Detecting cognitive impairment by eye movement analysis using automatic classification algorithms

Journal of Neuroscience Methods

Volumn 201, Issue 1, 2011, Pages 196-203

  Lagun, Dmitry ^a   Manzanares, Cecelia ^a   Zola, Stuart M ^a,c,d   Buffalo, Elizabeth A ^a,b   Agichtein, Eugene ^a  

^a EMORY UNIVERSITY   (United States)

^b EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c Alzheimer's Disease Research Center   (United States)

^d VETERANS AFFAIRS MEDICAL CENTER   (United States)

Author keywords

Alzheimer's disease; Behavioral test; Eye movement; Recognition memory

Indexed keywords

AGED; ALZHEIMER DISEASE; AREA UNDER THE CURVE; ARTICLE; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; EYE FIXATION; EYE MOVEMENT; HUMAN; LOGISTIC REGRESSION ANALYSIS; MEMORY; MILD COGNITIVE IMPAIRMENT; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SACCADIC EYE MOVEMENT; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; TASK PERFORMANCE; TECHNIQUE; VISUAL PAIRED COMPARISON; VISUAL STIMULATION;

AGED; AGED, 80 AND OVER; ALGORITHMS; ALZHEIMER DISEASE; COGNITION DISORDERS; EYE MOVEMENTS; FEMALE; HUMANS; MALE; MILD COGNITIVE IMPAIRMENT; PHOTIC STIMULATION; PSYCHOMOTOR PERFORMANCE;

EID: 80052310447     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2011.06.027     Document Type: Article

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