Compute WASO and nightly sleep statistics

Scores each epoch within detected sleep periods as wake or sleep using score_epochs_cole_kripke(), then computes per-night statistics.

Usage

compute_waso(x, wake_thresh = 60L, search_gap = FALSE)

Arguments

x

A tibble as returned by detect_naps_crespo() (or detect_sleep_crespo() if nap detection is skipped), containing columns datetime, ZCMn, and state.

wake_thresh

integer(1). Minimum duration in epochs of a wake bout required to delimit a new sleep period boundary. Default is 60.

search_gap

logical(1). If TRUE, allows a gap search between consecutive sleep periods when identifying night boundaries. Default is FALSE.

Value

A list with two elements:

nights

A tibble with one row per detected night/nap and columns night, is_nap, bed_time, get_up_time, tbt, tst, waso, sol, soi, nw, eff.

data

The input tibble x with state and sleep updated with epoch-level Cole-Kripke wake/sleep scores.

Details

The following metrics are computed for each detected night / nap:

Metric	Definition
tbt	Total Bed Time — epochs from bed time to get-up time
tst	Total Sleep Time — tbt − waso − sol − soi
waso	Wake After Sleep Onset — wake epochs between sleep onset and final wake
sol	Sleep Onset Latency — epochs from bed time to first sleep epoch
soi	Sleep Offset Inertia — trailing wake epochs at end of sleep period
nw	Number of awakenings — count of wake-onset transitions
eff	Sleep efficiency — tst / tbt

References

Cole, R. J., Kripke, D. F., Gruen, W., Mullaney, D. J., & Gillin, J. C. (1992). Automatic sleep/wake identification from wrist activity. Sleep, 15(5), 461–469. doi:10.1093/sleep/15.5.461

Examples

if (FALSE) { # \dontrun{
rec    <- read_acttrust("recordings/P001.txt")
prep   <- prepare_actigraphy(rec)
prep   <- detect_offwrist_bimodal(prep)
prep   <- detect_sleep_crespo(prep)
prep   <- detect_naps_crespo(prep)
result <- compute_waso(prep)
result$nights
} # }