find_peaks

internal

Segmentation and classification procedures for data from the 'Activinsights GENEActiv' <https://activinsights.com/technology/geneactiv/> accelerometer that provides the user with a model to guess behaviour from test data where behaviour is missing.
Includes a step counting algorithm, a function to create segmented data with custom features and a function to use recursive partitioning provided in the function rpart() of the 'rpart' package to create classification models.

Charles Sweetland

GENEAclassify

Segmentation and Classification of Accelerometer Data

Chris Campbell

Aimee Gott

Joss Langford

Activinsights Ltd 

find_peaks function

<dl><dt>x</dt>
<dd>timeseries signal</dd>
<dt>m</dt>
<dd>The number of points either side of the peak to required to be a peak.</dd></dl>

Arguments

Find_Peaks — find_peaks

<dl>

<dt>x</dt>
<dd>timeseries signal</dd>


<dt>m</dt>
<dd>The number of points either side of the peak to required to be a peak.</dd>

</dl>

Find_Peaks

find_peaks: Find_Peaks

Description

Usage

Arguments

Details