Analysis of Epileptic iEEG Data by Applying Convolutional Neural Networks to Low-Frequency Scalograms
| Autor: | Muhittin Bayram, Muhammet Ali Arserim |
|---|---|
| Přispěvatelé: | Dicle Üniversitesi, Mühendislik Fakültesi, Elektrik Elektronik Mühendisliği Bölümü, Bayram, Muhittin, Arserim, Muhammet Ali |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Brain modeling
Data modelsIntracranial electroencephalogram (iEEG) convolutional neural network (CNN) Epilepsy General Computer Science Quantitative Biology::Neurons and Cognition delta subband Entropy Convolutional neural network (CNN) Physics::Medical Physics General Engineering Electroencephalography Deep learning TK1-9971 Intracranial electroencephalogram (iEEG) epilepsy Convolutional neural networks General Materials Science Electrical engineering. Electronics. Nuclear engineering Delta subband entropy |
| Zdroj: | IEEE Access, Vol 9, Pp 162520-162529 (2021) |
| ISSN: | 2169-3536 |
| Popis: | WOS:000730450200001 In this paper, Convolutional Neural Networks (CNN) method was applied to low frequency scalograms in order to contribute to the development of diagnostic and early diagnosis systems of epileptic intracranial EEG (iEEG) signals of brain dynamics at preictal, ictal, and postictal states, and to achieve results that will be the basis for determining the pathological conditions of iEEG signals. As part of this study, iEEG data obtained from epileptic subjects were first decomposed into their subbands by discrete wavelet transformation, and then Shannon entropy was applied to these five subbands (delta, theta, alpha, beta, and gamma). The results obtained made us observe that the delta subband entropy value is lower than other subband entropy values. A low entropy value means that the data is less chaotic. A low degree of chaos means better predictability. Within this context, scalogram images of low-frequency delta subband were obtained at preictal, ictal, and postictal stages and treated with the CNN method, and consequently, a 93.33% accuracy rate was obtained. |
| Databáze: | OpenAIRE |
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