Lutfur Nahar

International Islamic University Chittagong

Papers

Total Citations

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About

Lutfur Nahar is a researcher focused on advancing computer vision techniques for human pose estimation, with particular applications in healthcare and rehabilitation. Her most-cited work, "Skeleton and Joint Angle Estimation Based on MobileNet" (2023), addresses the critical challenge of detecting body key-points and estimating 2D skeletonized poses—a fundamental problem for monitoring movement in clinical and assistive technologies. By leveraging the efficient MobileNet architecture, Nahar’s research enables real-time, lightweight pose estimation that can be deployed on resource-constrained devices, making it practical for rehabilitation monitoring and telehealth applications. With 2 citations, this paper has already begun influencing the field by demonstrating how deep learning can bridge the gap between accurate joint angle measurement and accessible, portable systems. Nahar’s contributions are particularly notable for their potential to transform patient care, allowing clinicians to track recovery progress through automated, non-invasive analysis of body movements. Her work sits at the intersection of computer vision and biomedical engineering, offering scalable solutions that could democratize physical therapy and assistive diagnostics.