For patients with disabilities, particularly those with motor
disabilities and difficulties to interact with computer and devices,
Human-Machine Interaction (HMI) research may provide them new ways
to solve this problem. In this paper, we propose the Brain-Computer Interface
(BCI) approach as a potential technique. The patients may use
a portable electroencephalography (EEG) device to give instruction to
a computing device via eye movements. Classification algorithms have
been investigated in past research to allow detection of eye movement.
We would like to investigate another technique, namely the Symbolic
Aggregate Approximation (SAX) algorithm, to find out its suitability
and performance against known classification algorithms such as Support
Vector Machine (SVM), k-Nearest Neighbour (KNN) and Decision
Tree (DT).
