Arun Chavan, Dr. Mahesh Kolte
In the paper, wavelet analysis is applied to EEG. The wavelet transform is used to represent essential characteristics of EEG spikes and spike wave(SSW) complex with few coefficients. Since spikes contain high frequency energy, they will be represented in particular scale localized in a small time window. The wave portion of the spike wave complex will be represented in a lower scale of WT, covering wider span of time. Thus with the proper selection of WT scales and time spans a fewer number of WT coefficients may be used to represent the SSW complexes[6].In order to reduce the false detection, we can extend the contextual information by referring to other signals such as EOG for information about eye movements, EMG (Electro Myo Gram) for information about muscle electrical activity. With this it is possible to reduce greatly the false detection of sharp transients due to artifacts.[3]
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