Analyse Eye Data

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Documentation for package ‘eyetools’ version 0.9.2

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AOI_seq Sequence analysis of area of interest entries
AOI_time Analysis of time spent in areas of interest
AOI_time_binned Binned time analysis of area of interest entries
combine_eyes Combine binocular data into single X/Y coordinate pairs
compare_algorithms A battery of metrics and plots to compare the two algorithms (dispersion and VTI)
conditional_transform conditional_transform
create_AOI_df Create a blank data frame for populating with AOIs
dist_to_visual_angle Compute visual angle from distance metrics
fixation_dispersion Fixation detection using a dispersion method
fixation_VTI Fixation detection using a velocity threshold identification method
HCL Example dataset from that contains binocular eye data from two participants from a simple contingency learning task (the data are from Beesley, Nguyen, Pearson, & Le Pelley, 2015). In this task there are two stimuli that appear simultaneously on each trial (to the left and right of the screen). Participants look at these cues and then make a decision by selecting an "outcome response" button.
HCL_AOIs Example AOIs for use with HCL
HCL_behavioural Example dataset of behavioural data to complement dataset HCL.
hdf5_get_event Get messgaes stored in TOBII-generated HDF5 files
hdf5_to_df Convert TOBII-generated HDF5 files to dataframe
interpolate Interpolation of missing data (NAs)
plot_AOI_growth Plots absolute or proportional time spent in AOIs over time
plot_heatmap Plot heatmap of raw data
plot_seq Plot of raw data over time
plot_spatial Plot raw data and fixations
saccade_VTI Velocity threshold identification of saccades
smoother Smoothing of raw data