rest_on_table

The dataset includes accelerometer data sampled at 80Hz and 6g. This data is used to derive the thresholding.

datasets

The MIMS-unit algorithm is developed to compute Monitor Independent
Movement Summary Unit, a measurement to summarize raw accelerometer data
while ensuring harmonized results across different devices. It also includes
scripts to reproduce results in the related publication
(John, D., Tang. Q., Albinali, F. and Intille, S. (2019) <doi:10.1123/jmpb.2018-0068>).

Qu Tang

MIMSunit

Algorithm to Compute Monitor Independent Movement Summary Unit
(MIMS-Unit)

Dinesh John

Stephen Intille

mHealth Research Group 

rest_on_table function

A data frame with 5000 rows and 4 variables:<dl class="dl-horizontal">
 <dt>HEADER_TIME_STAMP</dt><dd>The timestamp of raw accelerometer data, in POSIXct</dd>
 <dt>X</dt><dd>The x axis value of raw accelerometer data, in number</dd>
 <dt>Y</dt><dd>The x axis value of raw accelerometer data, in number</dd>
 <dt>Z</dt><dd>The x axis value of raw accelerometer data, in number</dd>
</dl>

Format

A short snippet of raw accelerometer signal from a device resting on a table. — rest_on_table

A data frame with 5000 rows and 4 variables:<dl class='dl-horizontal'>
 <dt>HEADER_TIME_STAMP</dt><dd>The timestamp of raw accelerometer data, in POSIXct</dd>
 <dt>X</dt><dd>The x axis value of raw accelerometer data, in number</dd>
 <dt>Y</dt><dd>The x axis value of raw accelerometer data, in number</dd>
 <dt>Z</dt><dd>The x axis value of raw accelerometer data, in number</dd>
</dl>

rest_on_table: A short snippet of raw accelerometer signal from a device resting on a table.

Description

Usage

Arguments

Format