Friday, September 11, 2009

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.


Marcus said...

Hi Martin,

Thank you for this post! The algorithm has been tested on 250 Hz data (recorded with the SMI RED250 system) with a promising outcome. It can however be discussed whether glissades can be robustly identified at this rate.
More detailed results on how it performs on data collected with lower sampling frequencies will soon be available.

Keep up the good work with your blog!

/Marcus Nyström

Martin Tall said...

Hi Marcus,

Looking forward to more details on the performance of the algorithm and the RED250. Kudos for releasing the Matlab code!

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Giuseppe Marchioro said...
This comment has been removed by the author.
Giuseppe Marchioro said...

Dear Martin,
thank you for the post.
Unfortunately the links are not working anymore. I found and read the article, but I could not find an alternative link to the Matlab code.
May you know where I can find the code?

Thank you in advance.
Best regards,

Team said...

Hi.. Great site.. But the link to Matlab Code is not working.. Please look into it.. Thanks in Advance.

Henrique Cesar said...

New link for the algorithm: