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_
g.imputeTimegaps(x, sf, k = 0.25, impute = TRUE,
PreviousLastValue = c(0,0,1),
PreviousLastTime = NULL, epochsize = NULL)
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
Data.frame with raw accelerometer data, and a timestamp column with millisecond resolution.
Sample frequency in Hertz
Minimum time gap length to be imputed
Boolean to indicate whether the time gaps identified should be imputed
Automatically identified last value in previous chunk of data read.
Automatically identified last timestamp in previous chunk of data read.
Numeric vector of length two, with short and long epoch sizes.
Vincent T van Hees <v.vanhees@accelting.com>