Comparing a supervised and an unsupervised classification method for burst detection in neonatal EEG

Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Volumn , Issue , 2008, Pages 3836-3839

  Lofhede J ^a   Degerman, J ^b   Lofgren N ^a   Thordstein, M ^d   Flisberg, A ^c   Kjellmer, I ^c   Lindecrantz, K ^a  

^a UNIVERSITY OF BORÅS   (Sweden)

^b CHALMERS UNIVERSITY OF TECHNOLOGY   (Sweden)

^c QUEEN SILVIA CHILDREN'S HOSPITAL   (Sweden)

^d SAHLGRENSKA UNIVERSITY HOSPITAL   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

HIDDEN MARKOV MODELS; SUPPORT VECTOR MACHINES;

AREA UNDER THE CURVES; BURST DETECTION; FULL TERM INFANTS; GOLD STANDARDS; RECEIVER OPERATING CHARACTERISTIC CURVES; SUPERVISED TRAININGS; UNSUPERVISED CLASSIFICATION; VISUAL INSPECTION;

BIOMEDICAL SIGNAL PROCESSING;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; CLASSIFICATION; ELECTROENCEPHALOGRAPHY; HUMAN; METHODOLOGY; NEWBORN; PHYSIOLOGY; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL; STATISTICS; THEORETICAL MODEL;

ALGORITHMS; ELECTROENCEPHALOGRAPHY; HUMANS; INFANT, NEWBORN; MARKOV CHAINS; MODELS, STATISTICAL; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; PROBABILITY; REPRODUCIBILITY OF RESULTS; ROC CURVE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 61849126870     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/iembs.2008.4650046     Document Type: Conference Paper

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