An Adaptive Algorithm for Fixation, Saccade, and Glissade Detection in Eye-Tracking Data (Nyström M. & Holmqvist K, 2009)

From Markus Nyström and Kenneth Holmqvist at the Lund University Humanities Lab (HumLab) in Sweden comes an interesting paper on a novel algorithm that is capable of detecting glissades (aka dynamic overshoot) in eye tracker data. These are wobbling eye movements often found at the end of saccades and has previously been considered errors in saccadic programming with limited value. What ever their function is the phenomena does exists and should be accounted for. The paper reports finding glissades following half of all saccades while reading or viewing scenes, and has an average duration of 24 ms. This is work is important as it extends the default categorization of eye movement e.g. fixation, saccade, smooth pursuit, and blink. The algorithm is based on velocity saccade detection and is driven by data while containing a limited number of subjective settings. The algorithm contains a number of improvements such as thresholds for peak- and saccade onset/offset detection, adaptive threshold adjustment based on local noise levels, physical constraints on eye-movements to exclude noise and jitter, and new recommendations for minimum allowed fixation and saccade duration. Also, important to note that the data was obtained using a high-speed 1250 Hz SMI system, how the algorithm performs on a typical remote tracker running at 50-250Hz has yet to be defined.

• Nyström, M. & Holmqvist, K., "An Adaptive Algorithm for Fixation, Saccade, and Glissade Detection in Eye-Tracking Data", Behavior Research Methods.
  
  
• Download Matlab source code for the algorithm (version 1.0)