CONTROLLING OF A DRONE USING EEG AND EMG TECHNOLOGY WITH AN OPENBCI MACHINE

Authors

  • Julen Fraile Education

DOI:

https://doi.org/10.56007/arrivet.v1i2.45

Keywords:

BCI, EEG, EMG

Abstract

This article presents the development of a system combining EEG (electroencephalography) and EMG (electromyography) signals to control a drone, with a particular focus on using EEG to monitor the user's concentration. The project, conducted within TKNIKA's Brain-Computer Interface (BCI) area of specialization, leverages the OpenBCI Ultracortex Mark IV headset and Cyton board to acquire neural and muscular data, enabling the drone's operation and safety mechanisms. The primary objective is to assess concentration levels and automatically disengage the drone if the user loses focus. This integration of brain and muscle signals not only showcases a possible approach to human-drone interaction but also explores the practical implications of using EEG-based control for enhancing user safety and performance in any human controlled machine. The article discusses the key technical challenges and innovations involved in synchronizing EEG and EMG data streams to ensure reliable control and safety features for real-time machine operation.

Published

2025-07-18

Issue

Vol. 1 No. 2 (2025): ARRIVET - Applied Research Results in Vocational Education and Training magazine

Section

d. Training for Research – activities in preparation for applied research and its results

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