Research Article
Wavelet Analysis of Electrical Signals from Brain: The Electroencephalogram
@INPROCEEDINGS{10.1007/978-3-642-37949-9_24, author={Rohtash Dhiman and Priyanka and J. Saini}, title={Wavelet Analysis of Electrical Signals from Brain: The Electroencephalogram}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 9th International Conference, QShine 2013, Greader Noida, India, January 11-12, 2013, Revised Selected Papers}, proceedings_a={QSHINE}, year={2013}, month={7}, keywords={Electroencephalogram (EEG) Wavelet transform (WT) Wavelet Packet decomposition (WPD)}, doi={10.1007/978-3-642-37949-9_24} }- Rohtash Dhiman
Priyanka
J. Saini
Year: 2013
Wavelet Analysis of Electrical Signals from Brain: The Electroencephalogram
QSHINE
Springer
DOI: 10.1007/978-3-642-37949-9_24
Abstract
The Electroencephalogram (EEG) is a measure of neural activity and is used to study cognitive processes, physiology, and complex brain dynamics. The analysis and processing of EEG data and to extract information from it, is a difficult task. The EEG signals are non-stationary signals. So, only transformation of these signals from time to frequency domain does not serve the purpose, it is required to know the time domain information too associated with the frequency domain information. Wavelet transform is one such tool being used recently for such analysis of non-stationary signals like EEG. In this paper, wavelet packet decomposition of EEG signals is presented. Feature extraction from EEG signal is also introduced in this paper.
