This work is in submission/revision. Before the time of publication, the manuscript will not be available. At the time of publication, this site will be updated with additional code/documentation. Before publication, the codes are subject to refactoring. Please create github issues if you have any question related to the package.

Short introduction

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 in publishing manuscript for the detail description of the algorithm. If you would like to get access to the manuscript, please contact Qu Tang or Dinesh John.

System Requirements

  1. R (>3.5.1)
  2. memory (> 4GB)

For Windows

Rtools 3.5 (see:

For Linux (use ubuntu as an example)

Install depedency system packages for devtools: build-essential, libcurl4-gnutls-dev, libxml2-dev, libssl-dev.


  1. Stable version on CRAN (bundled or binary)

Coming soon…

  1. Development version (source codes)
  • For Windows users
devtools::install_github("qutang/MIMSunit", type='win.binary')
  • For mac or Linux users

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 1 min, 1 sec, 5 sec, 10 sec and so on.

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