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Journals / Politeknik Dergisi / 2003 / Cilt: 6 - Sayı: 2

Classification of epileptic EEG signals using neuro-fuzzy system

Epileptik EEG sinyallerinin sinirsel-bulanık sistem ile sınıflandırılması

Necaattin BARIŞÇI
SERDAR MÜLDÜR
Pages
445–449
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The classification results show that neuro fuzzy system offers best results in the case of diagnosis.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this work, epileptic and normal EEG signals recorded from 40 patients were transferred to a personel computer.
📊
Key Findings & Data:In order to do a good and rapid diagnosis, 40 patients' FFT results classified using neuro - fuzzy system.
💡
Conclusion & Impact:The classification results show that neuro fuzzy system offers best results in the case of diagnosis.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this work, epileptic and normal EEG signals recorded from 40 patients were transferred to a personel computer. The fast Fourier transform (FFT) method was applied to the recorded signal from each patient. In order to do a good and rapid diagnosis, 40 patients' FFT results classified using neuro - fuzzy system. The classification results show that neuro fuzzy system offers best results in the case of diagnosis.

Özet

Bu çalışmada 40 hastadan kaydedilen epileptik ve normal EEG işaretleri bir kişisel bilgisayara aktarılmıştır. Her bir hastadan kaydedilen EKG sinyaline, Hızlı Fourier Dönüşümü (HFD) spektral analizi uygulanmıştır. Doğru ve hızlı bir teşhis gerçekleştirebilmek için 40 hastanın HFD sonuçlan sinirsel - bulanık sistem kullanılarak sınıflandırılmıştır. Bu sınıflandırma sonucunda sinirsel - bulanık sistemin teşhise yönelik iyi sonuçlar verdiği gözlenmiştir.

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Cite This Article

BARIŞÇI, N., MÜLDÜR, S. (2003). Classification of epileptic EEG signals using neuro-fuzzy system. Politeknik Dergisi, Cilt: 6 - Sayı: 2, 445–449. https://ajindex.com/articles/307267

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