get_confounds_for_step: Calculate confounds for a single pupil data step

In eyeris: Flexible, Extensible, & Reproducible Pupillometry Preprocessing

Calculate confounds for a single pupil data step

Description

Computes various metrics from pupil data including:

• Missing data (count and proportion of NA samples)

• Blink detection

• Gaze on/off screen detection

• Gap analysis

• Gaze distance from screen center

• Gaze variance

• Blink rate

• Blink duration

• Blink time

Usage

get_confounds_for_step(pupil_df, pupil_vec, screen_width, screen_height, hz)

Arguments

pupil_df	A data frame containing pupil data
pupil_vec	A vector of pupil data for the current step
screen_width	The screen width in pixels
screen_height	The screen height in pixels
hz	The sampling rate in Hz

Details

Missing data is reported as both a raw count (n_missing) and a proportion (prop_missing, ranging from 0 to 1) of samples in the window for which the pupil signal is NA (e.g., blinks and signal dropout prior to interpolation). Multiply prop_missing by 100 to obtain a percentage. This is distinct from prop_invalid, which additionally folds in samples flagged as blinks or off-screen gaze.

Value

A data frame containing confounds metrics for the current step, including n_missing and prop_missing (the count and proportion of missing/NA samples)

eyeris documentation built on June 19, 2026, 9:08 a.m.