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
Projecte final de carrera realitzat en col.laboració amb Philips Research
