TY - JOUR
T1 - (Not so) Smart sleep tracking through the phone
T2 - Findings from a polysomnography study testing the reliability of four sleep applications
AU - Fino, Edita
AU - Plazzi, Giuseppe
AU - Filardi, Marco
AU - Marzocchi, Michele
AU - Pizza, Fabio
AU - Vandi, Stefano
AU - Mazzetti, Michela
N1 - Ricercatori distaccati presso IRCCS a seguito Convenzione esclusiva con Università di Bologna (Plazzi Giuseppe, Pizza Fabio, Vandi Stefano).
PY - 2019
Y1 - 2019
N2 - An increasing number of sleep applications are currently available and are being widely used for in-home sleep tracking. The present study assessed four smartphone applications (Sleep Cycle-Accelerometer, SCa; Sleep Cycle-Microphone, SCm; Sense, Se; Smart Alarm, SA) designed for sleep−wake detection through sound and movement sensors, by comparing their performance with polysomnography. Twenty-one healthy participants (six males, 15 females) used the four sleep applications running on iPhone (provided by the experimenter) simultaneously with portable polysomnography recording at home, while sleeping alone for two consecutive nights. Whereas all apps showed a significant correlation with polysomnography-time in bed, only SA offered significant correlations for sleep efficacy. Furthermore, SA seemed to be quite effective in reliable detection of total sleep time and also light sleep; however, it underestimated wake and partially overestimated deep sleep. None of the apps resulted capable of detecting and scoring rapid eye movement sleep. To sum up, SC (functioning through both accelerometer and microphone) and Se did not result sufficiently reliable in sleep−wake detection compared with polysomnography. SA, the only application offering the possibility of an epoch-by-epoch analysis, showed higher accuracy than the other apps in comparison with polysomnography, but it still shows some limitations, particularly regarding wake and deep sleep detection. Developing scoring algorithms specific for smartphone sleep detection and adding external sensors to record other physiological parameters may overcome the present limits of sleep tracking through smart phone apps.
AB - An increasing number of sleep applications are currently available and are being widely used for in-home sleep tracking. The present study assessed four smartphone applications (Sleep Cycle-Accelerometer, SCa; Sleep Cycle-Microphone, SCm; Sense, Se; Smart Alarm, SA) designed for sleep−wake detection through sound and movement sensors, by comparing their performance with polysomnography. Twenty-one healthy participants (six males, 15 females) used the four sleep applications running on iPhone (provided by the experimenter) simultaneously with portable polysomnography recording at home, while sleeping alone for two consecutive nights. Whereas all apps showed a significant correlation with polysomnography-time in bed, only SA offered significant correlations for sleep efficacy. Furthermore, SA seemed to be quite effective in reliable detection of total sleep time and also light sleep; however, it underestimated wake and partially overestimated deep sleep. None of the apps resulted capable of detecting and scoring rapid eye movement sleep. To sum up, SC (functioning through both accelerometer and microphone) and Se did not result sufficiently reliable in sleep−wake detection compared with polysomnography. SA, the only application offering the possibility of an epoch-by-epoch analysis, showed higher accuracy than the other apps in comparison with polysomnography, but it still shows some limitations, particularly regarding wake and deep sleep detection. Developing scoring algorithms specific for smartphone sleep detection and adding external sensors to record other physiological parameters may overcome the present limits of sleep tracking through smart phone apps.
KW - polysomnography
KW - sleep applications
KW - sleep tracking
KW - smartphone
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U2 - 10.1111/jsr.12935
DO - 10.1111/jsr.12935
M3 - Article
C2 - 31674096
AN - SCOPUS:85074776966
JO - Journal of Sleep Research
JF - Journal of Sleep Research
SN - 0962-1105
M1 - e12935
ER -