P A Karthick1, Hideaki Tanaka2, Hui Ming Khoo3, Jean Gotman4. 1. Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada. Electronic address: pakarthick1@gmail.com. 2. Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada; Department of Neurosurgery, Fukuoka University Hospital, Fukuoka City, Japan. 3. Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada; Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan. 4. Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.
Abstract
OBJECTIVE: We propose a system based on the first five seconds of intracerebrally recorded focal seizures to predict their evolution from focal to bilateral tonic-clonic seizure (FTC), to spread outside the onset zone but without tonic-clonic component (FS), or to a seizure remaining focal (F). METHODS: Nineteen time and frequency domain features were extracted from 39 seizures of 32 patients and were subjected to support vector machine based classification. Three prediction approaches regarding seizure evolution were (1) FTC vs FS vs F, (2) FTC vs FS or F and (3) FTC or FS vs F. RESULTS: We used 21 seizures for training. Most features had significantly different distributions in the three seizure types (p < 0.05). Eighteen seizures were used for testing. We predicted the evolution of 12 seizures in FTC vs FS vs F, 13 seizures in FTC vs FS or F and 14 seizures in FTC or FS vs F. CONCLUSION: The first five seconds of a focal seizure contains information regarding the eventual evolution of the seizure, which could be predicted in most seizures. SIGNIFICANCE: The proposed system could alert the health care team when a patient is hospitalized for intracerebral EEG and improve safety and eventually result in an implantable device.
OBJECTIVE: We propose a system based on the first five seconds of intracerebrally recorded focal seizures to predict their evolution from focal to bilateral tonic-clonic seizure (FTC), to spread outside the onset zone but without tonic-clonic component (FS), or to a seizure remaining focal (F). METHODS: Nineteen time and frequency domain features were extracted from 39 seizures of 32 patients and were subjected to support vector machine based classification. Three prediction approaches regarding seizure evolution were (1) FTC vs FS vs F, (2) FTC vs FS or F and (3) FTC or FS vs F. RESULTS: We used 21 seizures for training. Most features had significantly different distributions in the three seizure types (p < 0.05). Eighteen seizures were used for testing. We predicted the evolution of 12 seizures in FTC vs FS vs F, 13 seizures in FTC vs FS or F and 14 seizures in FTC or FS vs F. CONCLUSION: The first five seconds of a focal seizure contains information regarding the eventual evolution of the seizure, which could be predicted in most seizures. SIGNIFICANCE: The proposed system could alert the health care team when a patient is hospitalized for intracerebral EEG and improve safety and eventually result in an implantable device.
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