Farid A. Tolbah
Papers
4
Total Citations
40
H-Index
4
About
Farid A. Tolbah is a robotics researcher whose work bridges the critical gap between human motion and machine intelligence. His primary research areas encompass sound source localization, rehabilitation robotics, and prosthetic control systems. Tolbah's most impactful contribution is a two-stage approach for passive sound source localization using the SRP-PHAT algorithm, designed for compact microphone arrays on small mobile robots in indoor environments—a key advancement for autonomous navigation and human-robot interaction. In rehabilitation robotics, he developed a lower limb gait activity recognition algorithm using inertial measurement units (IMUs) and a hybrid mutual information-genetic algorithm for feature selection, achieving robust classification with random forests. His work on proportional myoelectric prosthetic hand control introduced a multi-regression model estimator with a pattern classifier selector, enabling more natural, simultaneous hand movements from surface EMG signals. Tolbah has also applied artificial neural networks to model and simulate 3DOF parallel manipulators, improving precision in forward kinematics. With over 40 citations across his most-cited papers, his research continues to influence the development of intelligent, human-aware robotic systems.
Research Focus
Key Achievements
Top Papers
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