A low complexity seizure prediction algorithm

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2011, Pages 1640-1643

  Brown, Michael J ^a   Netoff, Theoden ^a   Parhi, Keshab K ^a  

^a University of Minnesota   (United States)

Author keywords

Epilepsy; Feature Selection; Implantable device; Seizure Prediction; Support Vector Machine (SVM)

Indexed keywords

AVERAGE SENSITIVITIES; COMPLEXITY REDUCTION; COMPUTATIONAL COMPLEXITY REDUCTIONS; EPILEPSY; EPILEPTIC PATIENTS; FALSE ALARMS; FALSE POSITIVE; FALSE POSITIVE RATES; HIGH SENSITIVITY; IMPLANTABLE DEVICES; IMPLANTABLE MEDICAL DEVICES; LOW COMPLEXITY; ORDERS OF MAGNITUDE; REDUCED COMPLEXITY; SEIZURE PREDICTION; SUPPORT VECTOR; TIME SPENT;

ALARM SYSTEMS; ALGORITHMS; BIOMEDICAL ENGINEERING; ERRORS; FEATURE EXTRACTION; FORECASTING; IMPLANTS (SURGICAL); SUPPORT VECTOR MACHINES;

COMPUTATIONAL COMPLEXITY;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; ELECTROENCEPHALOGRAPHY; HUMAN; METHODOLOGY; REPRODUCIBILITY; SEIZURE; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; DIAGNOSIS, COMPUTER-ASSISTED; ELECTROENCEPHALOGRAPHY; HUMANS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SEIZURES; SENSITIVITY AND SPECIFICITY;

EID: 84862244583     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2011.6090473     Document Type: Conference Paper

References (9)

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9. L. Chisci, et al., "Real-time Epileptic Seizure Prediction using AR Models and Support Vector Machines," IEEE Transactions on Biomedical Engineering, pp. 1124-1132 Feb 2010.