloLuis Fernandez-Luque
Mar 9, 2021·IScience·Reto Huber, Arko Ghosh
Feb 18, 2021·NPJ Digital Medicine·Ignacio Perez-PozueloLuis Fernandez-Luque

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Software Mentioned

extractTaps
TapCounter
MALTAB
TapCounter App
Google Playstore
MATLAB

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