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Epilepsy is a common neural disorder disease; about 1.7% of the global population has epilepsy. Most patients take antiepileptic drugs to reduce their seizures. Among them, nearly one-third of the patients are drug-resistant epilepsy. The alternative treatment is the resection surgery of removing the epileptogenic zone. However, all above patients will still have some seizures, which will influence...
Accurate localization of brain regions responsible for language and cognitive functions in Epilepsy patients should be carefully determined prior to surgery. Electrocorticography (ECoG)-based Real Time Functional Mapping (RTFM) has been shown to be a safer alternative to the electrical cortical stimulation mapping (ESM), which is currently the clinical/gold standard. Conventional methods for analyzing...
Brain machine interfacing (BMI) needs continuous analyses of ongoing brain activity. For a successful interaction, related brain activities and events should be reliably detected; using various approaches including machine learning techniques. To this end, a variety of characteristic signal features as well as different types of classifiers can be used. One possible application of such an interaction...
Epilepsy is the third most commonly diagnosed neurological disorder. For drug-resistant patients, epilepsy surgery is the only option. The outcome of epilepsy surgery largely depends on an accurate mapping of epileptogenic zone. In clinic, this is done with subdural electrode array to monitor the Electrocorticography (ECoG) with a disappointing low spatial resolution of ∼ 1cm. As a result, the cure...
Epilepsy is defined as a collection of symptoms and clinical signs are emerging due to intermittent brain dysfunction, which occur due to loose or excessive abnormal electrical discharges of neurons in paroxysmal with various etiologies. In this article the implemented software detection of disease epilepsy, characteristics which will represent in the detection of epilepsy and not epilepsy are from...
Autism Spectrum Disorder(ASD) is a collection of heterogeneous disorders with prevalent cognitive and behavioral abnormalities. ASD is generally considered a life-long disability occurring as a stand-alone disorder but it occurs with possible co-morbid conditions such as Attention Deficit Hyperactivity Disorder (ADHD), epilepsy, Obsessive-Compulsive Disorder (OCD), Anxiety etc., Electroencephalography...
Epileptic seizure source identification involves neurologists combing through a substantial amount of data manually, which sometimes takes weeks per patient. This paper presents a methodology for minimizing the amount of data a neurologist has to analyze to identify the seizure focus. The method keeps the neurologist as the final decision maker and aids in the decision making process. It has to be...
Seizures affect a significant portion of the world's population and while a small proportion of the seizures are easy to detect, the vast majority are subtle enough to require the expertise of a neurologist. In this paper, we present a multifaceted computational approach to detecting the presence and locality of a seizure using Electroencephalography (EEG) signals. We test the proposed approach using...
Epilepsy is the fourth most frequent neurological disorder. Epileptic seizures are the result of temporary electrical disturbances in the brain. This disorder can be diagnosed by electroencephalograms (EEG). Accordingly, data mining supported by machine learning (ML) methods can be used to find patterns in EEG and to build classifiers. However, the presence of physiological abnormalities is considered...
In this paper, the need of novel methods to extract diagnostic information from the Electroencephalographic (EEG) recordings of epileptic patients was addressed. A novel method, based on Wavelet Coherence (WC) between EEG signals and Hierarchical Clustering (HC), was proposed to estimate the EEG network connectivity density in Childhood Absence Epilepsy (CAE) patients. The EEG recordings of four patients...
Epilepsy or recurrent seizures is one of the most common non communicable neurological disorder that is prevalent in today's world population are sudden outburst of excess electrical activity of the neurons. Epilepsy can be detected from Electroencephalogram (EEG) as EEG captures and presents the electrical activity of the brain. Non-invasive EEG or scalp EEG is generally used where electrodes are...
The records of scalp electroencephalogram (EEG) give many features of the epileptic region and its functionality. The process records using independent component analysis (ICA) will give enough information to the epileptologist, to go ahead with further investigation and decision for surgery. This paper presents the analysis of interictal high frequency events of a subject of Warsaw Memorial Child...
Developing a Brain-Computer Interface (BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for patients. Because of the nonstationary nature of EEG signals, normal and seizure patterns vary across different patients. Thus, finding a group of manually extracted features...
Epilepsy is a common neural disorder disease; about 1.7% of the global population has epilepsy. Most patients use antiepileptic drugs to reduce their seizures. Among them, nearly one-third of the patients are drug-resistant epilepsy. The alternative treatment is the resection surgery of removing the epileptogenic zone. However, all above patients will still have some seizures, which will influence...
This work introduces an algorithm for localization of the seizure onset zone (SOZ) of epileptic patients based on electrocorticography (ECoG) recordings. The algorithm represents the set of electrodes using a directed graph in which nodes correspond to recording electrodes, while the edge weights are the pair-wise causal influence. This causal influence is quantified by estimating the pair-wise directed...
This paper presents a novel patient-specific algorithm for prediction of seizures in epileptic patients. Spectral power features, including relative spectral powers and spectral power ratios, and cross correlation coefficients between all pairs of electrodes, are extracted as two independent feature sets. Both feature sets are selected independently in a patient-specific manner by classification and...
Determination of seizure origin is often challenging due to the rapid speed at which electrical activity propagates throughout the brain. The Directed Transfer Function (DTF) has been proposed and validated as a quantitative approach to determine the flow of seizure activity. In this work, outflow and inflow features are extracted from the DTF matrix and used as inputs to a Kmeans unsupervised clustering...
epilepsy is a neurological disease with the feature of repeated seizures. The probability to predict upcoming seizures is an issue that attracts both researchers and clinicians. Meanwhile, the directed transfer function (DTF) analysis as mechanism for feature extraction in the intracranial electroencephalographic (iEEG) recordings applied to epileptic prediction could reflect the dynamics changes...
In this study we investigated how directed functional connectivity can be used to localize the seizure onset zone (SOZ) from ictal intracranial EEG (iEEG) recordings. First, simulations were conducted to investigate the performance of two directed functional connectivity measures, the Adaptive Directed Transfer Function (ADTF) and the Adaptive Partial Directed Coherence (APDC), in combinations with...
Deep brain stimulation (DBS) shows promises in the treatment of refractory epilepsy. Due to the complex causes of epilepsy, the mechanisms of DBS are still unclear. Depolarization block caused by the persistent excitation of neurons may be one of the possible mechanisms. To test the hypothesis, 4-aminopyridine (4-AP) was injected in rat hippocampal CA1 region in-vivo to induce epileptiform activity...
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