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In-Depth Information
nement to
make it more practical and viable for clinical applications. For instance, the fre-
quency rate at which the images
We are aware that some aspects of the system still require further re
flash may limit using the system with people
known to have epilepsy, a possible consequence following acquired brain injury.
The time required to place the electrodes on the scalp was reduced considerable:
only three electrodes are required here. However, SSVEP-Music requires calibra-
tion to match the sensitivity of the system with the user
'
s visual cortex response to
the
flashing images. This is outside typical clinical skills and can be time-
consuming. The downside is that this calibration needs to be done before a session
begins. Although this could be overcome with training, increasing the time burden
of a clinical session is known to be a preventative factor in
uencing the uptake of
technology by the health care sector.
Nevertheless, despite all the limitations, we succeeded in providing more control
options and devolving the creative process to the user. And more importantly, we
demonstrated that it is indeed possible to build a BCMI system for a person with
locked-in syndrome to make music.
1.6
Discussion: Moving Forwards
In addition to the limitations discussed above, I am currently addressing two technical
challenges, which I believe are important to move research into BCMI forwards:
a. Discovery of meaningful musical information in brain signals for control beyond
the standard EEG rhythms.
b. Design of powerful
techniques and tools for
implementing
flexible and
sophisticated online generative music systems.
In order to address the former, I have been conducting brain scanning experi-
ments aimed at gaining a better understanding of brain correlates of music cogni-
tion, with a view on discovering patterns of brain activity suitable for BCMI
control. In the following section, I report on the results of two experiments: one on
listening imagination and another on musical tonality.
As for the second challenge, it is important to ensure that the BCMI system
offers an adequate musical repertoire or challenge to maintain the engagement of
people who may have vastly sophisticated musical experiences and tastes. I have
been looking into expanding the generative capabilities of the BCMI-Piano music
algorithm by means of constraint satisfaction programming techniques.
1.7
Active Listening Experiment
This experiment was developed with Alex Duncan, a former postgraduate research
student, and Kerry Kilborn and Ken Sharman, at University of Glasgow. The
objective of the experiment was to test the hypothesis that it is possible to detect
