| Type: | Package |
| Title: | Generate ActiLife Counts |
| Version: | 0.2.1 |
| Description: | ActiLife software generates activity counts from data collected by Actigraph accelerometers https://s3.amazonaws.com/actigraphcorp.com/wp-content/uploads/2017/11/26205758/ActiGraph-White-Paper_What-is-a-Count_.pdf. Actigraph is one of the most common research-grade accelerometers. There is considerable research validating and developing algorithms for human activity using ActiLife counts. Unfortunately, ActiLife counts are proprietary and difficult to implement if researchers use different accelerometer brands. The code creates ActiLife counts from raw acceleration data for different accelerometer brands and it is developed based on the study done by Brond and others (2017) <doi:10.1249/MSS.0000000000001344>. |
| URL: | https://github.com/walkabillylab/activityCounts, https://github.com/jbrond/ActigraphCounts |
| BugReports: | https://github.com/walkabillylab/activityCounts/issues |
| Depends: | R (≥ 2.10) |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.2.3 |
| Suggests: | knitr, rmarkdown, ggplot2, testthat (≥ 3.0.0) |
| VignetteBuilder: | knitr |
| Imports: | seewave, signal, tibble, lubridate, magrittr |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2025-04-03 18:47:01 UTC; dlf545 |
| Author: | Ruben Brondeel [aut], Javad Rahimipour Anaraki [aut], Daniel Fuller [aut, cph, cre], SeyedJavad KhataeiPour [aut], Beap Lab [cph] |
| Maintainer: | Daniel Fuller <daniel.fuller@usask.ca> |
| Repository: | CRAN |
| Date/Publication: | 2025-04-07 16:10:05 UTC |
activityCounts: Generate ActiLife Counts
Description
ActiLife software generates activity counts from data collected by Actigraph accelerometers https://s3.amazonaws.com/actigraphcorp.com/wp-content/uploads/2017/11/26205758/ActiGraph-White-Paper_What-is-a-Count_.pdf. Actigraph is one of the most common research-grade accelerometers. There is considerable research validating and developing algorithms for human activity using ActiLife counts. Unfortunately, ActiLife counts are proprietary and difficult to implement if researchers use different accelerometer brands. The code creates ActiLife counts from raw acceleration data for different accelerometer brands and it is developed based on the study done by Brond and others (2017) doi:10.1249/MSS.0000000000001344.
Details
There are two datasets and a main function in this package
Author(s)
Ruben Brondeel, Javad Rahimipour Anaraki, SeyedJavad KhataeiPour, Daniel Fuller.
Maintainer
Daniel Fuller daniel.fuller@usask.ca
See Also
counts to see how to produce counts.
sampleXYZ
raw accelerometer data for testing counts() function.
sampleCounts
counts calculated by activityCounts and ActiLife
counts
Description
Calculates ActiLife counts based on raw accelerometer data
Usage
counts(
data,
hertz = -1,
x_axis = 2,
y_axis = 3,
z_axis = 4,
time_column = -1,
start_time = -1
)
Arguments
data |
Accelerometer data, Must have at least three columns. |
hertz |
Sampling frequency in Hz |
x_axis |
Indicates the column number which has the accel data for x direction, the default is 2 |
y_axis |
Indicates the column number which has the accel data for y direction, the default is 3 |
z_axis |
Indicates the column number which has the accel data for z direction, the default is 4 |
time_column |
Optional. Indicates the column number which has the date and time. The first row will be considered as the start time of the study. You can use the "start_time" argument to provide the start time explicitly. |
start_time |
Optional. Use this to define the start time of the experiment. You can use this argument if the data does not contain a time column. |
Value
Returns a data.table with four columns:
- Time
The start time of the measurement
- x
the number of counts for X axis
- y
the number of counts for Y axis
- z
the number of counts for Z axis
See Also
sampleXYZ
raw accelerometer data for testing counts() function.
sampleCounts
counts calculated by activityCounts and ActiLife
Examples
# for tha sampleXYZ dataset, sampling frequency is 100 Hz
counts(data = sampleXYZ, hertz = 100)
# when start time is given explicitly
study_start_time <- "2017-08-22 12:30:10"
counts(data = sampleXYZ, hertz = 100 , start_time = study_start_time)
# the data has a time column, which is the first column
counts(data = sampleXYZ, hertz = 100 , time_column = 1)
# explicitly specify the X, Y and Z axis columns.
counts(data = sampleXYZ, hertz = 100 , x_axis = 2,y_axis = 3, z_axis = 4)
pptrunc
Description
pptrunc
Usage
pptrunc(data, max_value)
Arguments
data |
The variable that will be truncated |
max_value |
The upper bound ( -max_value is the lower bound) |
Value
the highest(or the lowest) value of "data" and "max_value"
runsum
Description
runsum
Usage
runsum(data, len, threshold)
Arguments
data |
input data |
len |
the length |
threshold |
the threshold |
Value
returns a
The counts calculated by activityCounts and ActiLife based on included raw accelerometer data
Description
A simple data.table which its first row is measurement time. Then for each time step,
counts are calculated by activityCounts and the ActiLife software. The counts are calculated based on
included sampleXYZ dataset, which its sampling frequency is 100H.
Usage
sampleCounts
Format
A data.table with nine columns:
- Time
Date and time
- activityCounts_x_counts
counts calculated by
counts()function in X direction- activityCounts_y_counts
counts calculated by
counts()function in Y direction- activityCounts_z_counts
counts calculated by
counts()function in Z direction- ActiLife_x_counts
counts calculated by ActiLife software in X direction
- ActiLife_y_counts
counts calculated by ActiLife software in Y direction
- ActiLife_z_counts
counts calculated by ActiLife software in Z direction
See Also
counts to see how to produce counts.
sampleXYZ
raw accelerometer data for testing counts() function.
Raw accelerometer data for the activityCounts package
Description
A simple data.table that contains raw accelerometer data for testing the
counts function. Sampling frequency of this data.table is 100Hz, therefore pass
100 as the second argument when using the counts function.
Usage
sampleXYZ
Format
A data.table with four columns:
- Time
Timestamp
- accelerometer_X
accelerometer data in X direction
- accelerometer_Y
accelerometer data in Y direction
- accelerometer_Z
accelerometer data in Z direction
See Also
counts to see how to produce counts.
sampleCounts
counts calculated by activityCounts and ActiLife
trunc
Description
trunc
Usage
trunc(data, min_value)
Arguments
data |
The input variable which will be altered if less than the threshold |
min_value |
the threshold which the input below it will be set to zero |
Value
returns zero if the "data" is less than the "mean_value" otherwise returns the "data"