Francisco David Pérez-Reynoso
Universidad Politécnica de Pachuca, Instituto Politécnico Nacional, Universidad del Valle de México
Papers
3
Total Citations
72
H-Index
3
About
Francisco David Pérez-Reynoso is a leading researcher in assistive robotics and human–machine interfaces (HMI), with a focus on empowering individuals with severe motor disabilities. His core contributions lie in the development of custom, non-invasive control systems using physiological signals such as electrooculography (EOG) and electromyography (EMG). His most cited work (28 citations) introduces a multiclass classification system for 1D EOG signals, enabling the control of an omnidirectional robot—a breakthrough in accessibility. A second highly cited paper (25 citations) advances this by employing neural network modeling for real-time trajectory tracking of a manipulator robot, addressing the critical challenge of user-specific customization. More recently, his work on EMG pattern recognition (19 citations) expands the toolkit for rehabilitation and physiotherapy support systems. Across these studies, Pérez-Reynoso consistently tackles the problem of personalization, ensuring that interfaces adapt to the user rather than forcing the user to adapt to rigid classification parameters. His research has significant implications for improving quality of life and autonomy, bridging the gap between complex neural signals and practical robotic assistance.
Research Focus
Key Achievements
Top Papers
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