Epilepsy detection from EEG signals: a review.
1a School of Electrical Engineering , VIT , Vellore , India.
Journal of Medical Engineering & Technology
|November 23, 2018
Summary
This review summarizes over 100 studies on detecting epileptic seizures using electroencephalography (EEG). It highlights the need for varied pattern recognition techniques due to differing EEG data characteristics for accurate epilepsy diagnosis.
Area of Science:
- Neurology
- Biomedical Engineering
- Signal Processing
Background:
- Epileptic seizure detection is crucial for automated diagnosis systems.
- Extensive research exists, making a comprehensive review challenging.
- Existing literature focuses on identifying epileptic seizures from electroencephalography (EEG) data.
Purpose of the Study:
- To review and synthesize techniques for epileptic seizure detection.
- To analyze over 100 research papers on EEG-based seizure identification.
- To identify the challenges and requirements for effective seizure detection methods.
Main Methods:
- Systematic literature review of over 100 research papers.
- Analysis of pattern recognition techniques for epileptic seizure detection.
- Examination of EEG dataset characteristics and their impact on detection.
Main Results:
- Epileptic seizure detection research spans several decades.
- A wide array of pattern recognition techniques are employed.
- The effectiveness of these techniques varies based on EEG data characteristics.
Conclusions:
- Accurate epileptic seizure detection requires tailored pattern recognition approaches.
- Understanding EEG data variability is key to improving automated diagnosis.
- Further research is needed to develop robust and adaptable seizure detection systems.
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