R/import_data.R
import_actigraph_csv.Rdimport_actigraph_csv imports the raw multi-channel accelerometer data
stored in Actigraph raw csv format. It supports files from the following
devices: GT3X, GT3X+, GT3X+BT, GT9X, and GT9X-IMU.
import_actigraph_csv(
filepath,
in_voltage = FALSE,
has_ts = TRUE,
header = TRUE
)string. The filepath of the input data. The first column of the input data should always include timestamps.
set as TRUE only when the input Actigraph csv file is in analog quantized format and need to be converted into g value
boolean. If TRUE, the input csv file will have a timestamp column.
boolean. If TRUE, the input csv file will have column names in the first row.
dataframe. The imported multi-channel accelerometer signal, with the first column being the timestamps in POSXlct format, and the rest columns being accelerometer values in \(g\) unit.
For old device (GT3X) that stores accelerometer values as digital voltage. The function will convert the values to \(g\) unit using the following equation.
$$x_g = \frac{x_{voltage}r}{(2 ^ r) - \frac{v}{2}}$$
Where \(v\) is the max voltage corresponding to the max accelerometer value that can be found in the meta section in the csv file; \(r\) is the resolution level which is the number of bits used to store the voltage values. \(r\) can also be found in the meta section in the csv file.
This function is a File IO function that is used to import data from Actigraph devices during algorithm validation.
Other File I/O functions:
export_to_actilife(),
import_actigraph_count_csv(),
import_actigraph_csv_chunked(),
import_actigraph_meta(),
import_activpal3_csv(),
import_enmo_csv(),
import_mhealth_csv_chunked(),
import_mhealth_csv()
default_ops = options()
options(digits.secs=3)
# Use the sample actigraph csv file provided by the package
filepath = system.file('extdata', 'actigraph_timestamped.csv', package='MIMSunit')
# Check file format
readLines(filepath)[1:15]
#> [1] "------------ Data File Created By ActiGraph GT3X+ ActiLife v6.13.3 Firmware v2.5.0 date format M/d/yyyy at 40 Hz Filter Normal -----------"
#> [2] "Serial Number: CLE2B20130009"
#> [3] "Start Time 11:27:00"
#> [4] "Start Date 6/14/2018"
#> [5] "Epoch Period (hh:mm:ss) 00:00:00"
#> [6] "Download Time 15:16:42"
#> [7] "Download Date 6/14/2018"
#> [8] "Current Memory Address: 0"
#> [9] "Current Battery Voltage: 4.21 Mode = 12"
#> [10] "--------------------------------------------------"
#> [11] "Timestamp,Accelerometer X,Accelerometer Y,Accelerometer Z"
#> [12] "6/14/2018 12:08:39.725,-0.009,-0.053,-0.988"
#> [13] "6/14/2018 12:08:39.750,-0.009,-0.053,-0.982"
#> [14] "6/14/2018 12:08:39.775,-0.009,-0.053,-0.988"
#> [15] "6/14/2018 12:08:39.800,-0.009,-0.053,-0.982"
# Load the file with timestamp column
df = import_actigraph_csv(filepath)
# Check loaded file
head(df)
#> HEADER_TIME_STAMP X Y Z
#> 1 2018-06-14 12:08:39 -0.009 -0.053 -0.988
#> 2 2018-06-14 12:08:39 -0.009 -0.053 -0.982
#> 3 2018-06-14 12:08:39 -0.009 -0.053 -0.988
#> 4 2018-06-14 12:08:39 -0.009 -0.053 -0.982
#> 5 2018-06-14 12:08:39 -0.009 -0.053 -0.982
#> 6 2018-06-14 12:08:39 -0.009 -0.056 -0.988
# Check more
summary(df)
#> HEADER_TIME_STAMP X Y
#> Min. :2018-06-14 12:08:39.73 Min. :-0.370000 Min. :-0.41900
#> 1st Qu.:2018-06-14 12:09:10.90 1st Qu.:-0.202000 1st Qu.:-0.23800
#> Median :2018-06-14 12:09:42.07 Median :-0.003000 Median :-0.05300
#> Mean :2018-06-14 12:09:42.07 Mean :-0.003874 Mean :-0.05134
#> 3rd Qu.:2018-06-14 12:10:13.25 3rd Qu.: 0.191000 3rd Qu.: 0.13800
#> Max. :2018-06-14 12:10:44.43 Max. : 0.370000 Max. : 0.31400
#> Z
#> Min. :-1.367
#> 1st Qu.:-0.997
#> Median :-0.982
#> Mean :-0.985
#> 3rd Qu.:-0.974
#> Max. :-0.496
# Use the sample actigraph csv file without timestamp
filepath = system.file('extdata', 'actigraph_no_timestamp.csv', package='MIMSunit')
# Check file format
readLines(filepath)[1:15]
#> [1] "------------ Data File Created By ActiGraph GT3X+ ActiLife v6.13.3 Firmware v2.5.0 date format M/d/yyyy at 40 Hz Filter Normal -----------,,"
#> [2] "Serial Number: CLE2B20130009,,"
#> [3] "Start Time 11:27:00,,"
#> [4] "Start Date 6/14/2018,,"
#> [5] "Epoch Period (hh:mm:ss) 00:00:00,,"
#> [6] "Download Time 15:16:42,,"
#> [7] "Download Date 6/14/2018,,"
#> [8] "Current Memory Address: 0,,"
#> [9] "Current Battery Voltage: 4.21 Mode = 12,,"
#> [10] "--------------------------------------------------,,"
#> [11] "Accelerometer X,Accelerometer Y,Accelerometer Z"
#> [12] "-0.009,-0.053,-0.988"
#> [13] "-0.009,-0.053,-0.982"
#> [14] "-0.009,-0.053,-0.988"
#> [15] "-0.009,-0.053,-0.982"
# Load the file without timestamp column
df = import_actigraph_csv(filepath, has_ts = FALSE)
# Check loaded file
head(df)
#> HEADER_TIME_STAMP X Y Z
#> 1 2018-06-14 11:27:00 -0.009 -0.053 -0.988
#> 2 2018-06-14 11:27:00 -0.009 -0.053 -0.982
#> 3 2018-06-14 11:27:00 -0.009 -0.053 -0.988
#> 4 2018-06-14 11:27:00 -0.009 -0.053 -0.982
#> 5 2018-06-14 11:27:00 -0.009 -0.053 -0.982
#> 6 2018-06-14 11:27:00 -0.009 -0.056 -0.988
# Check more
summary(df)
#> HEADER_TIME_STAMP X Y
#> Min. :2018-06-14 11:27:00.00 Min. :-0.370000 Min. :-0.41900
#> 1st Qu.:2018-06-14 11:27:31.18 1st Qu.:-0.202000 1st Qu.:-0.23800
#> Median :2018-06-14 11:28:02.34 Median :-0.003000 Median :-0.05300
#> Mean :2018-06-14 11:28:02.34 Mean :-0.003874 Mean :-0.05134
#> 3rd Qu.:2018-06-14 11:28:33.52 3rd Qu.: 0.191000 3rd Qu.: 0.13800
#> Max. :2018-06-14 11:29:04.70 Max. : 0.370000 Max. : 0.31400
#> Z
#> Min. :-1.367
#> 1st Qu.:-0.997
#> Median :-0.982
#> Mean :-0.985
#> 3rd Qu.:-0.974
#> Max. :-0.496
# Restore default options
options(default_ops)