Papers
3
Total Citations
27
H-Index
3
About
Amina Ababou’s research bridges two critical frontiers: accessible medical imaging and intelligent rehabilitation robotics. Her early work tackled the shortage of ultrasound specialists by developing a removable device for axial force and orientation measurement on medical probes, a key enabler for tele-echography and robot-assisted ultrasound imaging. This foundational contribution, cited 11 times, addresses a pressing need for remote diagnostic tools in underserved areas. More recently, Ababou has focused on advanced control systems for lower limb exoskeletons used in rehabilitation. She has pioneered model-free adaptive controllers that combine Backstepping, Super Twisting algorithms, and neural networks (RBF and MLP) to achieve precise, robust motion control for a 10-degree-of-freedom exoskeleton. Her 2024 paper on this topic has already garnered 10 citations, and her 2023 work on adaptive finite-time control with MLP estimation has 6 citations. These contributions are significant for developing safer, more responsive assistive devices that can adapt to individual patients without requiring complex system models. Ababou’s work exemplifies how control theory and neural networks can be harnessed to create practical, life-changing rehabilitation technologies.
Research Focus
Key Achievements
Top Papers
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