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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.

The copyright of the work belongs to Northeastern University, mHealth Research Group. Please kindly cite the manuscript if you have used the package or referred to the algorithm in your work.

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.

1. R (>= 3.6.0)
2. memory (> 4GB)

Rtools >=3.5 (see: https://cran.r-project.org/bin/windows/Rtools/)

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

CRAN

install.packages('MIMSunit')

Github

install.packages("devtools")
devtools::install_github("mhealthgroup/MIMSunit")

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.

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