Automated Eye Tracking Data Quality Determination for Screen-Based Eye Trackers
R6 Screen Configuration Class
Standard Deviation of Gaze Samples
Convert 3D Vector to Fick Angles
Compute Gaze Accuracy
Bivariate Contour Ellipse Area (BCEA)
RMS of Sample-to-Sample Differences
Compute Data Quality Metrics from Validation Data
Compute Data Loss from Expected Sample Count
Compute Data Loss from number of invalid samples.
R6 class for calculating Data Quality from a gaze data segment
Compute Effective Sampling Frequency
Get ETDQualitizer Version
Convert Fick Angles to 3D Vector
Precision Using Moving Window
Summarize and Report Data Quality Metrics
Compute common data quality metrics for accuracy, precision and data loss for screen-based eye trackers. Supports input data both in pixels on the screen and in degrees, output measures are (where appropriate) expressed as angles in degrees.
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