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J Clin Sleep Med. 2020 Feb 11. doi: 10.5664/jcsm.8356. [Epub ahead of print]

Effect of Wearables on Sleep in Healthy Individuals: A Randomized Cross-Over Trial and Validation Study.

Author information

1
University of Arizona Health Sciences Center for Sleep and Circadian Sciences, University of Arizona, Tucson, Arizona.
2
Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, University of Arizona, Tucson.
3
Department of Pediatrics, University of Arizona, Tucson.
4
Asthma and Airway Diseases Research Center, University of Arizona, Tucson.
5
Breathe Chicago Center, Division of Pulmonary, Critical Care, Sleep, & Allergy, University of Illinois, Chicago, Illinois.

Abstract

OBJECTIVES:

To determine whether a wearable sleep-tracker improves perceived sleep quality in healthy subjects. To test whether wearables reliably measure sleep quantity and quality compared to polysomnography.

METHODS:

A single-center randomized cross-over trial of community-based participants without medical conditions or sleep disorders. Wearable device (WHOOP, Inc.) that provided feedback regarding sleep information to the participant for 1-week and maintaining sleep logs versus 1-week of maintaining sleep logs alone. Self-reported daily sleep behaviors were documented in sleep logs. Polysomnography was performed on one night when wearing the wearable. PROMIS Sleep disturbance sleep scale was measured at baseline, 7, and 14 days of study participation.

RESULTS:

In 32 participants (21 women; 23.8 ± 5 years), wearables improved nighttime sleep quality (PROMIS sleep disturbance; B= -1.69; 95% Confidence Interval -3.11, -0.27; P=0.021) 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=0.023) but total daily sleep remained unchanged (P=0.43). 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 (Intra-class 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 when compared to 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.

KEYWORDS:

sleep; sleep loss; sleep quality; sleep tracker; wearable

PMID:
32043961
DOI:
10.5664/jcsm.8356

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