Table 1.
Validation studies of wearable and mobile sleep tracking technologies, n=23
| Year | Author | Title | Location | Population | N of Study | Consumer Targeted Device(s) | Comparison |
|---|---|---|---|---|---|---|---|
| 2016 | Bellone et al.[27] | Comparative analysis of actigraphy performance in healthy young subjects | Argentina | Healthy adults | 22 | MicroMini Motionlogger Watch, Condor Act Trust, MisFit Flash, Fitbit Flex and Thermachron | None |
| 2014 | Bhagat et al.[14] | Clinical validation of a wrist actigraphy mobile health device for sleep efficiency analysis | USA | Sleep disorders | 33 | S-Band | PSG |
| 2015 | Bhat et al.[15] | Is There a Clinical Role For Smartphone Sleep Apps? Comparison of Sleep Cycle Detection by a Smartphone Application to Polysomnography | USA | Healthy adults | 20 | Sleep Time smartphone application | PSG |
| 2017 | Brooke et al.[30] | Concurrent Validity of Wearable Activity Trackers Under Free-Living Conditions | USA | Healthy adults | 95 | 8 monitors: Nike+ FuelBand SE, Garmin VivoFit, Misfit Shine, Fitbit Flex, Jawbone UP, Polar Loop, Fitbit Charge HR, and SenseWear Armband Mini | Sleep log |
| 2017 | Cook et al.[16] | Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: A comparison against polysomnography and wrist-worn actigraphy | USA | Psychiatric | 21 | Fitbit Flex | PSG |
| 2017 | Cuttone et al.[33] | Sensible sleep: A Bayesian model for learning sleep patterns from smart phone events | Denmark, Sweden | Sony mobile users | 126 for model development, 324 for testing | Mobile phone device (usage data) | Consumer-targeted armband sleep trackers |
| 2015 | De Zambotti et al.[17] | Evaluation of a consumer fitness-tracking device to assess sleep in adults | USA | Healthy adults and Sleep disorder | 28 | Jawbone Up | PSG |
| 2016 | Dickinson et al.[34] | A practical validation study of a commercial accelerometer using good and poor sleepers | USA | No criteria listed | 38 | Fitbit Charge HR | Fitbit |
| 2015 | Ferguson et al.[28] | The validity of consumer-level, activity monitors in healthy adults worn in free-living conditions: a cross-sectional study | Australia | Healthy adults | 21 | Fitbit One, Fitbit Zip, Jawbone UP, Misfit Shine, Nike Fuelband, Striiv Smart Pedometer, Withings Pulse, Bodymedia Sensewear Pro | Actigraphy |
| 2017 | Gruwez et al.[18] | Reliability of commercially available sleep and activity trackers with manual switch-to-sleep mode activation in free-living healthy individuals | Belgium | Healthy adults | 20 | Jawbone Up, Withings Pulse O2, Bodymedia Sensewear Pro | Home PSG |
| 2015 | Jiang et al.[19] | An effective way to improve actigraphic algorithm by using tri-axial accelerometer in sleep detection | China | Healthy adults | 21 | Zeo | Tri-axial accelerometer |
| 2010 | Kameyama et al.[29] | The development of a system for sleep care and its applications | Japan | Healthy adults | 45 | Sleep-telecare system (actigraphy and heart rate variability) | Actigraphy |
| 2017 | Kang et al.[20] | Validity of a commercial wearable sleep tracker in adult insomnia disorder patients and good sleepers | Korea | Healthy adults, sleep disorder | 50 | Fitbit Flex | Portable PSG |
| 2014 | Lane et al.[31] | BeWell: Sensing Sleep, Physical Activities and Social Interactions to Promote Wellbeing | China, USA, Italy | Healthy adults | 27 | Mobile phone application: BeWell | Sleep log |
| 2013 | Lawson et al.[21] | Validating a mobile phone application for the everyday, unobtrusive, objective measurement of sleep | UK | Healthy adults | 26 | Mobile phone sensors | PSG, Actigraphy |
| 2017 | Lee at al.[35] | Comparison of Wearable Activity Tracker with Actigraphy for Sleep Evaluation and Circadian Rest-Activity Rhythm Measurement in Healthy Young Adults | Korea | Healthy adults | 16 | Fitbit Charge HR | Fitbit |
| 2016 | Mantua et al.[22] | Reliability of sleep measures from four personal health monitoring devices compared to research based actigraphy and polysomnography | USA | Healthy adults | 40 | Basis Health Tracker, Misfit Shine, Fitbit Flex, Withings Pulse O2 | PSG |
| 2016 | Markwald et al.[23] | Performance of a Portable Sleep Monitoring Device in Individuals with High Versus Low Sleep Efficiency | USA | Healthy adults | 29 | Zeo | PSG, Actigraphy |
| 2014 | Min et al.[32] | Toss ‘N’ turn: Smartphone as sleep and sleep quality detector | Canada | Adults (healthy and psychiatric) | 27 | Mobile phone application Toss ‘N’ Turn | Sleep log |
| 2012 | Montgomery-Downs et al.[24] | Movement toward a novel activity monitoring device | USA | Healthy adults | 24 | Fitbit | PSG, Actigraphy |
| 2014 | Perez-Macias et al.[36] | Comparative assessment of sleep quality estimates using home monitoring technology | Finland | Healthy adults | 23 | Fitbit One, Beddit Pro | No gold standard comparison. Devices compared to each other. |
| 2016 | Rosenberger et al.[25] | Twenty-four Hours of Sleep, Sedentary Behavior, and Physical Activity with Nine Wearable Devices | USA | Healthy adults | 40 | Fitbit One, Jawbone Up, Nike Fuelband, GENEactiv, and LUMOback | Portable EEG (Z-machine) |
| 2016 | Singh et al.[26] | A method of REM– non-REM sleep distinction using EKG signal for unobtrusive personal monitoring | India | Healthy adults | 20 | Mobile phone + EKG signal analysis | PSG |