Quantitative EEG-Based Brain-Computer Interface - Quantitative EEG Analysis Methods and Clinical Applications - page 219

cated a promising perspective for real applications. However, it cannot escape from
the challenge of nonlinear and dynamic characteristics of brain systems as well,
especially in terms of information modulation. The way in which the brain
encodes/modulates the BCI code into the EEG activity varies across subjects and
changes with time. These factors pose the challenge of coadaptation as discussed in
the previous section. This suggests again that BCI system design is not just about the
algorithm and that human factors should be considered very seriously.
8.4.2 System Design for Practical Applications
For the BCI systems discussed here, many studies have been done to implement and
evaluate demonstration systems in the laboratory; however, the challenge facing the
development of practical BCI systems for real-life application is still worth empha-
sizing. According to a survey done by Mason et al. [72], the existing BCI systems
could be divided into three classes: transducers, demo systems, and assistive devices.
Among the 79 BCI groups investigated, 10 have realized assistive devices (13%), 26
have designed demonstration systems (33%), and the remaining 43 are only in the
stage of offline data analysis (54%). In other words, there is still a long way to go
before BCI systems can be put into practical use. However, as an emerging engineer-
ing research field, if it can only stay in the laboratory for scientific exploration, its
influence on human society will certainly be limited. Thus, the feasibility of creating
practical applications is a serious challenge for BCI researchers. A practical BCI sys-
tem must fully consider the user's human nature, which includes the following two
key aspects:
1. A better electrode system is needed that allows for convenient and
comfortable use. Current EEG systems use standard wet electrodes, in which
electrolytic gel is required to reduce electrode-skin interface impedance.
Using electrolytic gel is uncomfortable and inconvenient, especially if a large
number of electrodes are adopted. First of all, preparations for EEG
recording before BCI operation are time consuming. Second, problems
caused by electrode damage or bad electrode contact can occur. Third, an
electrode cap with large numbers of electrodes is uncomfortable for users to
wear and then not suitable for long-term recording. Moreover, an EEG
recording system with a high number of channels is usually quite expensive
and not portable. For all of these reasons, reducing the number of electrodes
in a BCI system is a critical issue and, currently, it has become the bottleneck
in developing an applicable BCI system. In our system, we use a
subject-specific electrode placement optimization method to achieve a high
SNR for SSVEP and SMR. Although we demonstrated the applicability of
the subject-specific positions in many online experiments, much work is still
needed to explore the stationarity of the optimized electrode positions.
Alternatively, more convenient electrode designs, for example, one that uses
dry electrodes [44, 73], are highly preferable to replace the currently used
wet electrode system.
2. Better signal recording and processing is needed to allow for stable and
reliable system performance. Compared with the environment in an EEG