Dr. Achraf Djemal

As a Ph.D. candidate at MST, I am dedicated to researching a multi-modal approach for epileptic seizure classification based on body-attached sensors. My work involves studying brain and muscle signals during abnormal movements like epilepsy, aiming to enhance diagnostic accuracy and treatment options.

Developed a real-time human activity recognition system using body-attached sensors on Raspberry Pi, leading to efficient tracking. • Implemented embedded machine/deep learning model for wearable and portable tracking. • Achieved successful real-time tracking of human activities, enhancing user experience and efficiency.