Event related (de-)synchronization patterns in actual and imagined hand movements

Abstract

This project presents different signal processing techniques, such as Principal Component Analysis (PCA) and Common Spatial Patterns (CSP), applied to characterize the reactivity of central rhythms in the alpha and beta bands during self paced voluntary and imaginary movement. The idea is to allow people to control devices, or interact with machines by simply thinking. To do so, we monitor the brain activity using electroencephalogram (EEG) measurements which record the signals from electrodes positioned on the scalp. The objective is to use motor imagery signals to build a brain computer interface, able to learn from data analyzed before, using the properties of neural networks. The possibility of designing an intuitive communication system between a brain and a computer, available to be operated by everyone, even by people with severe motor impairments, is the main objective of this study