TY - JOUR
T1 - Effect of wearables on sleep in healthy individuals
T2 - A randomized crossover trial and validation study
AU - Berryhill, Sarah
AU - Morton, Christopher J.
AU - Dean, Adam
AU - Berryhill, Adam
AU - Provencio-Dean, Natalie
AU - Patel, Salma I.
AU - Estep, Lauren
AU - Combs, Daniel
AU - Mashaqi, Saif
AU - Gerald, Lynn B.
AU - Krishnan, Jerry A.
AU - Parthasarathy, Sairam
N1 - Publisher Copyright: Copyright © 2020 American Academy of Sleep Medicine. All rights reserved.
PY - 2020/5/15
Y1 - 2020/5/15
N2 - Study Objectives: The purpose of this study was to determine whether a wearable sleep-tracker improves perceived sleep quality in healthy participants and to test whether wearables reliably measure sleep quantity and quality compared with polysomnography. Methods: This study included a single-center randomized crossover trial of community-based participants without medical conditions or sleep disorders. A wearable device (WHOOP, Inc.) was used that provided feedback regarding sleep information to the participant for 1 week and maintained sleep logs versus 1 week of maintained sleep logs alone. Self-reported daily sleep behaviors were documented in sleep logs. Polysomnography was performed on 1 night when wearing the wearable. The Patient-Reported Outcomes Measurement Information System sleep disturbance sleep scale was measured at baseline, day 7 and day 14 of study participation. Results: In 32 participants (21 women; 23.8 ± 5 years), wearables improved nighttime sleep quality (Patient-Reported Outcomes Measurement Information System sleep disturbance: B = −1.69; 95% confidence interval, −3.11 to −0.27; P =.021) after adjusting for age, sex, baseline, and order effect. There was a small increase in self-reported daytime naps when wearing the device (B = 3.2; SE, 1.4; P =.023), but total daily sleep remained unchanged (P =.43). The wearable had low bias (13.8 minutes) and precision (17.8 minutes) errors for measuring sleep duration and measured dream sleep and slow wave sleep accurately (intraclass coefficient, 0.74 ± 0.28 and 0.85 ± 0.15, respectively). Bias and precision error for heart rate (bias, −0.17%; precision, 1.5%) and respiratory rate (bias, 1.8%; precision, 6.7%) were very low compared with that measured by electrocardiogram and inductance plethysmography during polysomnography. Conclusions: In healthy people, wearables can improve sleep quality and accurately measure sleep and cardiorespiratory variables.
AB - Study Objectives: The purpose of this study was to determine whether a wearable sleep-tracker improves perceived sleep quality in healthy participants and to test whether wearables reliably measure sleep quantity and quality compared with polysomnography. Methods: This study included a single-center randomized crossover trial of community-based participants without medical conditions or sleep disorders. A wearable device (WHOOP, Inc.) was used that provided feedback regarding sleep information to the participant for 1 week and maintained sleep logs versus 1 week of maintained sleep logs alone. Self-reported daily sleep behaviors were documented in sleep logs. Polysomnography was performed on 1 night when wearing the wearable. The Patient-Reported Outcomes Measurement Information System sleep disturbance sleep scale was measured at baseline, day 7 and day 14 of study participation. Results: In 32 participants (21 women; 23.8 ± 5 years), wearables improved nighttime sleep quality (Patient-Reported Outcomes Measurement Information System sleep disturbance: B = −1.69; 95% confidence interval, −3.11 to −0.27; P =.021) after adjusting for age, sex, baseline, and order effect. There was a small increase in self-reported daytime naps when wearing the device (B = 3.2; SE, 1.4; P =.023), but total daily sleep remained unchanged (P =.43). The wearable had low bias (13.8 minutes) and precision (17.8 minutes) errors for measuring sleep duration and measured dream sleep and slow wave sleep accurately (intraclass coefficient, 0.74 ± 0.28 and 0.85 ± 0.15, respectively). Bias and precision error for heart rate (bias, −0.17%; precision, 1.5%) and respiratory rate (bias, 1.8%; precision, 6.7%) were very low compared with that measured by electrocardiogram and inductance plethysmography during polysomnography. Conclusions: In healthy people, wearables can improve sleep quality and accurately measure sleep and cardiorespiratory variables.
KW - Sleep
KW - Sleep loss
KW - Sleep quality
KW - Sleep tracker
KW - Wearable
UR - http://www.scopus.com/inward/record.url?scp=85084915733&partnerID=8YFLogxK
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U2 - 10.5664/jcsm.8356
DO - 10.5664/jcsm.8356
M3 - Article
C2 - 32043961
SN - 1550-9389
VL - 16
SP - 775
EP - 783
JO - Journal of Clinical Sleep Medicine
JF - Journal of Clinical Sleep Medicine
IS - 5
ER -