Title: Understanding Patient Attention in Robotic Therapy Conditions
Abstract: This research examines patient attention patterns during robotic rehabilitation using computer vision techniques that analyze facial expressions and body behaviors. These measurements establish baseline engagement patterns during therapy sessions, enabling us to understand how existing robot behaviors naturally influence patient attention before developing intervention strategies. This foundational analysis enables the creation of individual attention profiles, informing the design of personalized and adaptive robotic behaviors. The findings will advance evidence-based approaches in rehabilitation robotics, potentially enhancing therapeutic outcomes through improved patient engagement. Bio: Dr. Eng. Fady Alnajjar is an Associate Professor at UAEU specializing in Artificial Intelligence and Robotics. His research focuses on developing intelligent systems that address societal challenges in assistive technologies, healthcare, education, and infrastructure. By leveraging AI, machine learning, computer vision, and social robotics, Dr. Alnajjar designs innovative solutions for individuals with impairments, such as post-stroke patients and children with autism, as well as applications in structural monitoring and behavior recognition. As the founder of the AI and Robotics Lab at UAEU, he has contributed significantly to advancing AI and robotics education and research. His work emphasizes human-centered AI, aiming to empower individuals and improve quality of life through personalized and adaptive technology. Dr. Alnajjar has published over 150 articles, holds 10 US patents, and is committed to interdisciplinary collaboration to drive impactful innovations in intelligent systems.
