title: Automatic identification of oculomotor behavior using pattern recognition techniques.
abstract: In this paper, a methodological scheme for identifying distinct patterns of oculomotor behavior such as saccades, microsaccades, blinks and fixations from time series of eye's angular displacement is presented. The first step of the proposed methodology involves signal detrending for artifacts removal and estimation of eye's angular velocity. Then, feature vectors from fourteen first-order statistical features are formed from each angular displacement and velocity signal using sliding, fixed-length time windows. The obtained feature vectors are used for training and testing three artificial neural network classifiers, connected in cascade. The three classifiers discriminate between blinks and non-blinks, fixations and non-fixations and saccades and microsaccades, respectively. The proposed methodology was tested on a dataset from 1392 subjects, each performing three oculomotor fixation conditions. The average overall accuracy of the three classifiers, with respect to the manual identification of eye movements by experts, was 95.9%. The proposed methodological scheme provided better results than the well-known Velocity Threshold algorithm, which was used for comparison. The findings of the present study indicate that the utilization of pattern recognition techniques in the task of identifying the various eye movements may provide accurate and robust results.
authors.affiliation: School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
authors.forename: Alexandra I
authors.initials: AI
authors.lastname: Korda
authors.affiliation: Department of Biomedical Engineering, Faculty of Technological Applications, Technological Educational Institute of Athens, Agiou Spyridonos Str., Egaleo 12243, Greece. Electronic address: pasv@teiath.gr.
authors.forename: Pantelis A
authors.initials: PA
authors.lastname: Asvestas
authors.affiliation: School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
authors.forename: George K
authors.initials: GK
authors.lastname: Matsopoulos
authors.affiliation: Department of Biomedical Engineering, Faculty of Technological Applications, Technological Educational Institute of Athens, Agiou Spyridonos Str., Egaleo 12243, Greece.
authors.forename: Errikos M
authors.initials: EM
authors.lastname: Ventouras
authors.affiliation: Laboratory of Sensorimotor Control, University Mental Health Research Institute, Athens, Greece; Psychiatry Department, National and Kapodistrian University of Athens, Eginition Hospital, Athens, Greece.
authors.forename: Nikolaos P
authors.initials: NP
authors.lastname: Smyrnis
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D016477:Artifacts; D005133:Eye Movements / Q000502:physiology*; D006801:Humans; D008297:Male; D015233:Models, Statistical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012438:Saccades / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
keywords: Blinks; Classification; Fixation; Microsaccades; Neural network; Saccades; Velocity threshold algorithm