Problem statement
Many individuals with motor disabilities struggle with traditional computer interfaces.
The challenge is to create an innovative solution using Brain-Computer Interface (BCI)
technology, allowing users to control digital interfaces with their brain signals, making it
accessible, reliable, and user-friendly.
Abstract
This project focuses on developing a user-friendly BCI application that connects users’
brain signals to digital interfaces. It empowers individuals with motor disabilities,
enabling them to control computers and devices with mental commands. The
application integrates with various BCI devices, advancing assistive technology for
inclusive use.
Outcome
● Integration with BCI Devices:
Ensure compatibility with different BCI devices for widespread use.
● User-Friendly Interface:
Design an intuitive interface for easy navigation and control, catering to individuals with
motor disabilities.
● Accurate Signal Processing:
Implement advanced signal processing algorithms for precise interpretation of brain
signals.
● Customizable Commands:
Allow users to define personalized mental commands for specific actions, enhancing
adaptability.
● Real-Time Responsiveness:
Optimize the application for quick interpretation and execution of commands, providing
a natural interaction experience.
● Security and Privacy Measures:
Implement robust security measures, including data encryption, to protect users’ brain
data and privacy.
● Assistive Features:
Include predictive text input, cursor control, and application switching for enhanced
usability.
● Documentation and User Guidelines:
Provide comprehensive documentation and user guidelines, ensuring easy setup and
use of the BCI application.
● Continuous Improvement:
Design for scalability, allowing future updates based on user feedback and
advancements in BCI technology.
Reference
Brain-Computer Interface (BCI) is a device that allows direct communication path between central nervous system and external devices without peripheral nerves dependency. Brain-Computer Interface and its applications reached beyond medical applications, it is used to enhance, improve, restore or replace functions or it can be used as a research tool. Stakeholders of the field have developed future plans and the ethical in research. the multidisciplinary nature of Brain-Computer Interface is based on neuroscience, signal processing, biomedical sensors, and hardware. This paper aims to present briefly the current state and the future of Brain-Computer Interfaces. The future works of the author are based on hardware approach using System-On-Chip combined with novelty memristor crossbar memory, which can be used to emulate axons and neurons directly in the hardware.
- https://ec.europa.eu/programmes/horizon2020/en/news/bnci-horizon-2020-retreat.
- C. Gruger and B. Z. Allison, “Recent advances in Brain-Computer Interface research-The BCI award 2013,” SpringerBriefs in Electrical and Computer Engineering, 2014.
- D. T. Bundy and E. C. Leuthardt, “An ipsilateral contralesional BCI in chronic stroke patients,” SpringerBriefs in Electrical and Computer Engineering, 2014.
- D. Looney, P. Kidmose, M. J. Morell, and D. P. Mandic, “Ear-EEG: continuous brain monitoring,” SpringerBriefs in Electrical and Computer Engineering, 2014.
- D. J. Krusienski, G. Schalk, D. J. McFarland, and J. R Wolpaw, “Tracking of the Mu rhythm using an empirically derived matched filter,” 2nd International IEEE EMBS Conference on Neural Engineering, 2014.
https://ieeexplore.ieee.org/document/7781096/