A Data Mining Methodology for Event Analysis in Neurophysiological Signals
B eacute jar Javier, Martín Mario, Esposito Gennaro, Contreras Enrique, Ch aacute vez Di oacute genes, Cort eacute s Ulises, Rudom iacute n Pablo · Frontiers in artificial intelligence and applications · 2015
Methodologies for pattern extraction and analysis from neural activity data captured by simultaneous sensors, are gaining major interest due to technological advances in sensor devices. From early Electroencephalography (EEG), able to capture a few simultaneous signals, to in-vivo spinal recording, Magneto Encephalograpy (MEG) or functional Magnetic Resonance Imaging (fMRI), that capture up to hundreds of signals, the amount of data from neurophysiological experimentation to be analyzed multiplies every year.