EEG Spike Detection using Continuous Wavelet Transforms

Electroencephalography is the neurophysiological measurements of the electrical activity of the brain by recording from electrodes placed on the scalp or, in some relatively rare diagnostic procedures require electrodes on or beneath the cerebral cortex. The resulting traces are known as an electroencephalogram and represent so-called brainwaves. This book is about analyzing brain waves using continuous wavelet transform. Two algorithms are used to analyze these signals. They are amplitude threshold technique and wavelet transform technique. The drawbacks in amplitude threshold technique are overcome in wavelet transform technique. Various wavelet families like biorthogonal, symlet and daubechies have been used in analyzing EEG signals using wavelets. Abnormal or sudden transients that are observed in the EEG signal are considered as spikes. They are differentiated from the normal brain waves using a threshold value. The recordings from the brain which exceed this threshold value are considered as spikes. The graphs obtained from these techniques determine the condition of the brain.

Autorentext

M. Shoukath Ali is working as Associate Professor in the Department of Electronics & Communication Engineering at Guru Nanak Institutions Technical Campus (GNITC), Hyderabad.His areas of interest are WSNs and signal processing. His Publications include 10 research articles in International Journals / conferences and a book on Mobile adhoc networks.