Next Article in Journal
High Precision Timing with Parabolic Equation Fitting in Narrowband Systems
Next Article in Special Issue
An Unsupervised Framework for Online Spatiotemporal Detection of Activities of Daily Living by Hierarchical Activity Models
Previous Article in Journal
Space State Representation Corrections as an Aid in Pseudolite Positioning
Previous Article in Special Issue
A Survey of Vision-Based Human Action Evaluation Methods
Open AccessArticle

About the Accuracy and Problems of Consumer Devices in the Assessment of Sleep

1
Laboratory for Sleep, Cognition and Consciousness Research, Department of Psychology, University of Salzburg, Hellbrunner Strasse 34, 5020 Salzburg, Austria
2
School of Psychology, University of Surrey, Stag Hill, Guildford GU2 7XH, UK
3
Center for Cognitive Neuroscience Salzburg (CCNS), Hellbrunner Strasse 34, 5020 Salzburg, Austria
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(19), 4160; https://doi.org/10.3390/s19194160
Received: 23 July 2019 / Revised: 18 September 2019 / Accepted: 23 September 2019 / Published: 25 September 2019
(This article belongs to the Special Issue From Sensors to Ambient Intelligence for Health and Social Care)
Commercial sleep devices and mobile-phone applications for scoring sleep are gaining ground. In order to provide reliable information about the quantity and/or quality of sleep, their performance needs to be assessed against the current gold standard, i.e., polysomnography (PSG; measuring brain, eye, and muscle activity). Here, we assessed some commercially available sleep trackers, namely an activity tracker; Mi band (Xiaomi, Beijing, China), a scientific actigraph: Motionwatch 8 (CamNTech, Cambridge, UK), and a much-used mobile phone application: Sleep Cycle (Northcube, Gothenburg, Sweden). We recorded 27 nights in healthy sleepers using PSG and these devices and compared the results. Surprisingly, all devices had poor agreement with the PSG gold standard. Sleep parameter comparisons revealed that, specifically, the Mi band and the Sleep Cycle application had difficulties in detecting wake periods which negatively affected their total sleep time and sleep-efficiency estimations. However, all 3 devices were good in detecting the most basic parameter, the actual time in bed. In summary, our results suggest that, to date, the available sleep trackers do not provide meaningful sleep analysis but may be interesting for simply tracking time in bed. A much closer interaction with the scientific field seems necessary if reliable information shall be derived from such devices in the future. View Full-Text
Keywords: wrist-worn devices; sleep trackers; activity trackers; sleep classification; polysomnography wrist-worn devices; sleep trackers; activity trackers; sleep classification; polysomnography
Show Figures

Figure 1

MDPI and ACS Style

Ameen, M.S.; Cheung, L.M.; Hauser, T.; Hahn, M.A.; Schabus, M. About the Accuracy and Problems of Consumer Devices in the Assessment of Sleep. Sensors 2019, 19, 4160.

AMA Style

Ameen MS, Cheung LM, Hauser T, Hahn MA, Schabus M. About the Accuracy and Problems of Consumer Devices in the Assessment of Sleep. Sensors. 2019; 19(19):4160.

Chicago/Turabian Style

Ameen, Mohamed S.; Cheung, Lok M.; Hauser, Theresa; Hahn, Michael A.; Schabus, Manuel. 2019. "About the Accuracy and Problems of Consumer Devices in the Assessment of Sleep" Sensors 19, no. 19: 4160.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop