A Framework Based on Eye-Movement Detection from EEG Signals for Flight Control of a Drone

  • Eduardo Zecua CorichiEmail author
  • José Martínez CarranzaEmail author
  • Carlos Alberto Reyes GarcíaEmail author
  • Luis Villaseñor PinedaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10633)


There is a considerable number of people with some disability they may go from partial limb disability to total incapacity. For these people, technology is an opportunity to bring them back some capabilities. In this work, we present a framework where we envisage a system that can be used by a disabled person who can not move but still possesses eye movements. Therefore, by using electroencephalographic (EEG) signals, we recognize and classify eye movements, which are then translated to control commands. Based on the latter, we developed an application to illustrate how such commands could be used to control a drone that could be used to deliver messages or carry out any other activity that involves the drone having to fly from a start point to a final destination. The results obtained in this study indicate that ocular movements are recognized with an accuracy of 86%, which suggests the feasibility of our approach.


EEG Decision tree Classification Drones control PID 



This work has been partially funded by the Royal Society through the Newton Advanced Fellowship with reference NA140454.


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Department of computer SciencesInstituto Nacional de Astrofísica, Óptica y Electrónica (INAOE)TonantzintlaMexico

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