The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
EEG Signal Classification Using Wavelet Feature Extraction and Neural Networks
Abstract
Decision support systems have been utilised since 1960, providing physicians with fast and accurate means towards more accurate diagnoses and increased tolerance when handling missing or incomplete data. This paper describes the application of neural network models for classification of electroencephalogram (EEG) signals. Decision making was performed in two stages: initially, a feature extraction scheme using the wavelet transform (WT) has been applied and then a learning-based algorithm classifier performed the classification. The performance of the neural model was evaluated in terms of training performance and classification accuracies and the results confirmed that the proposed scheme has potential in classifying the EEG signals
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Citations
Cites
Analysis of EEG records in an epileptic patient using wavelet transform
Adeli, H., Zhou, Z., & Dadmehr, N. (2003) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00340-0 · Cited by 1,154
Neural classification of lung sounds using wavelet coefficients
Kandaswamy, A., Kumar, C. S., Ramanathan, R. P., Jayaraman, S., & Malmurugan, N. (2004) · Computers in Biology and Medicine · doi:10.1016/s0010-4825(03)00092-1 · Cited by 370
Automatic recognition of alertness level from EEG by using neural network and wavelet coefficients
SUBASI, A. (2005) · Expert Systems with Applications · doi:10.1016/j.eswa.2004.12.027 · Cited by 289
Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG
Petrosian, A., Prokhorov, D., Homan, R., Dasheiff, R., & Wunsch, D. (2000) · Neurocomputing · doi:10.1016/s0925-2312(99)00126-5 · Cited by 269
Detection of Seizure Activity in EEG by an Artificial Neural Network: A Preliminary Study
Pradhan, N., Puthusserypady, S. K., & Arunodaya, G. R. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0022 · Cited by 143
Güler, İ., & Übeylı, E. D. (2004) · Expert Systems with Applications · doi:10.1016/j.eswa.2004.05.001 · Cited by 110
An Adaptive Structure Neural Networks with Application to EEG Automatic Seizure Detection
Weng, W., & Khorasani, K. (1996) · Neural Networks · doi:10.1016/0893-6080(96)00032-9 · Cited by 107
Cited by
Guo, L., Rivero, D., Dorado, J., Munteanu, C. R., & Pazos, A. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.02.118 · Cited by 271
Neural Decoding of EEG Signals with Machine Learning: A Systematic Review
Saeidi, M., Karwowski, W., Farahani, F. V., Fiok, K., Taiar, R., Hancock, P. A., & Al-Juaid, A. (2021) · Brain Sciences · doi:10.3390/brainsci11111525 · Cited by 258
Epileptic seizures detection in EEG using DWT-based ApEn and artificial neural network
Kumar, Y., Dewal, M. L., & Anand, R. S. (2014) · Signal, Image and Video Processing · doi:10.1007/s11760-012-0362-9 · Cited by 253
Song, Y., & Liò, P. (2010) · Journal of Biomedical Science and Engineering · doi:10.4236/jbise.2010.36078 · Cited by 191
Metadata
- Authors
- Jahankhani, P., Kodogiannis, V., & Revett, K.
- Venue
- IEEE John Vincent Atanasoff 2006 International Symposium on Modern Computing (JVA'06)
- Publisher
- IEEE
- Published
- 2006-10
- Pages
- 120-124
- OpenAlex
- W2098994855
- Cited by
- 313
- References
- 7
- FWCI
- 13.72
- Type
- conference paper
- Language
- en
- Open access
- closed
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