Detects fixations by assessing dispersion of the eye position, using a method that is similar to that proposed by Salvucci & Goldberg (2000). Evaluates the maximum dispersion (distance) between x/y coordinates across a window of data. Looks for sufficient periods in which this maximum dispersion is below the specified dispersion tolerance. NAs are considered breaks in the data and are not permitted within a valid fixation period.
fixation_dispersion(
data,
min_dur = 150,
disp_tol = 100,
NA_tol = 0.25,
progress = TRUE
)a dataframe containing each detected fixation by trial, with mean x/y position in pixel, start and end times, and duration.
A dataframe with raw data (time, x, y, trial) for one participant (the standardised raw data form for eyetools)
Minimum duration (in milliseconds) of period over which fixations are assessed
Maximum tolerance (in pixels) for the dispersion of values allowed over fixation period
the proportion of NAs tolerated within any window of samples that is evaluated as a fixation
Display a progress bar
It can take either single participant data or multiple participants, where participants are demarcated by values in the "pID" column.
Salvucci, D. D., & Goldberg, J. H. (2000). Identifying fixations and saccades in eye-tracking protocols. Proceedings of the Symposium on Eye Tracking Research & Applications - ETRA '00, 71–78.
# \donttest{
data <- combine_eyes(HCL)
fixation_dispersion(data)
# }
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