Kianoush Aqabakee

Amirkabir University of Technology

Papers

1

Total Citations

9

H-Index

1

About

Dr. Kianoush Aqabakee is a pioneering researcher at the intersection of computational intelligence and rehabilitation robotics, with a primary focus on developing advanced control systems for lower limb exoskeletons. His work uniquely integrates recursive generalized type-2 fuzzy logic systems with radial basis function neural networks to address critical challenges in human-robot interaction. In his most-cited 2024 paper, Dr. Aqabakee introduced a novel framework that simultaneously estimates joint positions and implements adaptive electromyography-based impedance control, enabling exoskeletons to respond intuitively to user intent. This contribution has already garnered 9 citations, reflecting its immediate impact on the field. By leveraging the uncertainty-handling capabilities of type-2 fuzzy systems, his research significantly improves the robustness and safety of assistive devices, particularly for individuals with motor impairments. Dr. Aqabakee’s work stands out for its practical integration of machine learning and biomechanics, offering a pathway toward more natural and responsive human-machine interfaces. His achievements mark him as a rising leader in neurorehabilitation engineering, with potential to transform how exoskeletons adapt to dynamic physiological signals.

Research Focus

Key Achievements

1
H-Index
1
Papers
9
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Recursive generalized type-2 fuzzy radial basis function neural networks for joint position estimation and adaptive EMG-based impedance control of lower limb exoskeletons
9 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Amirkabir University of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago