NeuroPi: a portable Steady-State Visually Evoked Potential-based Brain-Computer Interface

Authors

  • Harlei Leite Technological Institute of Aeronautics (ITA)
  • Vitor Barbosa A3Data
  • Sarah Carvalho Technological Institute of Aeronautics (ITA)

DOI:

https://doi.org/10.14209/jcis.2024.12

Keywords:

Brain-Computer Interface, Steady-State Visually Evoked Potential, Embedded System

Abstract

The NeuroPi system is a Brain-Computer Interface (BCI) based on Steady-State Visually Evoked Potentials (SSVEP) that redefines human-machine interaction. This system employs brain activity responses induced by oscillatory visual stimuli to enable intuitive and efficient control of external devices. The system was designed to non-invasively gather brain signals using electroencephalography. A low-cost biosignal amplifier was employed to capture, filter, and digitize these signals. Python scripts were utilized for signal processing in the stages of preprocessing, feature extraction, and classification, ensuring seamless integration, customization, and straightforward adaptability. NeuroPi was designed with a focus on simplicity and user-friendliness, enabling the integration and control of electronic devices using brain signals. Additionally, the system is portable, cost-effective, and efficient, making it suitable for various real-world applications. Performance tests validate NeuroPi's effectiveness, highlighting its potential to contribute to the popularization of SSVEP-based BCI systems. The NeuroPi system is available to be freely used for research and development purposes.

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Author Biographies

Harlei Leite, Technological Institute of Aeronautics (ITA)

Harlei Miguel de Arruda Leite obtained his Ph.D. in Electrical Engineering from the University of Campinas, Brazil, in 2018. He is currently working as an assistant professor at the Institute of Aeronautics. His research interests encompass brain-computer interfaces, human-computer interfaces, machine learning, and signal processing.

Vitor Barbosa, A3Data

Vitor M. Barbosa holds a Master's degree in Electrical Engineering from the University of São Paulo, Brazil. He is currently employed at NTT Data. His primary research interests include signal processing, brain-computer interfaces, and machine learning.

Sarah Carvalho, Technological Institute of Aeronautics (ITA)

Sarah N. Carvalho holds dual Bachelor of Science degrees in Electrical Engineering from Politecnico di Torino, Italy (2010) and the University of Campinas, Brazil (2011). She earned her Master's degree in 2012 and Ph.D. in 2016, both in Electrical Engineering from the University of Campinas, Brazil. Currently, she serves as an assistant professor at the Institute of Aeronautics, focusing her research on brain-computer interfaces, biomedical signal processing, and machine learning.

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Published

2024-08-09

How to Cite

Leite, H., Barbosa, V., & Carvalho, S. (2024). NeuroPi: a portable Steady-State Visually Evoked Potential-based Brain-Computer Interface. Journal of Communication and Information Systems, 39(1), 119–126. https://doi.org/10.14209/jcis.2024.12

Issue

Vol. 39 No. 1 (2024): Vol. 39 No. 1 (2024)

Section

Regular Papers

License

Copyright (c) 2024 Harlei Leite, Vitor Barbosa, Sarah Carvalho (Author)

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Received 2023-11-08
Accepted 2024-07-30
Published 2024-08-09