Sensors Capabilities, Performance, and Use of Consumer Sleep Technology

Overview

Journal Sleep Med Clin

Publisher Elsevier

Specialty Psychiatry

Date 2020 Feb 2

PMID 32005346

Citations 31

Authors

Massimiliano de Zambotti

Nicola Cellini

Luca Menghini

Michela Sarlo

Fiona C Baker

Affiliations

Soon will be listed here.

Abstract

Sleep is crucial for the proper functioning of bodily systems and for cognitive and emotional processing. Evidence indicates that sleep is vital for health, well-being, mood, and performance. Consumer sleep technologies (CSTs), such as multisensory wearable devices, have brought attention to sleep and there is growing interest in using CSTs in research and clinical applications. This article reviews how CSTs can process information about sleep, physiology, and environment. The growing number of sensors in wearable devices and the meaning of the data collected are reviewed. CSTs have the potential to provide opportunities to measure sleep and sleep-related physiology on a large scale.

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References

Laukkanen R, Virtanen P . Heart rate monitors: state of the art. J Sports Sci. 2012; 16 Suppl:S3-7. DOI: 10.1080/026404198366920. View

Reilly J, Penpraze V, Hislop J, Davies G, Grant S, Paton J . Objective measurement of physical activity and sedentary behaviour: review with new data. Arch Dis Child. 2008; 93(7):614-9. DOI: 10.1136/adc.2007.133272. View

Dunn J, Runge R, Snyder M . Wearables and the medical revolution. Per Med. 2018; 15(5):429-448. DOI: 10.2217/pme-2018-0044. View

Hunter C, Figueiro M . Measuring Light at Night and Melatonin Levels in Shift Workers: A Review of the Literature. Biol Res Nurs. 2017; 19(4):365-374. PMC: 5862149. DOI: 10.1177/1099800417714069. View

Walker M . The role of sleep in cognition and emotion. Ann N Y Acad Sci. 2009; 1156:168-97. DOI: 10.1111/j.1749-6632.2009.04416.x. View

Laborde S, Mosley E, Thayer J . Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research - Recommendations for Experiment Planning, Data Analysis, and Data Reporting. Front Psychol. 2017; 8:213. PMC: 5316555. DOI: 10.3389/fpsyg.2017.00213. View

Le T, Cheng C, Sangasoongsong A, Wongdhamma W, Bukkapatnam S . Wireless Wearable Multisensory Suite and Real-Time Prediction of Obstructive Sleep Apnea Episodes. IEEE J Transl Eng Health Med. 2016; 1:2700109. PMC: 4819230. DOI: 10.1109/JTEHM.2013.2273354. View

Teo J, Davila S, Yang C, Hii A, Pua C, Yap J . Digital phenotyping by consumer wearables identifies sleep-associated markers of cardiovascular disease risk and biological aging. Commun Biol. 2019; 2:361. PMC: 6778117. DOI: 10.1038/s42003-019-0605-1. View

Bian J, Guo Y, Xie M, Parish A, Wardlaw I, Brown R . Exploring the Association Between Self-Reported Asthma Impact and Fitbit-Derived Sleep Quality and Physical Activity Measures in Adolescents. JMIR Mhealth Uhealth. 2017; 5(7):e105. PMC: 5548986. DOI: 10.2196/mhealth.7346. View

10.

Cook J, Eftekari S, Dallmann E, Sippy M, Plante D . Ability of the Fitbit Alta HR to quantify and classify sleep in patients with suspected central disorders of hypersomnolence: A comparison against polysomnography. J Sleep Res. 2018; 28(4):e12789. DOI: 10.1111/jsr.12789. View

11.

Spierer D, Rosen Z, Litman L, Fujii K . Validation of photoplethysmography as a method to detect heart rate during rest and exercise. J Med Eng Technol. 2015; 39(5):264-71. DOI: 10.3109/03091902.2015.1047536. View

12.

van Dooren M, de Vries J, Janssen J . Emotional sweating across the body: comparing 16 different skin conductance measurement locations. Physiol Behav. 2012; 106(2):298-304. DOI: 10.1016/j.physbeh.2012.01.020. View

13.

Folkard S, Lombardi D, Tucker P . Shiftwork: safety, sleepiness and sleep. Ind Health. 2005; 43(1):20-3. DOI: 10.2486/indhealth.43.20. View

14.

Maskevich S, Jumabhoy R, Dao P, Stout J, Drummond S . Pilot Validation of Ambulatory Activity Monitors for Sleep Measurement in Huntington's Disease Gene Carriers. J Huntingtons Dis. 2017; 6(3):249-253. DOI: 10.3233/JHD-170251. View

15.

Kang S, Kang J, Ko K, Park S, Mariani S, Weng J . Validity of a commercial wearable sleep tracker in adult insomnia disorder patients and good sleepers. J Psychosom Res. 2017; 97:38-44. DOI: 10.1016/j.jpsychores.2017.03.009. View

16.

KOUMANS A, TURSKY B, Solomon P . Electrodermal levels and fluctuations during normal sleep. Psychophysiology. 1968; 5(3):300-6. DOI: 10.1111/j.1469-8986.1968.tb02826.x. View

17.

Cook J, Prairie M, Plante D . Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: A comparison against polysomnography and wrist-worn actigraphy. J Affect Disord. 2017; 217:299-305. PMC: 5509938. DOI: 10.1016/j.jad.2017.04.030. View

18.

Onorati F, Regalia G, Caborni C, Migliorini M, Bender D, Poh M . Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors. Epilepsia. 2017; 58(11):1870-1879. DOI: 10.1111/epi.13899. View

19.

Cook J, Prairie M, Plante D . Ability of the Multisensory Jawbone UP3 to Quantify and Classify Sleep in Patients With Suspected Central Disorders of Hypersomnolence: A Comparison Against Polysomnography and Actigraphy. J Clin Sleep Med. 2018; 14(5):841-848. PMC: 5940436. DOI: 10.5664/jcsm.7120. View

20.

Luik A, Farias Machado P, Espie C . Delivering digital cognitive behavioral therapy for insomnia at scale: does using a wearable device to estimate sleep influence therapy?. NPJ Digit Med. 2019; 1:3. PMC: 6548338. DOI: 10.1038/s41746-017-0010-4. View