bioRxivAnimal Behavior & Cognition
Capturing sleep-wake cycles by using day-to-day smartphone touchscreen interactions
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 = 84 individuals, accumulating 1384 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 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 taps can be leveraged to update the behavioural signatures of sleep with these peculiarities of modern digital behaviour.
- organism: human
- assay: behavioral assay
- research focus: host-pathogen & immune response
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- approach: experimental assay
- approach: statistical model
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