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This paper presents a novel wearable biomedical Network on Chip (NoC) concept development to monitor and predict irregular brain waves as advanced sensitive portable for an electroencephalogram (EEG) analysis device. The proposed device will monitor brain’s spontaneous electrical activity in normal and abnormal situations for specific patients suffering from different types of epilepsy...
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...
Visibility graph analysis of time series became widely used as a time series analysis in the recent years. State transfer network is a network of mapping mono/multivariate time series into a network of local states based on visibility graph, it was used to study the evolutionary behavior of time series and in this study, we applied this principle to the detection of epileptic seizures. Two sets of...
The aim of this study is to estimate the clinical characteristics and treatment of epileptic seizures in children with tuberous sclerosis complex and to determine if there is a correlation between brain CT/MRI findings and evolution of epilepsy in these patients. The medical data of 11 children diagnosed with tuberous sclerosis and epileptic seizures were retrospectively studied. Brain imaging was...
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...
According to Ayurveda, a kind of herb called Brahmi has been applying in the treatment of brain and nervous system disorders, such as epilepsy, neuropathic pain, and helping people to stay calm. Brahmi is also known as the medicine that nourishes the nervous system and enriches the memorial function of the brain. The significant substances that have been studied most are Bacoside A and Bacoside B,...
Understanding pathways of neurological disorders requires extensive research on both structural and functional characteristics of the brain. Graph theoretical analysis of functional connectivity networks highlight the dynamics of communication among brain neurons. Resembling brain to a Networked Control System, describes seizure, epileptic episodes, as a response to a set of triggers. This unknown...
The most commonly used clinical tool for initial diagnosis of epilepsy is electroencephalogram (EEG). Recent advances in magnetoencephalography (MEG) technology provide a new source of information to analyze brain activities. In order to determine whether or not particular subjects' brain signals exhibit epileptic activities, epileptologists often spend considerable amount of time to review MEG recordings...
The recent introduction of functional ultrasound (fUS) based on ultrafast Doppler imaging for blood flow detection unveiled a gigantic field of applications in Neuroimaging. Its considerable sensitivity, temporal and spatial resolution enabled to image the neurovascular coupling in unprecedented situations such as olfactory stimulation or spatial representation in an awake animal. However, to date...
EEG contains immense information about the brain activity which cannot be understood completely by visual inspection. Powerful signal processing algorithms in EEG analysis can greatly assist the physicians and neurologists to extract such hidden information. It has been found that EEG being a time-varying and non-stationary signal, can be analyzed by non-linear methods. In this paper we tried to evaluate...
The electroencephalogram (EEG) is a recording of the electrical activity of the brain from the scalp. The recorded waveforms reflect the cortical electrical activity. EEG activity is very small, measured in microvolts (µV). EEG is a non-invasive method to record electrical activity of the brain. Most commonly it is used to identify the type and location of the abnormal activity in the brain during...
It is fairly established that dynamic recordings of functional activity maps can naturally and efficiently be represented by functional connectivity networks. In this article we study weighted and fully-connected brain networks, created from electroencephalographic (EEG) measurements that concern patients with focal and generalized epilepsy. We introduce a totally new methodology that has never been...
Brain signals arise as a mixture of various neural processes that occur in different spatial, frequency and temporal locations. In detection paradigms, algorithms are developed that target specific processes. In this work, we apply tensor factorisation to a set of intracranial electroencephalography data from a group of epileptic patients and factorise the data into three modes; space, time and frequency...
Localization of epileptic focus and motor regions, is presented in the paper using raw referential EEG data from database http://eeg.pl/epi of Warsaw Memorial Child Hospital. The study is carried out on two patients named CHIMIC and JANPRZ who were diagnosed with drug-resistant epilepsy and were subsequently operated. Along with EEG recordings, inter-ictal discharges, magnetic resonance imaging (MRI)...
The pre-diagnosis of diseases with computerized systems is widely used in recent years for reducing diagnosis time and ratio of misdiagnosis. In this study, a pre-diagnosis system has been proposed which separates of healthy and epileptic seizures periods. For the experiments, EEG signals acquired from healthy and epileptic individuals were used. In feature extraction stage, recurrence quantification...
Epilepsy represents a significant problem which reflects the existence of abnormal and hyper-synchronous discharges in large ensembles of neurons in brain structures. Despite, the epilepsy have been widely studied, its detection in incipient states is still in development. In order to solve this problem using EEG signals, a rigorous classification process have to be made. One-class classifiers are...
Event-related analyses of functional MRI (fMRI) typically assume that the onset and offset of neuronal activity match stimuli onset and offset, and that evoked fMRI signal changes follow the canonical haemodynamic response function (HRF). Some event types, however, may be unsuited to this approach: brief stimuli might elicit an extended neuronal response; anticipatory effects might result in activity...
‘Small-world’ neuronal networks are characterized by strong clustering in combination with short path length, and assist the progress of synchronization and conceivably seizure procreation. In this article we aim to investigate if the brain networks display ‘small-world’ features during seizures, by using graph-theoretic measures as well as scalp EEG recordings from patients with focal and generalized...
There are numerous types of mental and neurological disorder where the electroencephalogram (EEG) data size is too long and requires a long time to observe the data by clinician. EEG waveform may contain valuable and useful information about the different states of the brain. Since biological signal is highly random in both time and frequency domain. Thus the computerized analysis is necessary. Being...
Focal brain cooling is under investigation in clinical trials of drug resistant epilepsy. This method has been studied intensively in rodents, but more evidence from large animal studies is required. To provide evidence that focal brain cooling is a safe and effective therapeutic intervention for intractable focal epilepsy, we investigated the placement of a newly-developed cooling device over the...
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