Figure 1 | Scientific Reports

Figure 1

From: A standardized workflow for long-term longitudinal actigraphy data processing using one year of continuous actigraphy from the CAN-BIND Wellness Monitoring Study

Figure 1

Pre-processing Pipeline Summary. Raw actigraphy data were acquired at 30 Hz and pre-processed to minute epochs, where activity data, a timestamp and corresponding wear sensor data were extracted. These data were trimmed, and data missingness patterns were addressed. Non-wear scoring (using the van Hees, Choi and Troiano algorithms) and sleep–wake scoring (using the Cole-Kripke and Tudor-Locke algorithms) were completed. A novel non-wear scoring method was developed, combining data from the van Hees, Choi and Troiano algorithms, with the wear sensor data (the Majority algorithm). Next, sleep and non-wear data were combined at the interval and epoch levels. A sensitivity analysis was performed to assess optimal threshold for overlap of sleep with non-wear intervals, yielding a final aggregated actigraphy database at the epoch and interval levels.

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