Sadeh Sleep/Wake Scoring

Classifies each epoch as sleep or wake from activity counts with the Sadeh algorithm (Sadeh et al. 1994), validated on adults and adolescents on one-minute epochs.

Usage

sleep.sadeh(
  counts,
  epoch_length = 60,
  wake_threshold = 0,
  clip = NULL,
  na_action = c("na", "wake", "zero")
)

Arguments

counts: Numeric vector of activity counts (vertical axis).
epoch_length: Epoch length in seconds (default 60). The algorithm was validated on 60-second epochs; other lengths raise a warning.
wake_threshold: Sleep-index cut: an epoch is sleep when $SI \ge$ wake_threshold (default 0, Sadeh 1994; ActiLife uses -4).
clip: Optional upper cap on counts before scoring (default NULL, no cap; ActiLife and pyActigraphy use 300). Affects AVG, SD, and LG.
na_action: How NA-count epochs appear in the output: "na" (default) emits NA, so non-wear gaps are not read as sleep; "wake" scores them wake; "zero" scores them from a zero count.

Value

Character vector of states, "S" (sleep) or "W" (wake), the same length as counts.

Details

The sleep index uses an eleven-epoch window (five before, the current epoch, and five after): $$SI = 7.601 - 0.065 \cdot AVG - 1.08 \cdot NATS - 0.056 \cdot SD - 0.703 \cdot LG$$ where $AVG$ is the window mean, $NATS$ the number of epochs with counts in [50, 100), $SD$ the standard deviation over the current and five preceding epochs, and $LG = \log(\mathrm{count} + 1)$. An epoch is scored sleep when $SI \ge 0$ (Sadeh et al. 1994). For ActiLife/ActiGraph parity, set wake_threshold = -4 and clip = 300.

References

Sadeh A, Sharkey KM, Carskadon MA (1994). “Activity-based sleep-wake identification: an empirical test of methodological issues.” Sleep, 17(3), 201–207. doi:10.1093/sleep/17.3.201 .

Examples

# \donttest{
agd <- agd.counts(read.agd(example_agd(1), verbose = FALSE))
state <- sleep.sadeh(agd$axis1)
table(state)
#> state
#>    S    W 
#> 6757 3162 
# }