Automated Detection of Interictal Epileptiform Discharges from Scalp Electroencephalograms by Convolutional Neural Networks
نویسندگان
چکیده
منابع مشابه
Detection of Interictal Epileptiform Discharges in Eeg
The diagnosis of epilepsy heavily depends on the detection of epileptiform discharges in interictal EEG, the EEG in between two seizures. By visual analysis a physician wants to detect these epileptiform discharges (spikes). Due to the wide variety of morphologies of epileptiform discharges, and their similarity to waves that are part of normal EEG or to artifacts, this detection is far from st...
متن کاملInterictal Epileptiform Discharges
EEG remains the primary technique in the diagnosis, characterization, and localization of partial seizures. This review examines the significance and character of interictal epileptiform abnormailites, periodic lateralized epileptiform discharges, and ictal patterns in patients with partial epilepsy. Interictal epileptiform discharges are common and assist in the diagnosis and localization of p...
متن کاملThe BOLD response to interictal epileptiform discharges.
We studied single-event and average BOLD responses to EEG interictal epileptic discharges (IEDs) in four patients with focal epilepsy, using continuous EEG-fMRI during 80-min sessions. The detection of activated areas was performed by comparing the BOLD signal at each voxel to a model of the expected signal. Since little is known about the BOLD response to IEDs, we modeled it with the response ...
متن کاملFactors underlying scalp-EEG interictal epileptiform discharges in intractable frontal lobe epilepsy.
AIMS Scalp-EEG interictal epileptiform discharges (IEDs) may be less predictive of the outcome of frontal lobe epilepsy surgery than of temporal lobe epilepsy surgery. We identified factors associated with the location of scalp-EEG IEDs in intractable frontal lobe epilepsy. METHODS Ten factors were assessed in a retrospective review of 53 patients with either concordant (frontal lobe seizure ...
متن کاملDetection of schizophrenia patients using convolutional neural networks from brain effective connectivity maps of electroencephalogram signals
Background: Schizophrenia is a mental disorder that severely affects the perception and relations of individuals. Nowadays, this disease is diagnosed by psychiatrists based on psychiatric tests, which is highly dependent on their experience and knowledge. This study aimed to design a fully automated framework for the diagnosis of schizophrenia from electroencephalogram signals using advanced de...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Neural Systems
سال: 2020
ISSN: 0129-0657,1793-6462
DOI: 10.1142/s0129065720500306