Classification Algorithm for Saccadic Oculomotor Behavior

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dc.contributor.authorKomogortsev, Oleg
dc.contributor.authorGobert, Denise V.
dc.contributor.authorDai, Zanxun
dc.date.accessioned2010-05-06T10:03:26Z
dc.date.available2012-02-24T10:03:27Z
dc.date.issued2010-05-04
dc.description.abstractThis paper presents a detection algorithm that allows automatic classification of hypermetric and hypometric oculomotor plant behavior in cases when saccadic behavior of the oculomotor plant is assessed during the course of the step stimulus. Such behavior can be classified with a number of oculomotor plant metrics represented by the number of overshoots, undershoots, corrected undershoots/overshoots, multi-corrected overshoots/undershoots. The algorithm presented in this paper allows for the automated classification of nine oculomotor plant metrics including dynamic overshoots and express saccades. Data from sixty-five human subjects were used to support this experimental study. The performance of the proposed algorithm was tested and compared to manual classification methods resulting in a detection accuracy of up to 72% for several of the oculomotor plant metrics.
dc.description.departmentComputer Science
dc.formatText
dc.format.extent6 pages
dc.format.medium1 file (.pdf)
dc.identifier.citationKomogortsev, O. V., Gobert, D., & Dai, Z. (2010). Classification algorithm for saccadic oculomotor behavior (Report No. TXSTATE-CS-TR-2010-23). Texas State University-San Marcos, Department of Computer Science.
dc.identifier.urihttps://hdl.handle.net/10877/2578
dc.language.isoen
dc.subjectclassification
dc.subjectalgorithm
dc.subjectsaccade
dc.subjecteye tracking
dc.subjectbehavior
dc.subjectoculomotor
dc.subjectComputer Science
dc.titleClassification Algorithm for Saccadic Oculomotor Behavior
dc.typeTechnical Report

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