Abstract
Following the previous post on deriving sleep/wake patterns from the acceleration data of Actiwatch, this document gives an example of deriving sleep parameters according to the instruction manual of Actiwatch [1].
1. Deriving Sleep Parameters from Sleep/Wake Patterns
Figure 1 shows the sleep/wake patterns derived from Actiwatch 2, as introduced in the previous post. Some important sleep events are labeled, such as bedtime, get-up time, sleep onset, sleep offset, and wake episodes. Actiwatch 2 has an event marker button for users to record when they went to bed (Bed Time) and got out of bed (Get Up Time). Sleep onset is the time point of the start of the first 10 consecutive minutes of sleep after going to bed, while sleep offset is the time point of the last minute of the last 10 consecutive minutes of sleep before getting out of bed [1-2]. Table 1 then illustrates the resulting 7 sleep parameters, which are usually adopted in a sleep report.
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2. References
[1] Respironics, “Instruction manual of Actiwatch Communication and Sleep Analysis Software. Instruction manual.
[2] D. Fekedulegn, M. E. Andrew, M. Shi, J. M. Violanti, S. Knox, and K. E. Innes, "Actigraphy-based assessment of sleep parameters," Annals of Work Exposures and Health, vol. 64, no. 4, pp. 350-367, 2020.
Dr. Ahn is an internal medicine physician with a background in physics/engineering and physiological signal analyses. He is the Chief Medical Officer at Labfront and an Assistant Professor in Medicine & Radiology at Harvard Medical School. Dr. Ahn is passionate about democratizing health sciences and exploring health from an anti-disciplinary perspective.
Han-Ping is the senior research lead (and chief plant caretaker) at Labfront, specializing in physiological data analysis. An alumnus of the BIDMC/Harvard's Center for Dynamical Biomarkers, Han-Ping uses his PhD in electrophysics to help Labfront customers convert raw physiological data into health insights. He does his best Python coding while powered by arm massages from his spiky-tongued cat, Pi.
Francis is a research Lead at Labfront, responsible for data validation and analysis. He is interested in applying physics or math to medical research.
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