Information Technology Reference
In-Depth Information
Also, a simple library of wheelchair interfaces is being developed together with an
application that enables fast generation and configuration of these interfaces. The
interface selection application will be based on the use of machine learning algo-
rithms that will use the available patient and environment models to select the most
appropriate interfaces from the interface library.
4
Implementation
This section presents the implementation for the proposed User Profile feature.
Firstly, it explains the approach followed to specify which test sets are going to be
loaded by the module responsible for tracking the users' profile. Secondly, we show
the simple profiling methods that were implemented to create the future user classifi-
cation. Next, we will present how the extracted information was used to adjust certain
settings of the interface. Finally, a demonstration of how the profile is stored to enable
future use is also made.
4.1
Definition of the Sets
To perform the measures previously described, a simple XML grammar was defined.
It implements four configurable distinct test types: sequences of gamepad buttons;
voice commands; positions for both joysticks and positions for head.
Example of XML containing user profile test set:
<INTELLWHEELS_PROFILER>
<BINARY_JOYSTICK>
<item>
<sequence> joystick.1
joystick.2 </sequence>
<difficulty> easy </difficulty>
</item>
</BINARY_JOYSTICK>
<ANALOG_JOYSTICK>
(…)
<ANALOG_WIIMOTE>
<item> <x>100</x> <y>0</y></item>
</ANALOG_WIIMOTE>
<SPEECH>
<item> go forward </item>
<item> turn right </item>
<item> create new sequen </item>
<item> stop </item>
</SPEECH>
</INTELLWHEELS_PROFILER>
The proposed XML grammar makes it possible for an external operator to configure
the test set that they find most appropriate for a specific context or user. When a user
starts the training session, the four different types of tests are iterated. In order to
