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tombeesley
eyetools:Analyse Eye Data
Enables the automation of actions across the pipeline, including initial steps of transforming binocular data and gap repair to event-based processing such as fixations, saccades, and entry/duration in Areas of Interest (AOIs). It also offers visualisation of eye movement and AOI entries. These tools take relatively raw (trial, time, x, and y form) data and can be used to return fixations, saccades, and AOI entries and time spent in AOIs. As the tools rely on this basic data format, the functions can work with data from any eye tracking device. Implements fixation and saccade detection using methods proposed by Salvucci and Goldberg (2000) <doi:10.1145/355017.355028>.
Maintained by Tom Beesley. Last updated 3 months ago.
areas-of-interestattention-visualizationcognitive-sciencedwell-time-algorithmeye-trackereye-trackingeyetrackingggplot2psychologypsychology-experimentssaccadestobiitobii-eye-trackervisualization
21.1 match 4 stars 5.45 score 8 scripts
drjohanlk
kollaR:Filtering, Visualization and Analysis of Eye Tracking Data
Functions for analysing eye tracking data, including event detection (I-VT, I-DT and two means clustering), visualizations and area of interest (AOI) based analyses. See separate documentation for each function. The principles underlying I-VT and I-DT filters are described in Salvucci & Goldberg (2000,\doi{10.1145/355017.355028}). Two-means clustering is described in Hessels et al. (2017, \doi{10.3758/s13428-016-0822-1}).
Maintained by Johan Lundin Kleberg. Last updated 24 days ago.
1.5 match 1.30 score