Papers
8
Total Citations
34
H-Index
4
About
A. Mahmood’s research lies at the intersection of biomechatronics, human motion analysis, and intelligent control systems, with a particular focus on restoring and enhancing human motor function. His most significant contributions center on the synthesis and control of sit-to-stand (STS) motion, a critical indicator of physical independence. By leveraging clinical evidence that head position is a key sensory input for balance, Mahmood developed a novel neuro-fuzzy control framework that models the human central nervous system to generate physiologically relevant STS trajectories. This work, published in 2020, has garnered 8 citations and represents a foundational step toward assistive devices that respond intuitively to user intent. Expanding into rehabilitation robotics, he has advanced the control of robotic digits for anthropomorphic hands, using bond graph modeling and linear quadratic regulator synthesis to achieve seamless coordination with impaired human hands. His earlier work on robust control of customized robotic arms, cited 4 times, addressed unstructured uncertainties critical for prosthetic limb design. Across his portfolio, Mahmood’s research demonstrates a consistent drive to translate clinical hypotheses into verifiable, control-oriented models, making him a notable contributor to the field of human-centered robotics and rehabilitation engineering.
Research Focus
Key Achievements
Top Papers
- 1Neuro-fuzzy control of sit-to-stand motion using head position tracking8 citations · 2020
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- 3Cartesian Control of Sit-to-Stand Motion Using Head Position Feedback5 citations · 2020
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- 6Synthesis of Sit-to-Stand Movement Using SimMechanics3 citations · 2019
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