Standardization of Automated Analyses of Oculomotor Fixation and Saccadic Behaviors

• Published in: IEEE transactions on biomedical engineering Vol. 57; no. 11; pp. 2635 - 2645
• Main Authors: Komogortsev, Oleg V., Gobert, Denise V., Jayarathna, Sampath, Koh, Do Hyong, Gowda, Sandeep M.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.11.2010; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adolescent; Adult; Algorithms; Alzheimer's disease; Analysis; baseline; Biological and medical sciences; Brain injuries; Classification; Classification algorithms; Computer science; Eye and associated structures. Visual pathways and centers. Vision; eye-movement classification; Female; Fixation, Ocular - physiology; Fundamental and applied biological sciences. Psychology; Humans; Investigative techniques of ocular function and vision; Investigative techniques, diagnostic techniques (general aspects); Logic; Male; Medical sciences; oculomotor behavior; Permission; Psychology; Saccades - physiology; Standardization; Vertebrates: nervous system and sense organs; Visual system; Young Adult; Human; Standardization; Exploration; baseline; Algorithm; Eye movement; oculomotor behavior; Analysis; Classification; Technique; Automatic analysis; Mathematical model; Comparative study; Biomedical engineering; eye-movement classification
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2010.2057429

In an effort toward standardization, this paper evaluates the performance of five eye-movement classification algorithms in terms of their assessment of oculomotor fixation and saccadic behavior. The results indicate that performance of these five commonly used algorithms vary dramatically, even in the case of a simple stimulus-evoked task using a single, common threshold value. The important contributions of this paper are: evaluation and comparison of performance of five algorithms to classify specific oculomotor behavior; introduction and comparison of new standardized scores to provide more reliable classification performance; logic for a reasonable threshold-value selection for any eye-movement classification algorithm based on the standardized scores; and logic for establishing a criterion-based baseline for performance comparison between any eye-movement classification algorithms. Proposed techniques enable efficient and objective clinical applications providing means to assure meaningful automated eye-movement classification.