EEG seizure detection
Newborn EEG Seizure Detection Based on Interspike Space Distribution in the Time-Frequency Domain
... based EEG seizure detection ...between seizure and nonseizure activities. To detect spikes in the EEG, the signal is mapped into the time-frequency ...for seizure ...
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EEG seizure detection and prediction algorithms: a survey
... multi-channel EEG signal decomposition into narrow fre- quency bands that can be analyzed separately for better detectability of ...for EEG seizure detection [70], but this proposal needs fur- ...
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Electroencephalography (EEG) based automatic Seizure Detection and Prediction UsingDWT
... identify EEG seizures, there is an essential to analyses discrete time sequences of EEG ...of EEG. Another methodology to deal with the EEG seizure detection method in time ...
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EEG Signal Analysis Using Fuzzy Approximate Analysis towards Epileptic Seizure Detection
... ABSTRACT: Electroencephalogram (EEG) is recording of electrical activity of the brain which can be used to detect Epileptic Seizures. Group of Neurons when misfiring produce abnormal electrical discharge which ...
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Automatic seizure detection based on the combination of newborn multi-channel EEG and HRV information
... multi-channel EEG and single channel ECG. Two approaches for combining EEG and HRV were proposed in this article, namely feature fusion and classifier/decision fu- ...the EEG and the HRV sig- nals ...
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Epileptic Seizure Prediction Based On Features Extracted Using Wavelet Decomposition And Linear Prediction Filter
... on EEG pulse detection and interpretation to both diagnose and treat ...Fast detection of epileptic seizures means that it is enough time before it actually happens because a medication will prevent ...
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Exploring Douglas-Peucker Algorithm in the Detection of Epileptic Seizure from Multicategory EEG Signals
... of EEG signals ...the detection of epileptic ...epileptic EEG data ...large EEG data. Although most of the EEG recordings are multicat- egories in a real clinical application, most of ...
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Automatic seizure detection using three-dimensional CNN based on multi-channel EEG
... of seizure detection includes distinguishing different stages of seizures, which are generally divided into inter-ictal, pre-ictal and ictal periods ...the seizure detection procedure is ...
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Time–frequency texture descriptors of EEG signals for efficient detection of epileptic seizure
... In this work, t–f representation of EEG signals, texture descriptors, and SVM approach has been used to detect the epileptic seizure. The STFT spectrogram has been con- sidered for discrimination of the ...
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Epileptic Seizure Classification of EEG Image Using SVM
... automatic seizure detection system is an important ...the EEG images are extracted using Discrete Cosine Transform (DCT) and Discrete Wavelet Transform ...the EEG features of classes. The ...
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Alleged Cases of Vaccine Encephalopathy Rediagnosed Years Later as Dravet Syndrome
... first seizure after vaccina- tion concomitantly with a ...subsequent seizure types or intellect, are any different between those patients with Dravet syndrome whose symp- toms started within 2 days of vacci- ...
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Coherence Analysis of Epileptic Seizure and Normal EEG
... a seizure by delivering therapy or notifying a caregiver could ease the burden of ...seizures. Seizure may be defined as the phenomenon of rhythmic irregular discharge from either a specific area or the ...
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A review of developments of EEG based automatic medical support systems for epilepsy diagnosis and seizure detection
... decomposes EEG signals into different fre- quency domains. Epileptic EEG recordings can be de- tected in terms of the difference between epileptic EEG data and normal EEG data in frequency ...
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Neonatal Apneic Seizure of Occipital Lobe Origin: Continuous Video-EEG Recording
... The observational description by the attending nurse was that all of these episodes of cyanosis were accompanied by regurgitation with slow desaturation, bradypnea, apnea, and bradycardia and hypotonia, which required ...
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Short-term Seizure Outcomes in Childhood Epilepsy
... of CWE in our study appears to be similar to that of previous studies. The main limitation of this study was that we were only able to investigate short-term seizure outcomes. However, these are of interest ...
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Support Vector Machine Kernel Functions Performance Evaluation in Epileptic Seizure Detection from EEG
... epileptic seizure detection using time-domain features of ...decomposes EEG epochs with EMD and get several IMFs and selected first ...epileptic seizure detection ...
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Seizure classification in EEG signals utilizing Hilbert-Huang transform
... The work presented here is based on the results produced by the authors in [6] and [12]. This study when compared to [6] offers the possibility to track the instantaneous (local) frequency as well as the amplitude. By ...
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Epileptic seizure detection from EEG signals using logistic model trees
... perfect detection of epileptic seizure EEG signals is a complicated problem, requiring the analysis of large sets of EEG ...epileptic seizure EEG signals and achieve the ...
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Automatic Seizure Detection Based on Nonlinear Dynamical Analysis of EEG Signals and Mutual Information
... the EEG signals. The RQA of the EEG signals is used to characterize the nonlinear EEG dynamics and extract appropriate features for automatic seizure ...
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Presurgical EEG-fMRI in a complex clinical case with seizure recurrence after epilepsy surgery
... The EEG-fMRI scan was performed using a 32-channel MR-compatible EEG system (Brain Products , Munich, Germany) and a 3T MRI scanner (Siemens Trio, Erlangen, ...The EEG was first recorded outside the ...
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