Identify Bouts:
Usage
identify_bouts(
accelerometry_counts,
maximum_number_consec_inactive_epochs_in_bout,
active_counts_per_epoch_min,
minimum_bout_length
)Arguments
- accelerometry_counts
A data frame containing accelerometry counts and times
- maximum_number_consec_inactive_epochs_in_bout
Maximum number of consecutive inactive epochs in a bout without ending the bout
- active_counts_per_epoch_min
Minimum accelerometer counts for an epoch to be considered active (vs. inactive)
- minimum_bout_length
Minimum number of epochs for a period of activity to be considered as a potential bout
Value
A data frame with the same columns as the input data frame accelerometry_counts,
but with a new column named bout that indicates whether each epoch is part of a bout
(in which case it gets a bout number assigned) or not (0)
Details
This function partitions the accelerometry data into bouts of activity and non-bouts by
first identifying all epochs that are definitely not part of bouts. Then, it uses run length encoding to
partition the data into potential bouts and non-bouts, and labels each potential bout as a bout or non-bout
based on whether it meets the criteria for bout length and the number of consecutive inactive epochs allowed.
Finally, the function adds a new column to the input data frame accelerometry_counts named bout
that indicates whether each epoch is part of a bout (1) or not (0).