Book chapter
Algorithm to detect six basic commands by the analysis of electroencephalographic and electrooculographic signals
Registro en:
López-Arce, E., García, A., Galindo, F., Sánchez, V., Member, & IEEE. (2012). Algorithm to detect six basic commands by the analysis of electroencephalographic and electrooculographic signals.
978-1-4577-1200-5
ISSN 2155-1774
DOI: 10.1109/BioRob.2012.6290864
Autor
López Arce Vivas, Eduardo
García González, Alejandro
Galindo, Felipe
Sánchez González, Víctor Javier
Institución
Resumen
The Electroencephalographic signals are commonly
used for developing brain-machine interfaces (BMI),
in fact is the most used biological signal to translate brain’s
commands to the computer. Some additional physiological
measures have been used along with EEG in order to obtain
more robust and more accurate BMI systems. However, since
very sophisticated recording devices are more available, signal
processing is getting complicated, mainly due to the invested
computational time in signal extraction and pattern recognition.
Therefore, processing time in BMI could be too long, which
is useless for some applications, for instance, devices used in
rehabilitation engineering, or some robotic systems. In this
paper, we propose a six commands recognition algorithm using
only one EEG bipolar connection (O1-P3) in combination
with bilateral electrooculographic signals. Our algorithm could
identify these six commands based on simple temporal analysis
with an average recognition accuracy of 97.1% for the selected
sample of subjects. The average recognition time do not last
more than 0.5 seconds after one of the events occurred.