Information Technology Reference
In-Depth Information
10.2 Mapping and Digital Musical Interfaces
The pursuit of control within musical systems controlled by the brain has been at
the forefront of research ever since it was viable. Control has been a key driver in
BCMI research as within it is the ability to convey expression and communication
through music. Mapping can be likened to a key that unlocks the creative potentials
of control. Mapping allows us to translate an input signal so that it can be under-
stood and used by a musical system. Put simply, mapping is the connection of input
controls (via EEG) to an output, which in the case of a BCMI is a musical engine. In
the pursuit of enhancing user interactivity in BCMIs, mapping plays a key role in
designing creative and practical applications. Even Alvin Lucier, the
rst composer
to perform using EEG signals, had a desire for more comprehensive mappings
within his system to allow for greater musical control (Lucier
1976
).
Research into mappings and digital instruments has largely focused on gestural
control and physical interaction (Miranda and Wanderley
2006
). Goudeseune
(
2002
) presents a comprehensive framework of mapping techniques for digital
instrument design, building on the proviso that performers can think of mappings as
containing the
feel
of an instrument; how it responds to the physical control. Garnett
and Goudeseune (
1999
) refer to the results of mapping as providing
'
consistency,
continuity and coherence
, key factors in the design of musical control systems.
Clearly, different strategies for mapping in instruments driven without gestural
input, known as
integral interfaces
, are needed to develop BCMI systems (Knapp
and Cook
2005
).
Mappings can be de
'
ned based on the number of connections between the input
and output parameters; one-to-one, one-to-many and many-to-many (combinations
of one-to-one and one-to-many) (Hunt et al.
2000
). Although this framework is
useful for evaluating system design, it does not take into account the relationship of
the input control to the mapping or any codependencies or rules a mapping may rely
on. Goudeseune (
2002
) recognises the intricacy involved in mapping design,
coining the term high-dimensional interpolation (HDI) to de
ne mapping a large
number of parameters to a small number of inputs where controls can be interpo-
lated and connected using a variety of rules and techniques.
The investigation of sophisticated mappings in BCMIs, in comparison with other
contemporary digital musical instruments and interfaces, has until recently been
sti
culties in eliciting control from EEG information. On the one
hand, simple mappings that exemplify EEG control have been favoured as they suit
this purpose well. Simple mappings, such as a linear control to modulate a syn-
thesiser
ed by the dif
s pitch, have been designed to be very effective to facilitate performing and
composing with BCMIs for non-musicians (Miranda et al.
2011
). On the other
hand, new methods of EEG acquisition provide much more accurate real-time
control than was previously available, and as a result can accommodate far more
advanced mapping techniques leading to complex compositional approaches.
Eaton
'
s
The Warren
, a performance BCMI piece that will be discussed later in this
chapter, provides a useful example of complex mapping strategies.
'
