The study of brain activity during specific mental states has
been explored by means of different methodologies in order to
extract discriminating features for the purpose of user recognition.
Specifically, brain activity can be recorded either by
measuring the blood flow in the brain or by measuring the neurons’
electrical activity. To the first category belong approaches
like functional magnetic resonance imaging (fMRI), which
measures the concentration of oxygenated and deoxygenated
haemoglobin in response to magnetic fields; near-infrared
spectroscopy (NIRS), which measures the concentration of
oxygenated and deoxygenated haemoglobin by means of the
reflection of infrared light by the brain cortex through the
skull; positron emission tomography (PET), which measures
neuron metabolism through the injection of a radioactive
substance in the subject. To the second category belong
approaches like magneto-encephalography (MEG), which is
sensitive to the small magnetic fields induced by the electric
currents in the brain, and electroencephalography (EEG),
which is sensitive to the electrical field generated by the
electric currents in the brain. EEG recordings are acquired with
portable and relatively inexpensive devices when compared
to the other brain imaging techniques. Specifically, signal
amplifiers with high sensitivity and high noise rejection are
used to measure the voltage fluctuations on the scalp surface,
resulting from the electric field generated by the firing of
collections of pyramidal neurons of the cortex. The EEG
amplitude of a normal subject in the awake state, recorded with
scalp electrodes, is in the range 10 – 200 μV, and a healthy
human brain has its own intrinsic rhythms falling in the range
of 0.5 − 40Hz. EEG based brain imaging techniques present
a limited spatial resolution due to the physical dimension,
in the range of several millimeters, of the surface electrodes
usually employed in the acquisition setup, which limits the
possible number of the electrodes covering the whole scalp