Zainab Harbi

Papers

Total Citations

H-Index

About

Zainab Harbi is a researcher at the intersection of artificial intelligence, healthcare technology, and human-robot interaction, with a primary focus on developing non-invasive tools for early dementia detection. Her most cited work, "Feature Extraction Method for Clock Drawing Test" (2015, 9 citations), addresses a critical gap in automated cognitive assessment by proposing a novel computational approach to analyze the classic Clock Drawing Test—a widely used screening tool for cognitive impairment. This work builds on her earlier efforts to create a dementia evaluation system using daily conversations and a conversational robot, though she identified limitations in real-world deployment. Harbi’s contributions lie in bridging traditional clinical assessments with machine learning, offering a more objective and scalable method for detecting early signs of dementia. Her research has practical implications for aging populations, aiming to make cognitive screening more accessible through technology. While her citation count reflects a niche but growing field, her work represents an important step toward integrating AI into geriatric care, with potential to improve quality of life for elderly individuals and support caregivers through early intervention.