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Original Articles

Identifying waking time in 24-h accelerometry data in adults using an automated algorithm

, , , , , , , , , & show all
Pages 1867-1873 | Accepted 05 Jan 2016, Published online: 02 Feb 2016

Figures & data

Table 1. Cut-off points for determining wake and bed times in the proposed algorithm.

Table 2. Descriptive characteristics of the study sample.

Table 3. Absolute differences in rise and bed times derived from algorithm-determined, self-report and fixed-time window methods.

Table 4. Comparison of waking time, sedentary time and percentage sedentary time determined by algorithm-determined, self-report and fixed-time window methods.

Figure 1. Bland–-Altman plot of the mean of and differences between waking hours based on self-reported and algorithm-calculated waking time. Dotted lines indicate the limits of agreement.

Figure 1. Bland–-Altman plot of the mean of and differences between waking hours based on self-reported and algorithm-calculated waking time. Dotted lines indicate the limits of agreement.

Figure 2. Illustration of misclassifying waking and sleeping time by the fixed-time window method compared to the algorithm-determined method. Grey bars = waking time.

Figure 2. Illustration of misclassifying waking and sleeping time by the fixed-time window method compared to the algorithm-determined method. Grey bars = waking time.

Figure 3. Bland–-Altman plot of the mean of and differences between sedentary time as determined by the algorithm an fixed-time window methods. Dotted lines indicate the limits of agreement.

Figure 3. Bland–-Altman plot of the mean of and differences between sedentary time as determined by the algorithm an fixed-time window methods. Dotted lines indicate the limits of agreement.