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Temporal information: Such features would describe how the relevant signal
varies with time. In practice, this means using the EEG signals values at different
time points or in different time windows.
￿
Note that these three sources of information are not the only ones, and alter-
natives can be used (see Sect. 7.5 ). However, they are by far the most used one,
and, at least so far, the most ef
cation performances. It
should be mentioned that so far, nobody managed to discover nor to design a set of
features that would work for all types of BCI. As a consequence, different kinds of
BCI currently use different sources of information. Notably, BCI based on oscil-
latory activity (e.g., BCI based on motor imagery) mostly need and use the spectral
and spatial information whereas BCI based on ERP (e.g., BCI based on the P300)
mostly need and use the temporal and spatial information. The next sections detail
the corresponding tools for these two categories of BCI.
cient ones in terms of classi
7.3
EEG Signal-processing Tools for BCI Based on Oscillatory
Activity
BCI based on oscillatory activity are BCI that use mental states which lead to
changes in the oscillatory components of EEG signals, i.e., that lead to change in
the power of EEG signals in some frequency bands. Increase of EEG signal power
in a given frequency band is called an event-related synchronization (ERS),
whereas a decrease of EEG signal power is called an event-related desynchroni-
zation (ERD) (Pfurtscheller and da Silva 1999 ). BCI based on oscillatory activity
notably includes motor imagery-based BCI (Pfurtscheller and Neuper 2001 ),
steady-state visual evoked potentials (SSVEP)-based BCI (Vialatte et al. 2010 )as
well as BCI based on various cognitive imagery tasks such as mental calculation,
mental geometric
figure rotation, mental word generation, etc. (Friedrich et al.
2012 ; Mill
n et al. 2002 ). As an example, imagination of a left hand movement
leads to a contralateral ERD in the motor cortex (i.e., in the right motor cortex for
left hand movement) in the
á
μ
and
β
bands during movement imagination, and to an
ERS in the
band (a.k.a., beta rebound) just after the movement imagination
ending (Pfurtscheller and da Silva 1999 ). This section
β
first describes a basic design
for oscillatory activity-based BCI. Then, due to the limitations exhibited by this
design, it exposes more advanced designs based on multiple EEG channels. Finally,
it presents a key tool to design such BCIs: the common spatial pattern (CSP)
algorithm, as well as some of its variants.
7.3.1 Basic Design for an Oscillatory Activity-based BCI
Oscillatory activity-based BCI are based on change in power in some frequency
bands, in some speci
c brain areas. As such, they naturally need to exploit both the
spatial and spectral information. As an example, a basic design for a motor-imagery
 
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