Detection of fixations and smooth pursuit movements in high-speed eye-tracking data

Research output: Contribution to journalArticle

Abstract

A novel algorithm for the detection of fixations and smooth pursuit movements in high-speed eye-tracking data is proposed, which uses a three-stage procedure to divide the intersaccadic intervals intoa sequence of fixation and smooth pursuit events. The first stage performs a preliminary segmentationwhile the latter two stages evaluate the characteristics of each such segment and reorganize the pre-liminary segments into fixations and smooth pursuit events. Five different performance measures arecalculated to investigate different aspects of the algorithm’s behavior. The algorithm is compared to thecurrent state-of-the-art (I-VDT and the algorithm in [11]), as well as to annotations by two experts. Theproposed algorithm performs considerably better (average Cohen’s kappa 0.42) than the I-VDT algorithm(average Cohen’s kappa 0.20) and the algorithm in [11] (average Cohen’s kappa 0.16), when comparedto the experts’ annotations.

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Medical Engineering

Keywords

  • smooth pursuit, eye-tracking, Signal processing
Original languageEnglish
Pages (from-to)145-152
JournalBiomedical Signal Processing and Control
Volume18
Publication statusPublished - 2015
Publication categoryResearch
Peer-reviewedYes