Yasmine Amara
Papers
1
Total Citations
2
H-Index
1
About
Yasmine Amara is a rising researcher in the field of rehabilitation robotics and intelligent control systems, whose work focuses on advancing adaptive, model-free control strategies for lower limb exoskeletons. Her most-cited paper, "Adaptive model-free control of lower limb exoskeletons using neural estimation and swarm-based optimization" (2025), introduces a novel framework that combines neural estimation with swarm intelligence algorithms to enable real-time, autonomous adjustment of exoskeleton assistance without requiring complex dynamic models. This approach addresses a critical challenge in wearable robotics—ensuring safe, intuitive, and personalized support for users with mobility impairments. While her citation count is still growing (2 citations for this key work), the innovative integration of bio-inspired optimization and neural networks positions her at the forefront of next-generation exoskeleton control. Amara’s contributions are particularly notable for their potential to reduce the computational burden and calibration time in clinical and home-use exoskeletons, making assistive technology more accessible. Her research bridges the gap between theoretical control theory and practical rehabilitation engineering, offering a promising pathway toward more responsive and user-friendly robotic aids for individuals with lower limb disabilities.
Research Focus
Key Achievements
Top Papers
- 1