Description Usage Arguments Details Value References See Also Examples
The Choi algorithm detects periods of non-wear in activity data from an ActiGraph device. Such intervals are likely to represent invalid data and therefore should be excluded from downstream analysis.
1 2 3 4 5 6 7 | apply_choi(
agdb,
min_period_len = 90,
min_window_len = 30,
spike_tolerance = 2,
use_magnitude = FALSE
)
|
agdb |
A |
min_period_len |
Minimum number of consecutive "zero" epochs to start a non-wear period. The default is 90. |
min_window_len |
The minimum number of consecutive "zero" epochs immediately preceding and following a spike of artifactual movement. The default is 30. |
spike_tolerance |
Also known as artifactual movement interval.
At most |
use_magnitude |
Logical. If true, the magnitude of the vector (axis1, axis2, axis3) is used to measure activity; otherwise the axis1 value is used. The default is FALSE. |
The Choi algorithm extends the Troiano algorithm by requiring that
short spikes of artifactual movement during a non-wear period are
preceded and followed by min_window_len
consecutive "zero"
epochs.
This implementation of the algorithm expects that the epochs are 60 second long.
A summary tibble
of the detected non-wear periods.
If the activity data is grouped, then non-wear periods are
detected separately for each group.
L Choi, Z Liu, CE Matthews and MS Buchowski. Validation of accelerometer wear and nonwear time classification algorithm. Medicine & Science in Sports & Exercise, 43(2):357–364, 2011.
ActiLife 6 User's Manual by the ActiGraph Software Department. 04/03/2012.
apply_troiano
, collapse_epochs
1 2 3 4 5 6 | library("dplyr")
data("gtxplus1day")
gtxplus1day %>%
collapse_epochs(60) %>%
apply_choi()
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.