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On predicting epileptic seizures from intracranial electroencephalography
Biomedical Engineering Letters ; (4): 1-5, 2017.
Article in English | WPRIM | ID: wpr-645474
ABSTRACT
This study investigates the sensitivity and specificity of predicting epileptic seizures from intracranial electroencephalography (iEEG). A monitoring system is studied to generate an alarm upon detecting a precursor of an epileptic seizure. The iEEG traces of ten patients suffering from medically intractable epilepsy were used to build a prediction model. From the iEEG recording of each patient, power spectral densities were calculated and classified using support vector machines. The prediction results varied across patients. For seven patients, seizures were predicted with 100% sensitivity without any false alarms. One patient showed good sensitivity but lower specificity, and the other two patients showed lower sensitivity and specificity. Predictive analytics based on the spectral feature of iEEG performs well for some patients but not all. This result highlights the need for patient-specific prediction models and algorithms.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Seizures / Sensitivity and Specificity / Electroencephalography / Epilepsy / Support Vector Machine / Drug Resistant Epilepsy / Electrocorticography Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Biomedical Engineering Letters Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Seizures / Sensitivity and Specificity / Electroencephalography / Epilepsy / Support Vector Machine / Drug Resistant Epilepsy / Electrocorticography Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: Biomedical Engineering Letters Year: 2017 Type: Article