An Improved Algorithm for Automatic Detection of Saccades in Eye Movement Data and for Calculating Saccade Parameters

Behrens F, Mackeben M, Schröder-Preikschat W (2010)

Publication Type: Journal article

Publication year: 2010

Journal

Behavior Research Methods Psychonomic Society / Springer Verlag (Germany)

Publisher: Psychonomic Society / Springer Verlag (Germany)

Book Volume: 42

Pages Range: 701-708

Journal Issue: 3

URI: http://www4.informatik.uni-erlangen.de/Publications/2010/behrens_brm_42_3.pdf

DOI: 10.3758/BRM.42.3.701

Abstract

This analysis of time series of eye movements is a saccade-detection algorithm that is based on an earlier algorithm. It achieves substantial improvements by using an adaptive-threshold model instead of fixed thresholds and using the eye-movement acceleration signal. This has four advantages: (1) Adaptive thresholds are calculated automatically from the preceding acceleration data for detecting the beginning of a saccade, and thresholds are modified during the saccade. (2) The monotonicity of the position signal during the saccade, together with the acceleration with respect to the thresholds, is used to reliably determine the end of the saccade. (3) This allows differentiation between saccades following the main-sequence and non-main-sequence saccades. (4) Artifacts of various kinds can be detected and eliminated. The algorithm is demonstrated by applying it to human eye movement data (obtained by EOG) recorded during driving a car. A second demonstration of the algorithm detects microsleep episodes in eye movement data. © 2010 The Psychonomic Society, Inc.

Authors with CRIS profile

Wolfgang Schröder-Preikschat Lehrstuhl für Informatik 4 (Verteilte Systeme und Betriebssysteme)

Involved external institutions

Otto-von-Guericke-Universität Magdeburg DE Germany (DE) Smith-Kettlewell Eye Research Institute US United States (USA) (US)

How to cite

APA:

Behrens, F., Mackeben, M., & Schröder-Preikschat, W. (2010). An Improved Algorithm for Automatic Detection of Saccades in Eye Movement Data and for Calculating Saccade Parameters. Behavior Research Methods, 42(3), 701-708. https://dx.doi.org/10.3758/BRM.42.3.701

MLA:

Behrens, F., M. Mackeben, and Wolfgang Schröder-Preikschat. "An Improved Algorithm for Automatic Detection of Saccades in Eye Movement Data and for Calculating Saccade Parameters." Behavior Research Methods 42.3 (2010): 701-708.

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