EEG Signal Classification for Brain-Computer Interface Using CNN

Abstract

Brain-Computer Interfaces (BCI) require accurate EEG signal classification for effective communication. This project implements a CNN-based model to classify EEG signals into different mental states. The model is trained on EEG datasets to recognize patterns in brain activity.

Key Words

• EEG Classification
• Brain-Computer Interface
• CNN
• Signal Processing

Delivery Time

Delivery within: 6 days