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

Linnéa Larsson, Marcus Nyström, Richard Andersson, Martin Stridh

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Pages (from-to)145-152
JournalBiomedical Signal Processing and Control
Volume18
DOIs
Publication statusPublished - 2015

Subject classification (UKÄ)

  • Medical Engineering

Free keywords

  • smooth pursuit
  • eye-tracking
  • Signal processing

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