Introduction

GGIR can automatically read data from the most-frequently used accelerometer brands in the field:

• GENEActiv .bin
• Axivity AX3 and AX6 .wav, .csv and .cwa
• ActiGraph .csv and .gt3x (.gt3x only the newer format generated with firmware versions above 2.5.0). Note for Actigraph users: If you want to work with .csv exports via the ActiLife then note that you have the option to export data with timestamps. Please do not do this as this causes memory issues for GGIR. To cope with the absence of timestamps GGIR will re-caculate timestamps from the sample frequency and the start time and date as presented in the file header
• Movisens with data stored in folders
• Genea (an accelerometer that is not commercially available anymore, but which was used for some studies between 2007 and 2012) .bin and .csv

However, the accelerometer manufacturers are proliferating with an increasing number of brands in the market. For such reason, GGIR includes the read.myacc.csv function, which is able to read accelerometer raw triaxial data stored in csv files, independently of the brand. This vignette provides a general introduction on how to use GGIR to read accelerometer raw data stored in csv files.

How it works:

Internally GGIR loads csv files with accelerometer data and standardises the output format to make the data compatible with other GGIR functions. Data format standardisation includes unit of measurement, timestamp, header format, and column locations.

The read.myacc.csv function

As for the rest of GGIR functions, read.myacc.csv is intended to be used within function GGIR. All the arguments of the read.myacc.csv can be easily recognized as they all start by “rmc”. GGIR checks whether argument rmc.firstrow.acc is provided by the user; in such case, GGIR will attempt to read the data with function read.myacc.csv. In other words you always need to specify rmc.firstrow.acc to use read.myacc.csv. Further, we recommend that you always first test the function argument settings by first trying to use function read.myacc.csv on its own. When that works copy the arguments to you GGIR call.

Usage of the read.myacc.csv function

This section shows an example real case in which the read.myacc.csv function can be used. The csv file to be read has the following structure:

This file contains timestamps in the column 1 (formatted as “%d/%m/%Y %H:%M:%OS”), the acceleration signals (in g’s) for the x, y, and z axis in the columns 2, 3, and 4, respectively, and temperature information in Celsius in the column 5. Also, this file has no header.

Before we can use this with GGIR, we first test read this file using the read.myacc.csv function directly.

library(GGIR)
read.myacc.csv(rmc.file = "C:/mystudy/mydata/datafile.csv",
               rmc.nrow = Inf,
               rmc.skip = 0,
               rmc.dec = ".",
               rmc.firstrow.acc = 2,
               rmc.col.acc = 2:4,
               rmc.col.temp = 5,
               rmc.col.time=1,
               rmc.unit.acc = "g",
               rmc.unit.temp = "C",
               rmc.unit.time = "POSIX",
               rmc.format.time = "%d/%m/%Y %H:%M:%OS",
               desiredtz = "Europe/London",
               rmc.sf = 100)

library(GGIR)
GGIR(
             mode=c(1,2,3,4,5),
             datadir="C:/mystudy/mydata/datafile.csv",
             outputdir="D:/myresults",
             do.report=c(2,4,5),
             #=====================
             # read.myacc.csv arguments
             #=====================
             rmc.nrow = Inf, 
             rmc.dec = ".",
             rmc.firstrow.acc = 2, 
             rmc.col.acc = 2:4, 
             rmc.col.temp = 5, 
             rmc.col.time=1,
             rmc.unit.acc = "g", 
             rmc.unit.temp = "C", 
             rmc.unit.time = "POSIX",
             rmc.format.time = "%d/%m/%Y %H:%M:%OS",
             desiredtz = "Europe/London",
             rmc.sf = 100,
             rmc.noise = 0.013
)