![](bg8.png)
R-square criteria, the number of necessary clusters
to achieve 80% of the total variability retain by the
clusters is 12. Since the sample of volunteers was
from the same population, this kind of conclusions
are very natural. So the next step will consist in
obtain information about handicapped people. In
fact, if the clusters of subjects could be defined then
it should be interesting to work with supervised
classification in which the best command mode
would be the class.
6 CONCLUSIONS AND FUTURE
WORK
Although many Intelligent Wheelchair prototypes
are being developed in several research projects
around the world, the adaptation of user interfaces to
each specific patient is an often neglected research
topic. Typically, the interfaces are very rigid and
adapted to a single user or user group. Intellwheels
project is aiming at developing a new concept of
Intelligent Wheelchair controlled using high-level
commands processed by a multimodal interface.
However, in order to fully control the wheelchair,
users must have a wheelchair interface adapted to
their characteristics. In order to collect the
characteristics of individuals it is important to have
variables that can produce a user profile. The first
stage must be a statistical analysis to extract
knowledge of user and the surrounding. The second
stage must be a supervised classification to use
Machine Learning algorithms in order to construct a
model for automatic classification of new cases.
This paper mainly refers to the proposal of a set of
tasks for extracting the required information for
generating user profiles. A preliminary study has
been done with several voluntaries, enabling to test
the proposed methodology before going to the field
and acquiring information with disabled individuals.
In fact, this will be the next step for future work. The
test set presented in this paper will be tested by a
group of disabled individuals, and the results of both
experiments will be compared to check if the
performances of both populations are similar. Also,
in order to collect feedback regarding the system
usability, disabled users will be invited to drive the
wheelchair in a number of real and simulated
scenarios.
ACKNOWLEDGEMENTS
The authors would like to acknowledge to
FCT – Portuguese Science and Technology
Foundation for the INTELLWHEELS project
funding (RIPD/ADA/109636/2009), for the PhD
Scholarship FCT/SFRH/BD/44541/2008, LIACC –
Laboratório de Inteligência Artificial e de
Computadores, DETI/UA – Dep. Electrónica,
Telecomunicações e Informática and ESTSP/IPP –
Escola Superior de Tecnologia da Saúde Porto –
IPP.
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