Please create github issues if you have any question related to the package.
MIMS-unit is abbreviated for Monitor Independent Movement Summary unit. This measurement is developed to harmonize the processing of accelerometer data from different devices. You may refer to the manuscript for the detail description of the algorithm.
Copyright and citation
Shiny Demo App
You may try to compute MIMS-unit values using our shiny demo app https://qutang.shinyapps.io/MIMSunit/. Note that the upload file size limit is 50 MB. The usage quote for the server is limited, so we do not guarantee the web app is always available to you.
All datasets used in the manuscript are available at https://mhealthgroup.github.io/MIMSunit/articles/datasets.html.
- R (>= 3.6.0)
- memory (> 4GB)
Rtools 3.5 (see: https://cran.r-project.org/bin/windows/Rtools/)
For Linux (use ubuntu as an example)
Install dependency system packages for
Osler in health
Note: It is recommended to use Rstudio when installing the package, because
devtools has some compatible issues with R command line interface.
MIMSunit::mims_unit(input_dataframe, dynamic_range=c(-3,3), epoch='1 min')
Assume the input dataframe is in following format, with the first column (timestamp) in
POSXlct objects and the device used to collect this data has dynamic range being -3g to 3g. You may set the epoch length to be
10 sec and so on.
HEADER_TIME_STAMP,X,Y,Z 2016-10-03 14:51:14.236,0.007,-0.005,0.984 2016-10-03 14:51:14.256,0.008,-0.007,0.981 2016-10-03 14:51:14.276,0.009,-0.006,0.978 2016-10-03 14:51:14.297,0.009,-0.007,0.984 2016-10-03 14:51:14.317,0.010,-0.010,0.982 2016-10-03 14:51:14.337,0.011,-0.010,0.982