| dateSummary {pawacc} | R Documentation |
Date summary for accelerometer files
Description
This function provides a date summary for Actigraph GT1M accelerometer files.
Usage
dateSummary(object, wear, timestamp, minval = 0,
rescale.epoch = 60, keep.error = FALSE)
Arguments
object |
an object of class |
wear |
a vector that classifies wear and non-wear time. See |
timestamp |
a timestamp vector for accelerometer values that can be provided by |
minval |
threshold defining the minimum number of minutes to identify first and last days. See details. |
rescale.epoch |
epoch expressed in the same unit as acceleromenter's epoch to determine minutes of wear time (default is 60 and assumed to be in seconds). |
keep.error |
logical flag. If |
Details
Based on total wear time (in minutes) for each day, the theshold minval is applied to identify the first and last days. For example, if accelerometers are sent by post to collect survey data, the first and last days in which the accelerometer was worn might not be known. Days before the first and those after the last day (truncated days) are discarded by collapse.accfile.
Value
A data frame containing the following variables
fileid |
file identifier |
days |
dates by calendar day |
freq |
frequency of accelerometer observations in each day |
hour_day |
total hours of accelerometer observations in each day |
start_day |
starting time of accelerometer observations |
end |
end time of accelerometer observations |
valid_mins |
wear time (minutes) |
IsStartDate |
dummy variable to define starting date (1 = yes) |
IsEndDate |
dummy variable to define end date (1 = yes) |
IsTruncated |
dummy variable to define truncated date (1 = yes) |
Author(s)
Marco Geraci
References
Geraci M, Rich C, Sera F, Cortina-Borja M, Griffiths LJ, and Dezateux C (2012). Technical report on accelerometry data processing in the Millennium Cohort Study. London, UK: University College London. Available at https://discovery.ucl.ac.uk/1361699
See Also
Examples
data(gt1m_sample)
mw <- markwear.accfile(gt1m_sample, 20)
tsf <- tsFormat(gt1m_sample)
dateSummary(gt1m_sample, mw, tsf)
## Not run:
fileid days freq hour_day start_day end_day valid_mins IsStartDate
1 test 2011-12-08 3840 16.000 08 23 571.25 1
2 test 2011-12-09 5760 24.000 00 23 557.00 0
3 test 2011-12-10 5760 24.000 00 23 676.50 0
4 test 2011-12-11 5760 24.000 00 23 493.50 0
5 test 2011-12-12 5760 24.000 00 23 638.25 0
6 test 2011-12-13 5760 24.000 00 23 680.50 0
7 test 2011-12-14 5760 24.000 00 23 717.00 0
8 test 2011-12-15 5760 24.000 00 23 0.50 0
9 test 2011-12-16 750 3.125 00 03 0.00 0
IsEndDate IsTruncated
1 0 0
2 0 0
3 0 0
4 0 0
5 0 0
6 0 0
7 0 0
8 0 0
9 1 0
## End(Not run)
# at least 600 minutes per day to determine first and last day
dateSummary(gt1m_sample, mw, tsf, minval = 600)
## Not run:
fileid days freq hour_day start_day end_day valid_mins IsStartDate
1 test 2011-12-08 3840 16.000 08 23 571.25 0
2 test 2011-12-09 5760 24.000 00 23 557.00 0
3 test 2011-12-10 5760 24.000 00 23 676.50 1
4 test 2011-12-11 5760 24.000 00 23 493.50 0
5 test 2011-12-12 5760 24.000 00 23 638.25 0
6 test 2011-12-13 5760 24.000 00 23 680.50 0
7 test 2011-12-14 5760 24.000 00 23 717.00 0
8 test 2011-12-15 5760 24.000 00 23 0.50 0
9 test 2011-12-16 750 3.125 00 03 0.00 0
IsEndDate IsTruncated
1 0 1
2 0 1
3 0 0
4 0 0
5 0 0
6 0 0
7 1 0
8 0 1
9 0 1
## End(Not run)