A Comparative Study between De-noising Algorithms for Non-Invasive Brain Computer Interface Applications

Brain Computer Interface provides a communication pathway between the machine and the human. Electroencephalogram (EEG) is a non-invasive technique for acquiring human brain signals. But these non-invasive signals are highly contaminated with several artefacts like Electrooculography (EOG), Electrocardiogram (ECG) etc. Generally EOG artefacts overlap the frequency of EEG signals very firmly. So the de-noising of these signals is a huge challenge to develop Brain Computer Interface based applications. This research shows a comparative study between two major timefrequency domain de-noising methods, Discrete Wavelet Transform (DWT) and Empirical Mode Decomposition (EMD)