Exploring Optimized Support Vector Machine for EEG Signal-Based Emotion Recognition: A Comparative Analysis and Performance Evaluation

Project Overview

During my summer research program at the University of California, Los Angeles (UCLA), I conducted research on BCI systems and EEG data analysis under the supervision of Professor Dejan Marković.

Research Focus

• Collected and analyzed EEG data using BCI technology
• Investigated innovative applications in depression diagnosis and treatment
• Focused on machine learning and deep learning techniques for EEG emotion classification
• Optimized machine learning algorithm efficiency and accuracy

Project Presentation

• Completed group presentation: “EEG-Based BCI Innovations in Depression Diagnosis and Therapy”
• Published EI conference paper on optimized SVM for EEG emotion recognition

Recommended citation: Deng Junhao. (2024). "Exploring Optimized Support Vector Machine for EEG Signal-Based Emotion Recognition: A Comparative Analysis and Performance Evaluation." 3DIT-MSP&DL 2024.