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Sensors 2016, 16(5), 646; doi:10.3390/s16050646

Reliability of Sleep Measures from Four Personal Health Monitoring Devices Compared to Research-Based Actigraphy and Polysomnography

1
Neuroscience & Behavior Program, University of Massachusetts, Amherst, 135 Hicks Way, Amherst, MA 01003, USA
2
Department of Psychological & Brain Sciences, University of Massachusetts, Amherst, 135 Hicks Way, Amherst, MA 01003, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Steffen Leonhardt and Daniel Teichmann
Received: 16 February 2016 / Revised: 24 April 2016 / Accepted: 30 April 2016 / Published: 5 May 2016
(This article belongs to the Special Issue Wearable Biomedical Sensors)
View Full-Text   |   Download PDF [1326 KB, uploaded 5 May 2016]   |  

Abstract

Polysomnography (PSG) is the “gold standard” for monitoring sleep. Alternatives to PSG are of interest for clinical, research, and personal use. Wrist-worn actigraph devices have been utilized in research settings for measures of sleep for over two decades. Whether sleep measures from commercially available devices are similarly valid is unknown. We sought to determine the validity of five wearable devices: Basis Health Tracker, Misfit Shine, Fitbit Flex, Withings Pulse O2, and a research-based actigraph, Actiwatch Spectrum. We used Wilcoxon Signed Rank tests to assess differences between devices relative to PSG and correlational analysis to assess the strength of the relationship. Data loss was greatest for Fitbit and Misfit. For all devices, we found no difference and strong correlation of total sleep time with PSG. Sleep efficiency differed from PSG for Withings, Misfit, Fitbit, and Basis, while Actiwatch mean values did not differ from that of PSG. Only mean values of sleep efficiency (time asleep/time in bed) from Actiwatch correlated with PSG, yet this correlation was weak. Light sleep time differed from PSG (nREM1 + nREM2) for all devices. Measures of Deep sleep time did not differ from PSG (SWS + REM) for Basis. These results reveal the current strengths and limitations in sleep estimates produced by personal health monitoring devices and point to a need for future development. View Full-Text
Keywords: actigraphy; wearables; validation; polysomnography; measurement actigraphy; wearables; validation; polysomnography; measurement
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Mantua, J.; Gravel, N.; Spencer, R.M.C. Reliability of Sleep Measures from Four Personal Health Monitoring Devices Compared to Research-Based Actigraphy and Polysomnography. Sensors 2016, 16, 646.

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