Back to Search
Start Over
Spectral information of EEG signals with respect to epilepsy classification
- Source :
- EURASIP Journal on Advances in Signal Processing, Vol 2019, Iss 1, Pp 1-17 (2019)
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- Background The spectral information of the EEG signal with respect to epilepsy is examined in this study. Method In order to assess the impact of the alternative definitions of the frequency sub-bands that are analysed, a number of spectral thresholds are defined and the respective frequency sub-band combinations are generated. For each of these frequency sub-band combination, the EEG signal is analysed and a vector of spectral characteristics is defined. Based on this feature vector, a classification schema is used to measure the appropriateness of the specific frequency sub-band combination, in terms of epileptic EEG classification accuracy. Results The obtained results indicate that additional frequency band analysis is beneficial towards epilepsy detection. Conclusions This work includes the first systematic assessment of the impact of the frequency sub-bands to the epileptic EEG classification accuracy, and the obtained results revealed several frequency sub-band combinations that achieve high classification accuracy and have never been reported in the literature before.
- Subjects :
- Computer science
Frequency band
Feature vector
Physics::Medical Physics
EEG frequency sub-bands
lcsh:TK7800-8360
02 engineering and technology
Electroencephalography
lcsh:Telecommunication
Epilepsy
lcsh:TK5101-6720
0202 electrical engineering, electronic engineering, information engineering
medicine
EEG signal processing
Quantitative Biology::Neurons and Cognition
medicine.diagnostic_test
business.industry
lcsh:Electronics
020206 networking & telecommunications
Pattern recognition
medicine.disease
020201 artificial intelligence & image processing
Artificial intelligence
EEG spectral analysis
business
Subjects
Details
- ISSN :
- 16876180
- Volume :
- 2019
- Database :
- OpenAIRE
- Journal :
- EURASIP Journal on Advances in Signal Processing
- Accession number :
- edsair.doi.dedup.....b4b7bbf71b673b853427fccd92143515