This video is my M.Tech term assignment presentation under the subject image processing and Computer Vision at NITK Surathkal.
The topic is:
EEG-Based Brain–Computer Interfaces (BCI) Using Image Processing
implemented using MATLAB and EEGLAB.

🔹 Contents Covered in the Presentation

Introduction to EEG & BCI – motivation, applications, and brain rhythms.

Why Image Processing? – treating EEG plots (ERP, PSD, scalp maps, spectrograms) as images.

Theoretical Foundations (LaTeX Report) – sampling, filtering, ICA, ERP, PSD, and time–frequency analysis.

Live MATLAB + EEGLAB Demo:

Dataset import & channel visualization

Preprocessing (bandpass, notch filtering, ICA artifact removal)

ERP extraction & scalp topography

Time–frequency (ERSP) heatmaps

Power Spectral Density (PSD)

Feature extraction (bandpower, CSP, ERP images)

Classification (LDA, SVM, CNN using image-based features)

Real-time EEG visualization

Conclusion & Future Scope – EEG as images for next-gen BCIs.

🔹 Tools & Frameworks Used

MATLAB (R2023a)

EEGLAB Toolbox → Download EEGLAB here (https://sccn.ucsd.edu/eeglab/download.php)

LaTeX (for mathematical derivations and report preparation)

🔹 Presentation Material

📑 Full Presentation Slides & LaTeX Report (PDF): https://drive.google.com/drive/folders/1Z-xyueekpLIRibmpxs_236zpsWv28AHX?usp=sharing

🔹 Key Highlights

EEG converted into images: ERP plots, spectrograms, ICA scalp maps.

Application of image processing & computer vision (CNNs, feature extraction).

Integration of signal + image processing for robust BCI decoding.

Real-time visualization of brain activity.

📌 Author & Course Info

👤 Author: Veda Prakash
🎓 Course: M.Tech (Image Processing & Computer Vision)
🏫 Institute: NITK Surathkal

🔹 Keywords (SEO / Tags)

EEG, BCI, EEG BCI, MATLAB EEG, EEGLAB tutorial, EEG image processing, EEG signal processing, Brain–Computer Interface, ICA EEG, ERP MATLAB, EEG spectrogram, EEG CNN, EEG classification, Motor Imagery, Neuroprosthetics, EEG research, NITK M.Tech