There are a number of brain signal features that
can be used in BCls. For example, P300 as used in
studies such as [11][12] presents visual stimuli to the
participant using flashing imagery. The P300
potential is a positive deflection seen in ongoing EEG
signal with a latency of 250ms to 500ms post
stimulus. The P300 stimulus is often elicited using
the oddball paradigm which presents sequences of
repetitive visual stimuli to the BCI user and by
randomly presenting a divergent stimulus among the
repetitive stimulus to the user, a P300 potential can be
elicited. Although high accuracies (>90%) can be
achieved with its use and low requirement for user
training, the inherent nature of flashing imagery can
cause some visual fatigue for users of P300 VEPs.
Steady State Visual Evoked Potentials
(SSVEP) as used in [13][14] also makes use of
flashing imagery to evoke visual potentials which are
readable from the EEG. SSVEP works by presenting
images to the user which flash at different but fixed
frequencies. It is the frequency of the individual
flashing items which produces recognisable
properties in the ongoing EEG signal. SSVEP also
provides high system accuracies (>90%) and can be
used without training but SSVEP can also cause
visual fatigue to the user, so its use for video games
may not be fully justified in an already visually rich
environment.
m YEP uses moving imagery to elicit a response
from the dorsal pathway of the brain [15][16] which
provides a more visually pleasing and less fatiguing
method of producing stimuli than other VEPs such as
P300 and SSVEP. An mVEP response is composed
of three main peaks post stimulus namely the PI 00 -
a positive peak observed lOOms after stimulus, the
N200 negative going peak 200ms following stimulus
presentation and the P300 positive going peak
observed in the ongoing EEG signal around 240ms
post stimulus. The brief motion of visual stimuli
generates neural activations in the Medial Superior
Temporal (MST) area of the brain which forms part
of the cerebral cortex in the dorsal stream. The
detection of motion takes place primarily in the
Middle Temporal (MT) area of the brain.
In a previous study [17] we investigated how
m YEP classification accuracy was affected by
increasing visual complexity using a rudimentary 3D
based game presentation that did not utilise high
fidelity graphics. In this study however, we have used
commercially available video games that cover five
different generations of game consoles. The games
chosen represent the state of the art of each games
The 20th International Conference on Computer Games
respective hardware technologies and era of graphical
technology. Each of the games used were chosen
according to their graphical maturity and gradually
increased in graphic complexity. Also, the games
presented cover a range of genres such as arcade, 2D
platform, 3D platform, racing simulation and first
person shooter to ensure adequate coverage of
gameplay mechanics and dynamics [18][19].
Section 2 provides details on the methodology
for the study. Section 3 is the data analysis section.
Section 4 presents the results of the study. Section 5
provides a discussion and section 6 concludes the
paper.