g.detecmidnight

Detect all midnights in a time series

internal

A tool to process and analyse data collected with wearable raw acceleration sensors as described in Migueles and colleagues (JMPB 2019), and van Hees and colleagues (JApplPhysiol 2014; PLoSONE 2015). The package has been developed and tested for binary data from 'GENEActiv' <https://activinsights.com/>, binary (.gt3x) and .csv-export data from 'Actigraph' <https://theactigraph.com> devices, and binary (.cwa) and .csv-export data from 'Axivity' <https://axivity.com>. These devices are currently widely used in research on human daily physical activity. Further, the package can handle accelerometer data file from any other sensor brand providing that the data is stored in csv format. Also the package allows for external function embedding.

Vincent T van Hees

GGIR

Raw Accelerometer Data Analysis

Jairo H Migueles

Severine Sabia

Matthew R Patterson

Zhou Fang

Joe Heywood

Joan Capdevila Pujol

Lena Kushleyeva

Mathilde Chen

Manasa Yerramalla

Patrick Bos

Taren Sanders

Chenxuan Zhao

Ian Meneghel Danilevicz

Victor Barreto Mesquita

Gaia Segantin

Medical Research Council UK 

Accelting 

French National Research Agency 

g.detecmidnight function

<dl> <dt>time</dt>
<dd>Vector of timestamps, either in iso8601 or in POSIX format</dd> <dt>desiredtz</dt>
<dd>See g.part2</dd> <dt>dayborder</dt>
<dd>see g.analyse</dd> 
</dl>

Arguments

Vincent T van Hees &lt;v.vanhees@accelting.com&gt;

Author

Detect all midnights in a time series — g.detecmidnight

<dl>

 <dt>time</dt>
<dd>Vector of timestamps, either in iso8601 or in POSIX format</dd>

 <dt>desiredtz</dt>
<dd>See g.part2</dd>

 <dt>dayborder</dt>
<dd>see g.analyse</dd>

 
</dl>

Detect all midnights in a time series

g.detecmidnight: Detect all midnights in a time series

Description

Usage

Value

Arguments

Author