Computer-assisted estimation of interictal discharge burden in idiopathic generalized epilepsy

2020 ◽  
Vol 105 ◽  
pp. 106970
Author(s):  
Dominique Eden ◽  
Ewan S. Nurse ◽  
Shannon Clarke ◽  
Philippa J. Karoly ◽  
Udaya Seneviratne ◽  
...  
Keyword(s):  
Computer Assisted ◽  
Idiopathic Generalized Epilepsy ◽  
Generalized Epilepsy ◽  
Interictal Discharge

The use of computer-assisted-telephone-interviewing to diagnose seizures, epilepsy and Idiopathic Generalized Epilepsy

2010 ◽  
Vol 91 (1) ◽  
pp. 20-27 ◽  
Author(s):  
Wendyl J. D'Souza ◽  
Jim Stankovich ◽  
Terence J. O’Brien ◽  
Simon Bower ◽  
Neil Pearce ◽  
...  
Keyword(s):  
Computer Assisted ◽  
Idiopathic Generalized Epilepsy ◽  
Generalized Epilepsy

scholarly journals Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy

2019 ◽  
pp. 106556 ◽  
Author(s):  
Shannon Clarke ◽  
Philippa J. Karoly ◽  
Ewan Nurse ◽  
Udaya Seneviratne ◽  
Janelle Taylor ◽  
...  
Keyword(s):  
Computer Assisted ◽  
Idiopathic Generalized Epilepsy ◽  
Generalized Epilepsy

scholarly journals Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy

2019 ◽  
Author(s):  
Shannon Clarke ◽  
Pip Karoly ◽  
Ewan Nurse ◽  
Udaya Seneviratne ◽  
Janelle Taylor ◽  
...  
Keyword(s):  
Learning Algorithm ◽  
False Positive Rate ◽  
Detection Algorithm ◽  
Epileptic Activity ◽  
Automated Detection ◽  
Computer Assisted ◽  
Reference Standard ◽  
Idiopathic Generalized Epilepsy ◽  
Therapeutic Outcomes ◽  
Generalized Epilepsy

AbstractEpilepsy diagnosis can be costly, time-consuming and not uncommonly inaccurate. The reference standard diagnostic monitoring is continuous video-EEG monitoring, ideally capturing all events or concordant interictal discharges. Automating EEG data review would save time and resources, thus enabling more people to receive reference standard monitoring and also potentially herald a more quantitative approach to therapeutic outcomes. There is substantial research into automated detection of seizures and epileptic activity from EEG. However, automated detection software is not widely used in the clinic; and, despite numerous published algorithms, few methods have regulatory approval for detecting epileptic activity from EEG.This study reports on a deep learning algorithm for computer-assisted EEG review. Deep, convolutional neural networks were trained to detect epileptic discharges using a pre-existing dataset of over 6000 labelled events in a cohort of 103 patients with idiopathic generalized epilepsy (IGE). Patients underwent 24-hour ambulatory outpatient EEG, and all data was curated and confirmed independently by two epilepsy specialists (Seneviratne et al, 2016). The resulting automated detection algorithm was then used to review diagnostic scalp-EEG for seven patients (four with IGE and three with events mimicking seizures) to validate performance in a clinical setting.The automated detection algorithm showed state-of-the-art performance for detecting epileptic activity from clinical EEG, with mean sensitivity of >95% and corresponding mean false positive rate of 1 detection per minute. Importantly, diagnostic case studies showed that the automated detection algorithm reduced human review time by 80%-99%, without compromising event detection or diagnostic accuracy. The presented results demonstrate that computer-assisted review can increase the speed and accuracy of EEG assessment and has the potential to greatly improve therapeutic outcomes.

A New SYNGAP1 Stop Mutation in a Patient with Idiopathic Generalized Epilepsy Showing Photosensitivity and Electroencephalography Normalization after Eye Opening

2014 ◽  
Vol 45 (S 01) ◽  
Author(s):  
C. von Stülpnagel-Steinbeis ◽  
C. Funke ◽  
C. Haberl ◽  
K. Hörtnagel ◽  
J. Jüngling ◽  
...  
Keyword(s):  
Idiopathic Generalized Epilepsy ◽  
Stop Mutation ◽  
Eye Opening ◽  
Generalized Epilepsy

scholarly journals The Impact of Idiopathic Generalized Epilepsy on Executive Functions

2021 ◽  
pp. 097275312096875
Author(s):  
Haritha Koganti ◽  
Shasthara Paneyala ◽  
Harsha Sundaramurthy ◽  
Nemichandra SC ◽  
Rithvik S Kashyap ◽  
...  
Keyword(s):  
Executive Functions ◽  
Executive Dysfunction ◽  
Cross Sectional Study ◽  
Idiopathic Epilepsy ◽  
Idiopathic Generalized Epilepsy ◽  
Word Fluency ◽  
Cross Sectional ◽  
Generalized Epilepsy ◽  
Multiple Domains ◽  
The Impact

Background: Idiopathic generalized epilepsy is defined as seizures with a possible hereditary predisposition without an underlying cause or structural pathology. Assessment of executive dysfunction in idiopathic generalized epilepsies based on standard Indian battery is not available in the literature. Aims and Objectives: To assess specific executive functions affected in patients with idiopathic epilepsy and their association with various variables. Materials and Methods: Type of observational cross-sectional study, where clinical profile of all idiopathic epilepsy patients attending the neurology OPD was studied and their executive higher mental functions were assessed using the NIMHANS battery. Results: A total of 75 idiopathic generalized epilepsy patients were included in the study. Executive functions that were commonly found abnormal in our study were word fluency ( P ≤ .001), category fluency ( P < .001), verbal n-back ( P < .001), Tower of London ( p < 0.01), and Stroop test ( P < 0.01). Executive functions showed a significant correlation with age at symptom onset, duration of epilepsy, and in those with uncontrolled seizures. Conclusion: Patients of idiopathic generalized epilepsy according to the present study were found to have significant executive dysfunction in multiple domains. This necessitates the screening for executive dysfunctions, which if detected should prompt the clinician to initiate cognitive retraining.

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