Abstract
The ability to communicate without using speech or hand gestures poses a great improvement in the quality of life of patients that suffer from movement impairment. Human-machine interaction tools are being studied and developed in order to optimize the usage of biological signals not affected by the individual’s disease. Among different approaches electrooculography signals are an alternative for those who can still move their eyes. This work proposes the use of Genetic Programming to interpret bio signals in the control of a mouse cursor. A digital system was designed to record and filter the EOG signal. Thereafter a Genetic Programming algorithm was used to find the best description for the cursor movement. We show that the algorithm was able to find an equation that describes the moment with 92.5 and 93.0% hit rate for each subject respectively. These preliminary results are compatible with the literature and show that Genetic Programming can be used to find a description of a cursor movement in a simple EOG system with no need of prior knowledge about the movement neither threshold definition.
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Medeiros, R., S. Souza, A.C., F. Rodrigues, G. (2019). Mouse Control Interface Using Electrooculogram and Genetic Programming. In: Costa-Felix, R., Machado, J., Alvarenga, A. (eds) XXVI Brazilian Congress on Biomedical Engineering. IFMBE Proceedings, vol 70/2. Springer, Singapore. https://doi.org/10.1007/978-981-13-2517-5_51
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DOI: https://doi.org/10.1007/978-981-13-2517-5_51
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