Information Technology Reference
In-Depth Information
Although these times are lengthy in comparison to EEG response times in other
BCMI devices, what (Grierson et al.
2011
) accomplished with his system was the
ability to widen choice to a range of values. Instead of a
decision,
the meaning within the stimuli was designed to visually represent many more
choices, up to 36 in this case example. Grierson and colleagues have since
developed a suite of BCMI applications based upon the NeuroSky bluetooth
headset (Grierson et al.
2011
).
The research into ERPs also went as far as to indicate that BCMI control may not
need to rely on a subject training their brain to act accordingly to the intelligence of
a BCMI. By relying on the ability of the brain to respond to the focus of attention in
a multi-variable environment, no training was necessary as long as the user had the
ability to recognise visual events and perform the counting task. As a result of these
factors, this method for eliciting P300 for control was subsequently utilised by the
neurotechnology company g.tec in their commercial BCI system.
As previously mentioned, the ERP response to a single event is problematic to
detect on a single trial basis, as it becomes lost in the noise of ongoing brain
activity. However, if a user is subjected to repeated visual stimulation at short
intervals (at rates approximately between 5 and 30 Hz), then before the signal has
had a chance to return back to its unexcited state, the rapid introduction of the next
'
one or the other
'
flashing onset elicits another response. Further successive
flashes induce what is
known as the steady-state response in the brain
'
s visual cortex, a continuously
evoked ampli
cation of the brainwave (Regan
1989
). This removes a need for
performing numerous delayed trials as the repeated visuals are consistently pro-
viding the stimuli required for a constant potential, translated as a consistent
increased amplitude level in the associated EEG frequency.
This technique, steady-state visual-evoked potential (SSVEP), was adopted in a
BCMI system designed for a patient with locked in syndrome (Miranda et al.
2011
)
as a tool for providing recreational music making. Here, four
flashing icons were
presented on a screen, their
flashing frequencies correlating to the frequencies of
corresponding brainwaves measured in the visual cortex. The user selects an icon
simply by gazing at it, and the amplitude of the corresponding brainwave frequency
increases. Whilst EEG data are analysed constantly, the system looks for amplitude
changes within the four frequencies. The icons represent four choices, always
available to the user at the same time. These controls are in turn mapped to com-
mands within a musical engine, as well as being feedback into the display screen to
provide visual feedback to the user. The instantaneous speed of the EEG response to
the stimuli finally brought real-time explicit control to a BCMI, which required no
user or system training beyond the task of visual focusing. Please refer to Chap.
1
for
more information on this system.
As well as the selection of commands, a second dimension of control was
gathered through the level of focused gazing. This elicited a relative linear response
within the amplitude of the corresponding brainwave. This allows users to employ
proportional control methods akin to intrinsically analogue tasks such as pushing a
fader or turning a dial. This differs from previous selective, more digital tasks in
BCMIs, such as a switch or a toggle function. In this system, Miranda and
