Vahid Abolghasemi
Papers
2
Total Citations
69
H-Index
2
About
Vahid Abolghasemi is a researcher whose work sits at the compelling intersection of biomedical signal processing, machine learning, and rehabilitation robotics. His research focuses on harnessing electromyography (EMG) signals to advance the capabilities of assistive and rehabilitative technologies, with a particular emphasis on lower limb biomechanics and human-robot interaction. Among his most notable contributions is a pioneering framework for processing surface EMG signals from the lower limbs to drive knee rehabilitation robots — work that has garnered 59 citations since its publication in 2022, reflecting its rapid and significant uptake within the rehabilitation engineering community. By applying optimised machine learning techniques to muscle force estimation, Abolghasemi has helped bridge the gap between clinical biomechanics and intelligent robotic systems. His complementary research into joint mechanical property estimation using novel mechatronic device design further demonstrates his commitment to translating engineering innovation into practical rehabilitation tools. Abolghasemi's work is particularly valuable for researchers and clinicians seeking data-driven approaches to personalised rehabilitation, offering new avenues for understanding movement control and improving patient outcomes through intelligent, responsive robotic systems.
Research Focus
Key Achievements
Top Papers
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