Implementation of Open-Source Tools with Brain-Computer Interfaces

Main Article Content

Daniel Eduardo Estevez Cárdenas
Nayibe Chio
Johann Barragán Gómez


The continuous advancement of technologies is an undeniable fact in today's world, with changes occurring more frequently in fields such as medicine, the automotive industry, and education. One of the technologies that has stood out in recent years is related to the analysis of brain signals, their classification, and utilization, often referred to as 'Brain-Computer Interfaces' (BCI). Despite significant progress in this technology, its applications are primarily focused on the healthcare sector, specifically in the rehabilitation of patients. It is for this reason that this project was initiated, with the goal of expanding the use of this technology into other areas. This is achieved through the development of a communication and control system using brain signals to interact with an external device, all implemented through open-source software. This project involved three main stages: signal reading, processing/classification, and control of the external device. To carry out the project, the 'MindWave Headset' from NeuroSky was used for reading brain signals, 'Open ViBE' software for signal processing and classification, and 'Python,' 'Arduino IDE,' and the 'Arduino UNO' board for controlling the external device's representation.

As a result of the entire project process, a fully functional system was obtained, designed using open-source software and tools, capable of controlling a simple device through a brain-computer interface. This product serves as a foundation for further advancements in implementing these technologies into new processes.


Download data is not yet available.

Article Details

How to Cite
Estevez Cárdenas , D. E. ., Chio, N., & Barragán Gómez , J. (2023). Implementation of Open-Source Tools with Brain-Computer Interfaces. I+ T+ C- Research, Technology and Science, 1(17). Retrieved from
Research Papers


H. Y. Espitia & E. A. Sandoval (2022). Implementación de interfaz cerebro-máquina para el control de movimiento de un brazo manipulador robótico UR3 para Aplicaciones de Pick and Place.

Díez, I. (2015). Design of classification methods for Brain Computer Interfaces: An application using the  OpenViBE software (thesis). Universidad del País Vasco, Leioa.

Rennard, Y., Lotte, F., Gilbert, G., Congedo, M., Maby, E., Delannoy, V., Bertrand, O., & Lécuyer, A. (2010, April 28). OpenViBE: An Open-Source Software Platform to Design, Test and Use Brain-Computer Interfaces in Real and Virtual Environments. France. Aprende Python (2023). Retrieved from

Diadema NeuroSky MindWave mobile 2. SANDOROBOTICS. (2021, August 13). Retrieved from,%2C%20iOS%2C%20o%20dispositivo%20Android.

Neurosky. (2023). MindWave Mobile 2. MindWave. Retrieved from

Arduino Uno. (2019). Retrieved from

Revera, J. D. (2017). DISEÑO DE UN SISTEMA DE GUIADO DE ROBOTS MEDIANTE LA  ADQUISICIÓN DE SEÑALES EEG (thesis). Universidad Politécnica de Valencia, Valencia.

NeuroSky Store - Apps. Apps. (2014).