g.imputeTimegaps: Impute gaps in three axis raw accelerometer data

In GGIR: Raw Accelerometer Data Analysis

Impute gaps in three axis raw accelerometer data

Description

Removes all sample with a zero in each of the three axes, and then (as default) imputes time gaps by the last recorded value per axis normalised to 1 _g_

Usage

  g.imputeTimegaps(x, sf, k = 0.25, impute = TRUE, 
                   PreviousLastValue = c(0,0,1), 
                   PreviousLastTime = NULL, epochsize = NULL)

Arguments

x	Data.frame with raw accelerometer data, and a timestamp column with millisecond resolution.
sf	Sample frequency in Hertz
k	Minimum time gap length to be imputed
impute	Boolean to indicate whether the time gaps identified should be imputed
PreviousLastValue	Automatically identified last value in previous chunk of data read.
PreviousLastTime	Automatically identified last timestamp in previous chunk of data read.
epochsize	Numeric vector of length two, with short and long epoch sizes.

Value

List including: - x, data.frame based on input x with timegaps imputed (as default) or with recordings with 0 values in the three axes removed (if impute = FALSE) - QClog, data.frame with information on the number of time gaps found and the total time imputed in minutes

Author(s)

Vincent T van Hees <[e-mail]>

GGIR documentation built on April 3, 2025, 6 p.m.