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Design of a Personal Communication Device, Based in EEG Signals

Jenifer Salguero(1), Oscar Fernando Avilés Sánchez(2*), Mauricio Felipe Mauledoux Monroy(3)

(1) Department of Mechatronics Engineering, Militar Nueva Granada University, Colombia
(2) Department of Mechatronics Engineering, Militar Nueva Granada University, Colombia
(3) Department of Mechatronics Engineering, Militar Nueva Granada University, Colombia
(*) Corresponding author


DOI: https://doi.org/10.15866/irecap.v7i2.10927

Abstract


This paper presents a brain-computer interface (BCI) designed for patients affected with Amyotrophic lateral sclerosis (ALS) or with other diseases with Bulbar-Spinal Muscular Atrophy that affect the patient’s interaction with the environment. By using an EEG portable (Emotiv Epoc) we acquired neural signals which were processed and used to make a choice in the initial prototype for healthy subjects. Considering this, we worked with EEG’s artifacts with the purpose of training and validating a neural network on seven different subjects. The accuracy of this technique is about 81.58% when the interface’s validation is finished with the same subjects. When the validation has finished with different subjects its accuracy is 73.68%. We can conclude that the Emotiv headset is a good alternative for the development of technological devices, which purpose is to reduce the communication gap between a diseased patient and his environment.
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Keywords


EEG; Neural Signal Processing; Neural Network

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References


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