Information Technology Reference
In-Depth Information
Operant conditioning involves the presentation of a task in conjunction with
some form of feedback, which allows the user to develop unconscious control of the
EEG. Once the brain is conditioned, the user is able to accomplish the task without
being conscious of the EEG activity that needs to be generated (Kaplan et al. 2005 ).
Somewhere in between the two aforementioned approaches is a paradigm
referred to as evoked potentials, or event-related potentials, abbreviated as ERP.
ERP occur from perception of a user to an external stimulus or set of stimuli.
Typically, ERP can be evoked from auditory, visual or tactile stimuli producing
auditory-, visual- and somatosensory-evoked potentials, respectively. ERP are the
electrophysiological response to a single event and therefore is problematic to
detect in EEG on a single trial basis, becoming lost in the noise of ongoing brain
activity. But if a user is subjected to repeated stimulation at short intervals, the
brain
is response to each subsequent stimulus is evoked before the response to the
prior stimulus has terminated. In this case, a steady-state response is elicited, rather
than left to return to a baseline state (Regan 1989 ).
For users with healthy vision and eye movements, the steady-state visual-evoked
potential (SSVEP) is a robust paradigm for a BCI. And it has the advantage that it
does not require much training in order to be operated satisfactorily. Typically, the
user is presented with images, or simple images, on a standard computer monitor
representing actions available to perform with the BCI; these could be, for instance,
letters or geometrical
'
figures. In order to make a selection, users must simply direct
their gaze at the image corresponding to the action they would like to perform. The
images must have a pattern reversing at certain frequency. As the user
s spotlight of
attention falls over a particular image, the frequency of the pattern reversal rate can
be detected in the user
'
is EEG through basic spectral analysis. What is interesting
here is that once the target signal is detected in the EEG, it is possible to classify not
only a user
'
is choice of image, but also the extent to which the user is attending it
(Middendorf et al. 2000 ). Therefore, each target is not a simple binary switch, but
can represent an array of options depending on the user
'
'
s attention.
1.4
BCMI-Piano
The BCMI-Piano resulted from the
first aforementioned dream: Would it be pos-
sible to play a musical instrument with signals from the brain? No hands needed.
Initially, we looked into translating aspects of the EEG onto musical notes
played on a synthesiser. However, this strategy proved to be unsatisfactory. The
system did not convey the impression that one was playing a musical instrument.
The notes sounded as if they were generated randomly and the synthesised sounds
lacked the auditory quality that one would expect to hear from an acoustic musical
instrument.
In order to remediate this, we connected the system to a MIDI-enabled acoustic
piano (Fig. 1.1 ). That is, an acoustic piano that can be played by means of MIDI
signals. MIDI stands for musical instrument digital interface. It is a protocol
developed in the 1980s, which allows electronic instruments and other digital
 
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