Seizure detection
Various epileptic seizure detection techniques using biomedical signals: a review
... a seizure or non-seizure are these estimated values like Δ and τ from local minima and ...online seizure detection ...the seizure detector (hardware) and implemented the algo- rithm ...
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VLSI Based Efficient Epeleptic Seizure Detection System
... However, training classical SVM is solving a quadratic programming (QP) problem which is computationally complex and energy-consuming, so integrating an efficient SVM training algorithm is very important. Evolving ...
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Combination of EEG Complexity and Spectral Analysis for Epilepsy Diagnosis and Seizure Detection
... subjects (Set E). The data length of each nonoverlapping window for ApEn calculation was 512 points, and the other ApEn parameters were r = 0 and m = 1 [12]. Based on these data, ApEn was a good index for discriminating ...
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Automatic Seizure Detection Based on Nonlinear Dynamical Analysis of EEG Signals and Mutual Information
... real-time detection of seizures could significantly improve the therapeutic potentials like “closed-loop” ...to seizure detection (Ramgopal et ...real-time detection of seizures is critical to ...
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An Efficient Method for Epileptic Seizure Detection in Long Term EEG Recordings
... for seizure detection using frequency-weighted ...false detection rate ...for seizure detection method has been proposed using statistically optimal null ...known seizure ...
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Automatic Seizure Detection using Inter Quartile Range
... A new combination of statistical features and linear classifier for seizure detection is presented in this paper, which shows 100% accuracy. The use of features those quantify the dispersion characteristics ...
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A Multi Channel Fusion Based Newborn Seizure Detection
... This paper is organized as follows. Section 2 addresses each step involved in development of both the pro- posed multi-channel fusion approaches. These steps include data acquisition, preprocessing of the EEG to re- move ...
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FPGA Implementation of EEG Feature Extraction and Seizure Detection
... efficient seizure detection system to enhance the sensitivity with a low FDR by proposing a dual-stage ...continuous detection of seizure onset in epilepsy ...automatic detection of ...
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Sensitivity of Amplitude-Integrated Electroencephalography for Neonatal Seizure Detection
... neonatologists. The seizures in those records were rela- tively long ( ⬎ 1 minute) or of unspecified “high ampli- tude.” The authors speculated that the poor sensitivity for neonatal seizure detection by ...
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Time-Frequency Analysis of Heart Rate Variability for Neonatal Seizure Detection
... There are a number of automatic techniques available for detecting epileptic seizures using solely electroencephalogram (EEG), which has been the primary diagnosis tool in newborns. The electrocardiogram (ECG) has been ...
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Informed Under Sampling for Enhancing Patient Specific Epileptic Seizure Detection
... Seizure detection algorithms are divided into multiple categories which includes the classification between epileptic and non-epileptic patients, seizure episode counting and onset seizure ...
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Electroencephalography (EEG) based automatic Seizure Detection and Prediction UsingDWT
... Till now recently, seizures be situated identified only visually by an expert neurologist. Nevertheless, this method constitutes a laborious task mainly in the case of long term EEG recordings. So, automatic computer ...
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Electrocardiogram based neonatal seizure detection
... A variety of time and frequency domain heartbeat timing fea- tures were tested and measures of their ability to discriminate between classes are supplied here (ROC area and Wilcoxon rank-sum test -value, Table II). As ...
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EEG seizure detection and prediction algorithms: a survey
... along n-dimensional spaces to generate n-dimensional envelopes, which are then averaged to get the local mean. The projection direction vectors are based on spherical and polar coordinates. To sample the n-sphere, quasi- ...
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Multiresolution Analysis in EEG Signal Feature Engineering for Epileptic Seizure Detection
... Despite the fact that the wavelet domain based feature engineering is an ideal method of feature extraction and selection in EEG signal processing, it is also an effective tool for preprocessing the EEG signals which ...
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A Survey On Approaches For Epileptic Seizure Detection And Prediction
... [2]. Seizure detection can be performed effectively using deep learning ...into seizure and non seizure class by making use of ...the detection of epileptic seizures using EEG ...
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Efficient feature selection using a hybrid algorithm for the task of epileptic seizure detection
... epilepsy seizure falls into two broad categories, namely seizure detection [2] and seizure prediction ...In seizure detection, an expert system which is able to differentiate ...
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Epileptic seizure detection from EEG signals using logistic model trees
... healthy, seizure-free, and seizure) into several seg- ments based on specific time interval and then select representative samples by using OAT from each and every segment of the entire signal data of that ...
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Evolutionary coherence on EEG signals for epileptic seizure detection
... of seizure. Ictal defines the duration where seizure occurs, while preictal is before the onset of seizure and postictal is after the onset of ...
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A computer aided analysis scheme for detecting epileptic seizure from EEG data
... epileptic seizure detection algorithms have developed from several countries throughout the ...epileptic seizure from ...and seizure-free EEG signals based on the EMD and the second-order ...
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