State of the science and recommendations for using wearable technology in sleep and circadian research

M De Zambotti, C Goldstein, J Cook, L Menghini… - Sleep, 2024 - academic.oup.com
Wearable sleep-tracking technology is of growing use in the sleep and circadian fields,
including for applications across other disciplines, inclusive of a variety of disease states …

Wearable activity trackers: A survey on utility, privacy, and security

K Salehzadeh Niksirat, L Velykoivanenko… - ACM Computing …, 2024 - dl.acm.org
Over the past decade, wearable activity trackers (WATs) have become increasingly popular.
However, despite many research studies in different fields (eg psychology, health, and …

Quantifying the body and caring for the mind: self-tracking in multiple sclerosis

A Ayobi, P Marshall, AL Cox, Y Chen - … of the 2017 CHI conference on …, 2017 - dl.acm.org
Consumer health technologies have an enormous potential to transform the self-
management of chronic conditions. However, it is unclear how individuals use self-tracking …

Making sense of sleep sensors: How sleep sensing technologies support and undermine sleep health

R Ravichandran, SW Sien, SN Patel, JA Kientz… - Proceedings of the …, 2017 - dl.acm.org
Sleep is an important aspect of our health, but it is difficult for people to track manually
because it is an unconscious activity. The ability to sense sleep has aimed to lower the …

Promises and challenges in the use of consumer-grade devices for sleep monitoring

S Roomkham, D Lovell, J Cheung… - IEEE reviews in …, 2018 - ieeexplore.ieee.org
The market for smartphones, smartwatches, and wearable devices is booming. In recent
years, individuals and researchers have used these devices as additional tools to monitor …

[HTML][HTML] Accuracy of Fitbit wristbands in measuring sleep stage transitions and the effect of user-specific factors

Z Liang, MA Chapa-Martell - JMIR mHealth and uHealth, 2019 - mhealth.jmir.org
Background: It has become possible for the new generation of consumer wristbands to
classify sleep stages based on multisensory data. Several studies have validated the …

SleepExplorer: a visualization tool to make sense of correlations between personal sleep data and contextual factors

Z Liang, B Ploderer, W Liu, Y Nagata, J Bailey… - Personal and Ubiquitous …, 2016 - Springer
Getting enough quality sleep is a key part of a healthy lifestyle. Many people are tracking
their sleep through mobile and wearable technology, together with contextual information …

Data sensemaking in self-tracking: Towards a new generation of self-tracking tools

A Coşkun, A Karahanoğlu - International Journal of Human …, 2023 - Taylor & Francis
Abstract Human-Computer Interaction (HCI) researchers have been increasingly interested
in investigating self-trackers' experience with self-tracking tools (STT) to get meaningful …

Dozer: Towards understanding the design of closed-loop wearables for sleep

NA Semertzidis, A Li Pin Hiung… - Proceedings of the …, 2023 - dl.acm.org
Sleep plays a paramount role in maintaining healthy bodily functioning. Yet, poor sleep is an
increasingly prevalent global health concern. Most current sleep technology tracks sleep …

A multi-level classification approach for sleep stage prediction with processed data derived from consumer wearable activity trackers

Z Liang, MA Chapa-Martell - Frontiers in Digital Health, 2021 - frontiersin.org
Consumer wearable activity trackers, such as Fitbit are widely used in ubiquitous and
longitudinal sleep monitoring in free-living environments. However, these devices are …