Feature Extraction from Scalp EEG for Brain Tumor Detection using Wavelet-ICA Method

Abstract: EEG i.e. Electroencephalogram is the recording of brain activity can be used to diagnose several diseases such as seizure disorders, strokes, brain tumors and other physiological disorders.EEG is affected severely by power line noise, breathing, muscle movements, body movements, loose contact of electrodes and eye movements. Various algorithms are proposed by many researchers for removing these artifacts from EEG, extracting features and classify it with different classification techniques for efficient analysis of the brain related diseases. This paper presents ICA method for removing artifacts and wavelet transform for eliminating high frequency noises. This paper also presents feature extraction of EEG using different statistical parameters.

Keywords: Electroencephalogram, Independent component Analysis, Artificial Neural Network