Moein Owhadi-Kareshk
Papers
1
Total Citations
6
H-Index
1
About
Moein Owhadi-Kareshk is a researcher whose work sits at the intersection of robotics, human-machine interaction, and biomedical signal processing. His primary focus has been on developing intuitive control interfaces for robotic systems, particularly by leveraging physiological signals from the human body. His most cited work, "Control of elastic joint robot based on electromyogram signal by pre-trained Multi-Layer Perceptron" (2016), introduces a novel approach where electromyogram (EMG) signals from upper limb muscles serve as a direct control interface for elastic joint robots. By employing a pre-trained Multi-Layer Perceptron (MLP) neural network, this research enables more natural and responsive robot control, reducing the gap between human intention and machine action. Though his citation count is modest, with this paper garnering 6 citations, the work represents a meaningful step toward seamless human-robot collaboration. Owhadi-Kareshk’s contributions are particularly relevant for assistive robotics and prosthetics, where intuitive, muscle-based control can significantly enhance user experience. His research underscores the potential of integrating machine learning with biomedical signals to create more adaptive and human-centric robotic systems.
Research Focus
Key Achievements
Top Papers
- 1