g.part5.classifyNaps: Classify Naps from identified sustained inactivty bouts

In GGIR: Raw Accelerometer Data Analysis

Classify Naps from identified sustained inactivty bouts

Description

Classify Naps from identified sustained inactivty bouts, based on model that was originally trained with hip-worn accelerometer data in 3-3.5 year olds. Assume that metric ENMO is used and HASIB.algo is set to vanHees2015.

Usage

  g.part5.classifyNaps(sibreport = c(), desiredtz = "", 
        possible_nap_window = c(9, 18),
        possible_nap_dur = c(15, 240),
        nap_model = "hip3yr", HASIB.algo = "vanHees2015")

Arguments

sibreport	Object generated by g.sibreport
desiredtz	See g.getmeta.
possible_nap_window	Numeric vector of length two with range in clock hours during which naps are assumed to take place.
possible_nap_dur	Numeric vector of length two with range in duration (minutes) of a nap.
nap_model	Character to specify classification model. Currently the only option is "hip3yr", which corresponds to a model trained with hip data in 3-3.5 olds trained with parent diary data.
HASIB.algo	See g.part3.

Value

Data.frame with classified naps and newly detected non-wear periods.

Author(s)

Vincent T van Hees <[e-mail]>

GGIR documentation built on Oct. 17, 2023, 1:12 a.m.