Validation of fitness tracker for sleep measures in women with asthma.

OBJECTIVE: Nighttime wakening with asthma symptoms is a key to assessment and therapy decisions, with no gold standard objective measure. The study aims were to (1) determine the feasibility, (2) explore equivalence, and (3) test concordance of a consumer-based accelerometer with standard actigraphy for measurement of sleep patterns in women with asthma as an adjunct to self-report. METHODS: Panel study design of women with poorly controlled asthma from a university-affiliated primary care clinic system was used. We assessed sensitivity and specificity, equivalence and concordance of sleep time, sleep efficiency, and wake counts between the consumer-based accelerometer Fitbit Charge™ and Actigraph wGT3X+. We linked data between devices for comparison both automatically by 24-hour period and manually by sleep segment. RESULTS: Analysis included 424 938 minutes, 738 nights, and 833 unique sleep segments from 47 women. The fitness tracker demonstrated 97% sensitivity and 40% specificity to identify sleep. Between device equivalence for total sleep time (15 and 42-minute threshold) was demonstrated by sleep segment. Concordance improved for wake counts and sleep efficiency when adjusting for a linear trend. CONCLUSIONS: There were important differences in total sleep time, efficiency, and wake count measures when comparing individual sleep segments versus 24-hour measures of sleep. Fitbit overestimates sleep efficiency and underestimates wake counts in this population compared to actigraphy. Low levels of systematic bias indicate the potential for raw measurements from the devices to achieve equivalence and concordance with additional processing, algorithm modification, and modeling. Fitness trackers offer an accessible and inexpensive method to quantify sleep patterns in the home environment as an adjunct to subjective reports, and require further informatics development.

Prediction model development of women's daily asthma control using fitness tracker sleep disruption.

BACKGROUND: Night-time wakening with asthma symptoms is an important indicator of disease control and severity, with no gold-standard objective measurement. OBJECTIVE: The study objective was to use fitness tracker sleep data to develop predictive models of daily disease control-related asthma-specific wakening and FEV1 in working-aged women with poorly controlled asthma. METHODS: A repeated measures panel design included data from 43 women with poorly controlled asthma. Two components of asthma control were the primary outcomes, measured daily as (1) self-reported asthma-specific wakening and (2) self-administered spirometry to measure FEV1. Data were analyzed using generalized linear mixed models. RESULTS: Our models demonstrated predictive value (AUC=0.77) for asthma-specific night-time wakening and good predictive value (AUC=0.83) for daily FEV1. CONCLUSIONS: Fitness tracker sleep efficiency and wake counts demonstrate clinical utility as predictive of asthma-specific night-time wakening and daily FEV1. Fitness tracker sleep data demonstrated predictive capability for daily asthma outcomes.

Validation of Capturing Sleep Diary Data via a Wrist-Worn Device.

Paper sleep diaries are the gold standard for assessment of sleep continuity variables in clinical practice as well as research. Unfortunately, paper diaries can be filled out weekly instead of daily, lost, illegible or destroyed; and are considered out of date according to the newer technology savvy generations. In this study, we assessed the reliability and validity of using a wrist-worn electronic sleep diary. Design. A prospective design was used to compare capturing 14 days of sleep continuity data via paper to a wrist-worn electronic device that also captured actigraphy data. Results. Thirty-five healthy community dwelling adults with mean (sd) age of 36 (15), 80% Caucasians, and 74% females were enrolled. All sleep continuity variables via electronic and paper diary capture methods were significantly correlated with moderate, positive relationships. Assessment of validity revealed that electronic data capture had a significant relationship with objective measure of sleep continuity variables as measured by actigraphy. Paper diary variables were not significantly associated with objective measures. Conclusions. The use of a wrist-worn device to capture daily sleep diary data is as accurate as and for some variables more accurate than using paper diaries.