single_trial

A single trial monocular samples recorded at 500 Hz.

datasets

A modular and extendable approach to extract (micro)saccades from gaze samples via an ensemble of methods.
Although there is an agreement about a general definition of a saccade, the more specific details are harder to agree upon.
Therefore, there are numerous algorithms that extract saccades based on various heuristics, which differ in the assumptions about velocity,
acceleration, etc. The package uses three methods (Engbert and Kliegl (2003) <doi:10.1016/S0042-6989(03)00084-1>,
Otero-Millan et al. (2014)<doi:10.1167/14.2.18>, and Nyström and Holmqvist (2010) <doi:10.3758/BRM.42.1.188>)
to label individual samples and then applies a majority vote approach to identify saccades. The package includes three
methods but can be extended via custom functions. It also uses a modular approach to compute velocity and
acceleration from noisy samples. Finally, you can obtain methods votes per gaze sample instead of saccades.

Alexander (Sasha) Pastukhov

saccadr

Extract Saccades via an Ensemble of Methods Approach

Alexander Pastukhov

single_trial function

A data frame with 1006 rows and 2 variables:<dl>
 <dt>x</dt>
<dd>X coordinate in degrees of visual angle.</dd> <dt>y</dt>
<dd>Y coordinate in degrees of visual angle.</dd>
</dl>

Format

A single trial monocular samples recorded at 500 Hz. — single_trial

A data frame with 1006 rows and 2 variables:<dl>
 <dt>x</dt>
<dd>X coordinate in degrees of visual angle.</dd>

 <dt>y</dt>
<dd>Y coordinate in degrees of visual angle.</dd>


</dl>

single_trial: A single trial monocular samples recorded at 500 Hz.

Description

Usage

Arguments

Format