Development of an Open-Source EEG Foundation Model - Sharing my interest

[DubraskaS]

Hi, dear community and mentors,

My name is Dubraska (solorzano.dubraska@gmail.com), a last-trimester, Venezuelan electronic engineering student and machine learning enthusiast, currently also working as an IT analist. My passion for learning new things about programming fuels my daily grind. Currently, I'm wrapping up my undergraduate degree thesis on EMG signal classification with Machine Learning for upper limb orthosis control. This project exemplifies my eagerness to translate theory into practical applications, particularly in the realm of bioengineering. Building upon this, I possess a solid foundation in circuit design, digital systems, and embedded programming. I'm proficient in Python language and have a good background in the use of tensorflow and eager to leverage this expertise to contribute to an open-source project within the GSoC program. With a strong work ethic and a dedication to continuous learning, I believe this exciting opportunity would be a fundamental contribution to my professional and personal growth, and another step to working in the area I so much love.

I am highly captivated with this project about creating an open-source EEG foundation model, as it perfectly aligns with my interests. Emory's reputation for excellence in medical research, particularly in areas like brain-computer interfaces, is highly inspiring. Working alongside such a distinguished team would be an invaluable opportunity to learn from leading experts and contribute to a project with the potential to significantly impact the field of biomedicine.

My recent work on EMG signal classification demonstrates my familiarity with using machine learning for bioelectrical signals. The proposed project delves deeper and could have significant applications in brain-computer interfaces for assistive technologies. I would start with an extensive review of the most influencing and recent researches in the area of Brain-Computer Interfaces (BCIs) developed for EEG, not forgetting the various Deep learning models reviews and comparisons, in order to explore all the convincing and possible options. The project per se would then have 5 general scheduled steps:

1. Planification
2. Documentation
3. Available resources recompilation
4. Design and development
5. Testing

I look forward to deeper discussing of the project and to sharing my full proposal!

Regards,

Dubraska Solorzano