Background: Electrooculogram (EOG) signal is one of the bioelectric signals acquired from
the human body to study the movements of eyes and also to design and develop assistive devices. These
devices can be mobility devices, video gaming devices or any other assistive device.
Methods: Assistive devices are especially designed for quadriplegic or spinal cord injured patients.
Motors are one of the key components in the design of mobility devices. These motors are to be driven
with the help of EOG commands. This paper explains the process of eliminating involuntary eye
movements while driving the motors under the control of EOG signals. The system design is carried out
in two ways. Initially the system is designed in such a way that the motors are driven even for
involuntary eye movements which is a major drawback of the system.
Conclusion: This drawback has been overcome successfully by introducing the moving average
technique during classification of the EOG signals. The systems overall classification accuracy is also
computed by constructing confusion matrix and has produced high sensitivity, specificity with overall
average accuracy of 90.91%.
Keywords: EOG, assistive, involuntary, microcontroller, motors, Ag-AgCl electrodes, control signals.
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