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Choi (2011) Non-Wear Detection

Source: R/nonwear.R
detect.nonwear.choi.Rd

Classifies each epoch as wear or non-wear with the Choi et al. (2011) algorithm: a run of consecutive zero-count epochs of at least frame minutes is non-wear, tolerating a short nonzero spike only when it is flanked by a fully zero window of stream minutes both before and after. The returned mask can be passed as the wear_time argument to the rest-activity and sleep functions.

Usage

detect.nonwear.choi(
  counts,
  epoch_length = 60,
  frame = 90,
  spike_tolerance = 2,
  stream = 30
)

Arguments

counts

Numeric activity vector (vertical axis), minute epochs assumed.

epoch_length

Epoch length in seconds (default 60). Window lengths are given in minutes and scaled to epochs by this value.

frame

Minimum non-wear window in minutes (default 90).

spike_tolerance

Maximum tolerated nonzero spike in minutes (default 2).

stream

Flanking all-zero window required around a tolerated spike, in minutes (default 30).

Value

A logical vector, one per epoch: TRUE = wear, FALSE = non-wear. Never errors.

References

Choi L, Liu Z, Matthews CE, Buchowski MS (2011). “Validation of accelerometer wear and nonwear time classification algorithm.” Medicine & Science in Sports & Exercise, 43(2), 357–364. doi:10.1249/MSS.0b013e3181ed61a3 .

See also

detect.nonwear.troiano

Examples

ts <- seq(as.POSIXct("2024-01-01", tz = "UTC"), by = 60, length.out = 600)
counts <- c(rep(200, 200), rep(0, 200), rep(200, 200))   # 200-min non-wear gap
table(detect.nonwear.choi(counts))
#> 
#> FALSE  TRUE 
#>   200   400