Estimation of Statistical Parameters of EEG Signals Using Wavelets

The Electroencephalogram (EEG) is the standard technique for investigating the brains electrical activity in different psychological and pathological states. Analysis of Electroencephalogram (EEG) signal is a challenging task due to the presence of different artifacts such as Ocular Artifacts (OA) and Electromyogram. Normally EEG signals falls in the frequency range of DC to 60 Hz and amplitude of 1-5 µv. Ocular artifacts do have the similar statistical properties of EEG signals, often interfere with EEG signal, thereby making the analysis of EEG signals more complex. In this book, Iterative soft thresholding technique was employed by using different wavelet functions, in the removal of ocular artifacts (OA) present in the EEG signal and estimated the statistical parameters of the EEG signal.

Autorentext

B. Krishna Kumar holds a Ph.D. degree in Electronics and Communication Engineering from Jawaharlal Nehru Technological University, Hyderabad, INDIA (2016). He also has a M.Tech degree in Digital Systems and Computer Electronics from Jawaharlal Nehru Technological University, Hyderabad, INDIA.