Automated detection of videotaped neonatal seizures based on motion segmentation methods

Clinical Neurophysiology

Volumn 117, Issue 7, 2006, Pages 1585-1594

  Karayiannis, Nicolaos B ^a   Tao, Guozhi ^a   Frost Jr , James D ^b   Wise, Merrill S ^b   Hrachovy, Richard A ^b,c   Mizrahi, Eli M ^b  

^a UNIVERSITY OF HOUSTON   (United States)

^b BAYLOR COLLEGE OF MEDICINE   (United States)

^c MICHAEL E DEBAKEY VETERANS AFFAIRS MEDICAL CENTER   (United States)

Author keywords

Clustering; Motion segmentation; Motion strength signal; Neonatal seizure; Optical flow; Quantitative feature; Velocity field; Video recording

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOANALYSIS; AUTOMATION; BODY MOVEMENT; CONTROLLED STUDY; FOCAL EPILEPSY; HUMAN; MAJOR CLINICAL STUDY; MEDICAL DECISION MAKING; METHODOLOGY; MODEL; MYOCLONUS SEIZURE; NEWBORN; PHYSICIAN; PRIORITY JOURNAL; RANDOMIZATION; RELIABILITY; SENSITIVITY AND SPECIFICITY; TRAINING; VELOCITY; VIDEORECORDING;

CLUSTER ANALYSIS; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; INFANT; MOTION; MOVEMENT; NEURAL NETWORKS (COMPUTER); SEIZURES; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS; VIDEOTAPE RECORDING;

EID: 33745379447     PISSN: 13882457     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.clinph.2005.12.030     Document Type: Article

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