Analysis of Extracting Distinct Functional Components of P300 using Wavelet Transform

摘要

This paper investigates P300 features extracted through wavelet transform for BCI systems. Feature extraction is one of the key issues of signal processing for P300 based brain-computer interface systems (BCI). This paper examines and highlights the significance of using wavelets in P300 based BCI systems. We also mention various methods of feature extraction from P300 signals. The analysis suggests that wavelet transform is the best-suited tool for non-stationary signals like P300 signals.