Mohamed Amin Gouda
Papers
3
Total Citations
33
H-Index
2
About
Mohamed Amin Gouda is a researcher at the forefront of human-robot interaction and neural engineering, with a focus on developing intuitive, human-like robotic systems. His work bridges the critical gap between biological signals and machine control, primarily through the decoding of surface electromyography (sEMG) and electroencephalography (EEG) signals. Gouda’s major contributions include the design of a fiber-reinforced, human-like soft robotic manipulator that leverages sEMG-based force estimation to achieve more natural and compliant movement. In the domain of brain-computer interfaces (BCIs), he has pioneered the use of advanced signal processing techniques, such as Graph Fourier Transform and cross-frequency coupling, to decode both voluntary and involuntary upper-limb motor imagery—a key step toward restoring motor function in stroke patients. His work on accurate sEMG classification for hand gesture recognition further demonstrates his commitment to practical, non-invasive control of prosthetics and robots. With his most-cited papers garnering 16 and 15 citations respectively, Gouda’s research is steadily shaping the future of assistive robotics and neural rehabilitation, offering promising pathways for more responsive and human-centered robotic systems.
Research Focus
Key Achievements
Top Papers
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