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7 CONCLUSIONS
The results confirmed the viability of the sleep onset
detection using related to drowsiness patterns in the
EOG signal as blinking frequency and saccade
movements’ appearance. Some misdetection of the
algorithms may be due to the inter-subject variability
mostly regarding the shape of the saccade pattern.
Future work will be focused in the improvement
of the saccade detection algorithm by including the
detection of initiation and end of the saccade pattern
in order to make more specific the detection and
accurate the calculation of the variable velocity of
the saccade.
The future objective is to use the EOG signal as
Gold Standard in vehicle tests replacing the EEG
signal that shows low quality signal in real
environments.
ACKNOWLEDGEMENTS
This work has been partially funded by the Spanish
MINISTERIO DE CIENCIA E INNOVACIÓN.
Proyecto IPT-2011-0833-900000.Healthy Life style
and Drowsiness Prevention-HEALING DROP.
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