Wavelet Packet Sub-band Based Classification of Alcoholic and Controlled State EEG Signals
- D. Puri, R. Ingle, P. Kachare, M. Patil, R. Awale
- Corresponding Author
- D. Puri
Available Online December 2016.
- https://doi.org/10.2991/iccasp-16.2017.82How to use a DOI?
- Electroencephalogram, wavelet packet transform, sub-band decomposition, support vector machine.
- Electro-encephalogram (EEG) is one of the most practiced signals in brain computer interface systems. Several distinct EEG patterns have been analyzed in identifying physiological and psychological states. Work presented here focuses on classification of EEG patterns for alcoholic and controlled states. Third level sub-band energy features are generated for either classes using multi-resolution wavelet packet transformation. A well-known support vector classifier is employed to segregate these features in two well defined classes. Experimental results show significant improvement over wavelet tree feature extraction. Cross-validation tests confirm the greater classification accuracy for proposed technique.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - D. Puri AU - R. Ingle AU - P. Kachare AU - M. Patil AU - R. Awale PY - 2016/12 DA - 2016/12 TI - Wavelet Packet Sub-band Based Classification of Alcoholic and Controlled State EEG Signals BT - International Conference on Communication and Signal Processing 2016 (ICCASP 2016) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/iccasp-16.2017.82 DO - https://doi.org/10.2991/iccasp-16.2017.82 ID - Puri2016/12 ER -