Amandine Gesta
Papers
2
Total Citations
62
H-Index
2
About
Amandine Gesta is a researcher at the forefront of assistive robotics and human-machine interaction, with a focused expertise in developing intelligent systems for individuals with motor impairments. Her work critically bridges the gap between advanced machine learning and practical rehabilitation technologies. Gesta’s major contributions include a landmark systematic study on electromyography (EMG)-based hand gesture recognition for assistive robots, where she evaluated deep learning and machine learning models to enhance control for upper limb prostheses—a work that has garnered 50 citations and is foundational for improving the quality of life for amputees. She has also authored a comprehensive literature review on design considerations for lower limb pediatric exoskeletons, addressing the complex gait disorders associated with Cerebral Palsy. This highly cited work (12 citations) synthesizes critical engineering and clinical requirements, guiding the development of safer, more effective robotic aids for children. Through her research, Gesta is driving innovation in non-invasive, intuitive control systems and user-centered exoskeleton design, making her a notable voice in the future of rehabilitation robotics.
Research Focus
Key Achievements
Top Papers
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