BACKGROUND: Epilepsy is one of the most common neurological disorders approximately one in every 100 people worldwide are suffering from it. Uncontrolled epilepsy poses a significant burden to society due to associated healthcare cost to treat and co...
Medical & biological engineering & computing
Aug 22, 2015
In this paper, a novel hierarchical multi-class SVM (H-MSVM) with extreme learning machine (ELM) as kernel is proposed to classify electroencephalogram (EEG) signals for epileptic seizure detection. A clinical EEG benchmark dataset having five classe...
Management of drug resistant focal epilepsy would be greatly assisted by a reliable warning system capable of alerting patients prior to seizures to allow the patient to adjust activities or medication. Such a system requires successful identificatio...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 8, 2015
This paper presents a novel method for feature extraction from electroencephalogram (EEG) signals using empirical mode decomposition (EMD). Its use is motivated by the fact that the EMD gives an effective time-frequency analysis of nonstationary sign...
Focal cortical dysplasia (FCD) is the most common cause of pediatric epilepsy and the third most common lesion in adults with treatment-resistant epilepsy. Advances in MRI have revolutionized the diagnosis of FCD, resulting in higher success rates fo...
The epilepsies are a heterogeneous group of neurological disorders and syndromes characterised by recurrent, involuntary, paroxysmal seizure activity, which is often associated with a clinicoelectrical correlate on the electroencephalogram. The diagn...
IEEE journal of biomedical and health informatics
Jan 6, 2015
The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalography (EEG) signals based on complex classifiers. To carry out this study, first the features of EEG data are extracted using a dual-tree complex wave...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jun 4, 2014
OBJECTIVE: Prediction of epileptic seizures can improve the living conditions for refractory epilepsy patients. We aimed to improve sensitivity and specificity of prediction methods, and to reduce the number of false alarms.
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Dec 25, 2025
For patients with MRI-negative drug-resistant epilepsy, noninvasive localization of targets for transcranial electrical stimulation (tES) remains a clinical challenge. This study proposes a novel target localization approach that integrates electroen...
Anti-seizure medications (ASMs) are often prescribed using a trial-and-error approach with a similar sequence for many patients. Comparative effectiveness data beyond the first ASM prescription are limited. Artificial intelligence can automatically e...
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