Microsaccade characterization using the continuous wavelet transform and principal component analysis

During visual fixation on a target, humans perform miniature (or fixational) eye movements consisting of three components, i.e., tremor, drift, and microsaccades. Microsaccades are high velocity components with small amplitudes within fixational eye movements. However, microsaccade shapes and statis...

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Bibliographic Details
Main Authors: Mario Bettenbühl, Claudia Paladini, Konstantin Mergenthaler, Reinhold Kliegl, Ralf Engbert, Matthias Holschneider
Format: Article
Language:English
Published: Bern Open Publishing 2010-10-01
Series:Journal of Eye Movement Research
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Online Access:https://bop.unibe.ch/JEMR/article/view/2306
Description
Summary:During visual fixation on a target, humans perform miniature (or fixational) eye movements consisting of three components, i.e., tremor, drift, and microsaccades. Microsaccades are high velocity components with small amplitudes within fixational eye movements. However, microsaccade shapes and statistical properties vary between individual observers. Here we show that microsaccades can be formally represented with two significant shapes which we identfied using the mathematical definition of singularities for the detection of the former in real data with the continuous wavelet transform. For character-ization and model selection, we carried out a principal component analysis, which identified a step shape with an overshoot as first and a bump which regulates the overshoot as second component. We conclude that microsaccades are singular events with an overshoot component which can be detected by the continuous wavelet transform.
ISSN:1995-8692