saccade_VTI: Velocity threshold identification of saccades

In eyetools: Analyse Eye Data

Velocity threshold identification of saccades

Description

Use the velocity threshold algorithm from Salvucci & Goldberg (2000) to determine saccadic eye movements. Returns a summary of the saccades found per trial, including start and end coordinates, timing, duration, mean velocity, and peak velocity.

Usage

saccade_VTI(data, sample_rate = NULL, threshold = 150, min_dur = 20)

Arguments

data	A dataframe with raw data (time, x, y, trial) for one participant
sample_rate	sample rate of the eye-tracker. If default of NULL, then it will be computed from the timestamp data and the number of samples
threshold	velocity threshold (degrees of VA / sec) to be used for identifying saccades
min_dur	minimum duration (ms) expected for saccades. This helps to avoid identification of very short saccades occurring at the boundary of velocity threshold

Details

Analyses data separately for each unique combination of values in pID and trial.

Value

a data frame giving the saccades found by trial

References

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.

Examples

data <- combine_eyes(HCL)
saccade_VTI(data)

eyetools documentation built on June 18, 2025, 5:08 p.m.