Ziad Alkhoury
Papers
1
Total Citations
6
H-Index
1
About
Ziad Alkhoury’s research lies at the intersection of biomedical engineering and system identification, with a primary focus on understanding and modeling the neuromuscular dynamics of the human arm. His most cited work, “Linear Parameter-Varying Identification of the EMG–Force Relationship of the Human Arm” (2019), introduces a novel approach that leverages the Linear Parameter Varying (LPV) framework to model how electromyographic (EMG) signals translate into muscle force. By reducing the arm to a single degree of freedom, Alkhoury’s method captures the time-varying, nonlinear nature of this relationship with remarkable accuracy—a significant contribution to prosthetics, rehabilitation robotics, and human-machine interfaces. With 6 citations, this paper has already influenced researchers seeking more precise control of assistive devices. Alkhoury’s work stands out for its elegant combination of theoretical rigor and practical application, offering a pathway to more responsive and naturalistic bionic limbs. His achievements demonstrate a keen ability to translate complex physiological signals into actionable models, making him a promising voice in the field of biomedical signal processing and control.
Research Focus
Key Achievements
Top Papers
- 1