Design and Development of a Hybrid EEG-EOG Control System for Assistive Communication in Paralyzed Patients

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Prem kumar M
Deepika K
Gowri S
Varshika C

This project presents the development of a low-cost, non-invasive Brain-Computer Interface (BCI) designed to support individuals with paralysis or Amyotrophic Lateral Sclerosis (ALS) in communicating their basic needs. Built using the NPG Lite platform, the system integrates both electroencephalography (EEG) and electrooculography (EOG) signals to create an intuitive and accessible human-computer interaction method.


The proposed system adopts a hybrid signal-processing approach to improve usability and accuracy. Navigation through the user interface is achieved by detecting eye blinks using EOG signals, allowing users to scroll through predefined menu options without physical movement. Selection of a desired option is performed through EEG signals by measuring the user’s level of mental focus, particularly from the frontal lobe region. This dual-input mechanism ensures a balance between ease of use and reliability, minimizing false activations while maintaining responsiveness.


Captured neural and ocular data are processed in real time and transmitted wirelessly via Bluetooth Low Energy (BLE) to a laptop-based interface. The interface interprets these signals and converts them into actionable commands, enabling users to communicate essential needs such as requesting assistance, expressing discomfort, or interacting with caregivers.


By combining affordability, portability, and open-source accessibility, this system aims to provide a practical assistive technology solution for non-verbal individuals. Ultimately, the project seeks to restore a degree of independence and autonomy, improving quality of life while offering a scalable platform for further research and development in assistive BCI technologies.

Design and Development of a Hybrid EEG-EOG Control System for Assistive Communication in Paralyzed Patients. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(3), 1294-1304. https://doi.org/10.51583/IJLTEMAS.2026.150300112

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References

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How to Cite

Design and Development of a Hybrid EEG-EOG Control System for Assistive Communication in Paralyzed Patients. (2026). International Journal of Latest Technology in Engineering Management & Applied Science, 15(3), 1294-1304. https://doi.org/10.51583/IJLTEMAS.2026.150300112