Search results for "Scalp electroencephalogram"

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An Information-Theoretic Framework to Map the Spatiotemporal Dynamics of the Scalp Electroencephalogram

2016

We present the first application of the emerging framework of information dynamics to the characterization of the electroencephalography (EEG) activity. The framework provides entropy-based measures of information storage (self entropy, SE) and information transfer (joint transfer entropy (TE) and partial TE), which are applied here to detect complex dynamics of individual EEG sensors and causal interactions between different sensors. The measures are implemented according to a model-free and fully multivariate formulation of the framework, allowing the detection of nonlinear dynamics and direct links. Moreover, to deal with the issue of volume conduction, a compensation for instantaneous e…

AdultMaleInformation transferEntropyComputation0206 medical engineeringInformation TheoryBiomedical Engineering02 engineering and technologyScalp electroencephalogramElectroencephalographyMachine learningcomputer.software_genreEEG propagationYoung Adult03 medical and health sciences0302 clinical medicinevolume conductionmedicineHumansCausal connectivitytransfer entropy (TE)MathematicsBrain MappingScalpmedicine.diagnostic_testbusiness.industryBrainElectroencephalographySignal Processing Computer-AssistedPattern recognitioncomplex dynamic020601 biomedical engineeringmultivariate time series analysiComplex dynamicsNonlinear systemSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaFemaleentropy estimationTransfer entropyArtificial intelligenceInformation dynamicsbusinesscomputer030217 neurology & neurosurgeryIEEE Transactions on Biomedical Engineering
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One Dimensional Convolutional Neural Networks for Seizure Onset Detection Using Long-term Scalp and Intracranial EEG

2021

Epileptic seizure detection using scalp electroencephalogram (sEEG) and intracranial electroencephalogram (iEEG) has attracted widespread attention in recent two decades. The accurate and rapid detection of seizures not only reflects the efficiency of the algorithm, but also greatly reduces the burden of manual detection during long-term electroencephalogram (EEG) recording. In this work, a stacked one-dimensional convolutional neural network (1D-CNN) model combined with a random selection and data augmentation (RS-DA) strategy is proposed for seizure onset detection. Firstly, we segmented the long-term EEG signals using 2-sec sliding windows. Then, the 2-sec interictal and ictal segments w…

intracranial electroencephalogram (iEEG)convolutional neural networks (CNN).signaalinkäsittelyscalp electroencephalogram (sEEG)epilepsyseizure detectionsignaalianalyysineuroverkotEEGepilepsia
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