STUDY OBJECTIVES: The aim of this study was to examine the feasibility of sleep estimation using a device designed and marketed to measure core physical activity. METHODS: Thirty adolescent participants in an epidemiological research study wore 3 actigraphy devices on the wrist over a single night concurrent with polysomnography (PSG). Devices used include Actical actigraph, designed and marketed for placement around the trunk to measure physical activity, in addition to 2 standard actigraphy devices used to assess sleep-wake states: Sleepwatch actigraph and Actiwatch actigraph. Sleep-wake behaviors, including total sleep time (TST) and sleep efficiency (SE), were estimated from each wrist-device and PSG. Agreements between each device were calculated using Pearson product movement correlation and Bland-Altman plots. RESULTS: Statistical analyses of TST revealed strong correlations between each wrist device and PSG (r = 0.822, 0.836, and 0.722 for Sleepwatch, Actiwatch, and Actical, respectively). TST measured using the Actical correlated strongly with Sleepwatch (r = 0.796), and even stronger still with Actiwatch (r = 0.955). In analyses of SE, Actical correlated strongly with Actiwatch (r = 0.820; p < 0.0001), but not with Sleepwatch (0.405; p = 0.0266). SE determined by PSG correlated somewhat strongly with SE estimated from the Sleepwatch and Actiwatch (r = 0.619 and 0.651, respectively), but only weakly with SE estimated from the Actical (r = 0.348; p = 0.0598). CONCLUSIONS: The results from this study suggest that a device designed for assessment of physical activity and truncal placement can be used to measure sleep duration as reliably as devices designed for wrist use and sleep wake inference.
STUDY OBJECTIVES: The aim of this study was to examine the feasibility of sleep estimation using a device designed and marketed to measure core physical activity. METHODS: Thirty adolescent participants in an epidemiological research study wore 3 actigraphy devices on the wrist over a single night concurrent with polysomnography (PSG). Devices used include Actical actigraph, designed and marketed for placement around the trunk to measure physical activity, in addition to 2 standard actigraphy devices used to assess sleep-wake states: Sleepwatch actigraph and Actiwatch actigraph. Sleep-wake behaviors, including total sleep time (TST) and sleep efficiency (SE), were estimated from each wrist-device and PSG. Agreements between each device were calculated using Pearson product movement correlation and Bland-Altman plots. RESULTS: Statistical analyses of TST revealed strong correlations between each wrist device and PSG (r = 0.822, 0.836, and 0.722 for Sleepwatch, Actiwatch, and Actical, respectively). TST measured using the Actical correlated strongly with Sleepwatch (r = 0.796), and even stronger still with Actiwatch (r = 0.955). In analyses of SE, Actical correlated strongly with Actiwatch (r = 0.820; p < 0.0001), but not with Sleepwatch (0.405; p = 0.0266). SE determined by PSG correlated somewhat strongly with SE estimated from the Sleepwatch and Actiwatch (r = 0.619 and 0.651, respectively), but only weakly with SE estimated from the Actical (r = 0.348; p = 0.0598). CONCLUSIONS: The results from this study suggest that a device designed for assessment of physical activity and truncal placement can be used to measure sleep duration as reliably as devices designed for wrist use and sleep wake inference.
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