Sumaya Rahman
Papers
1
Total Citations
3
H-Index
1
About
Dr. Sumaya Rahman is a pioneering researcher in the field of human-robot interaction and rehabilitation robotics, with a core focus on advancing the precision of motion estimation through biosignal processing. Her most notable contribution is the development of a novel Graph Convolution Neural Network (GCNN) framework that integrates surface electromyography (sEMG) and inertial measurement unit (IMU) data to estimate elbow joint angles with unprecedented accuracy. This work, published in 2024, addresses a critical bottleneck in safe and effective human-robot collaboration, particularly for robotic rehabilitation and performance enhancement devices. By leveraging graph-based deep learning, Dr. Rahman’s approach overcomes long-standing challenges in sEMG-based motion estimation, offering a robust solution for real-time control of exoskeletons and assistive technologies. Though early in its citation trajectory, this research has already garnered 3 citations, signaling its growing influence. Dr. Rahman’s work stands at the intersection of biomechanics, machine learning, and robotics, promising to enhance the quality of life for individuals with motor impairments and to push the boundaries of intuitive human-machine interfaces.
Research Focus
Key Achievements
Top Papers
- 1