apply_sadeh | R Documentation |
The Sadeh sleep scoring algorithm is primarily used for younger adolescents as the supporting research was performed on children and young adults.
apply_sadeh(agdb)
agdb |
A |
The Sadeh algorithm requires that the activity data is in 60s epochs and uses an 11-minute window that includes the five previous and five future epochs. This function implements the algorithm as described in the ActiGraph user manual.
The Sadeh algorithm uses the y-axis (axis 1) counts; epoch counts over 300 are set to 300. The sleep index (SI) is defined as
SI = 7.601 - (0.065 * AVG) - (1.08 * NATS) - (0.056 * SD) - (0.703 * LG)
where at epoch t
the arithmetic mean (average) of the activity counts in
an 11-epoch window centered at t
the number of epochs in this 11-epoch window which have counts >= 50 and < 100
the standard deviation of the counts in a 6-epoch
window that includes t
and the five preceding epochs
the natural (base e) logarithm of the activity at
epoch t
. To avoid taking the log of 0, we add 1 to the count.
The time series of activity counts is padded with zeros as necessary, at the beginning and at the end, to compute the three functions AVG, SD, NATS within a rolling window.
Finally, the sleep state is asleep (S) if the sleep index SI is greater than -4; otherwise the sleep state is awake (W).
A tibble
of activity data. A new column sleep
indicates whether
each 60s epoch is scored as asleep (S) or awake (W).
A Sadeh, KM Sharkey and MA Carskadon. Activity based sleep-wake identification: An empirical test of methodological issues. Sleep, 17(3):201–207, 1994.
ActiLife 6 User's Manual by the ActiGraph Software Department. 04/03/2012.
apply_cole_kripke()
, apply_cole_kripke()
, apply_tudor_locke()
library("dplyr") data("gtxplus1day") gtxplus1day %>% collapse_epochs(60) %>% apply_sadeh()
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