Iman Kardan
Papers
9
Total Citations
131
H-Index
6
About
Iman Kardan’s research lies at the intersection of robotic exoskeletons, human-robot interaction, and intelligent control systems, with a particular focus on assistive technologies for gait rehabilitation and human augmentation. His most influential work, "Assist-As-Needed control of a hip exoskeleton based on a novel strength index" (56 citations), introduces a patient-adaptive control paradigm that dynamically adjusts robotic assistance based on the user’s real-time physical capacity—a significant step toward personalized rehabilitation robotics. Kardan has also made notable contributions to the foundational robotics problem of forward kinematics, developing an improved hybrid method that combines artificial neural networks with numerical algorithms (21 citations). His work on compliantly actuated exoskeletons using non-linear model predictive control (17 citations) addresses the critical challenge of providing smooth, safe, and efficient assistance during locomotion. Beyond exoskeletons, Kardan has advanced human-machine interfaces by developing a PSO-MLPANN hybrid approach for estimating joint torques from sEMG signals (7 citations), and has explored reinforcement learning for delayed output feedback control in gait-assist devices. His research consistently bridges theoretical control methods with practical, human-centered applications, making him a rising figure in the field of assistive robotics.
Research Focus
Key Achievements
Top Papers
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- 2An improved hybrid method for forward kinematics analysis of parallel robots21 citations · 2015
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