Analysis of Signal Processing Algorithms for Bio-Medical Applications

Abstract

Epilepsy is a burdensome brain disorder, in which heavy seizures will happen again and again. Sudden explosion of electrical activity during the seizures will create a blackout for patients and it will break the body equilibrium, so patients may fall down. Epilepsy affects a large population around the globe. It may begin at any age and last for generations. It can be controlled by the surgical removal of the brain region where the epilepsy has affected. The complicated nature of the brain makes this surgery difficult and problematic. Many risks are associated with this surgery such as memory problems, language problems etc. Thus, the early diagnosis of seizures is crucial. In this paper,the authors have been analysed the techniques to process the ElectroEncephaloGram(EEG) Signals. The signals can be denoised with the help of wavelet denoising method that can be applied to different stages of EEG.In this paper, the Discrete
wavelet transform (DWT) Multi-channel Singular Spectrum Analysis(MCSSA) are the techniques that can helps for the removal of artifacts of EEG signals.