The dataset contains data from two participants and the first six trials of the study.

datasets

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>.

Tom Beesley

eyetools

Analyse Eye Data

Matthew Ivory

HCL function

A dataframe of 31,041 observations and seven variables<dl>
<dt>pID</dt>
<dd>participant ID</dd><dt>time</dt>
<dd>timestamp of the sample (milliseconds)</dd><dt>left_x</dt>
<dd>x coordinate of the left eye</dd><dt>left_y</dt>
<dd>y coordinate of the left eye</dd><dt>right_x</dt>
<dd>x coordinate of the right eye</dd><dt>right_y</dt>
<dd>y coordinate of the right eye</dd><dt>trial</dt>
<dd>trial number</dd>...</dl>

Format

Example dataset from that contains binocular eye data from two participants from a simple contingency learning task
(the data are from Beesley, Nguyen, Pearson, &amp; 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

A dataframe of 31,041 observations and seven variables<dl>
<dt>pID</dt>
<dd>participant ID</dd>

<dt>time</dt>
<dd>timestamp of the sample (milliseconds)</dd>

<dt>left_x</dt>
<dd>x coordinate of the left eye</dd>

<dt>left_y</dt>
<dd>y coordinate of the left eye</dd>

<dt>right_x</dt>
<dd>x coordinate of the right eye</dd>

<dt>right_y</dt>
<dd>y coordinate of the right eye</dd>

<dt>trial</dt>
<dd>trial number</dd>

...

</dl>

Example dataset from that contains binocular eye data from two participants from a simple contingency learning task
(the data are from Beesley, Nguyen, Pearson, &amp; 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.

Description

Usage

Arguments

Format