Benjamin Marcheix
Papers
1
Total Citations
3
H-Index
1
About
Benjamin Marcheix is a robotics researcher whose work bridges the gap between accessible biosignal technology and intuitive human-machine interaction. His primary research areas include surface electromyography (sEMG)-based control, adaptive gesture recognition, and robotic manipulation. Marcheix’s most notable contribution is his 2019 paper, "Adaptive Gesture Recognition System for Robotic Control using Surface EMG Sensors," which has garnered 3 citations. In this work, he demonstrated how low-cost, commercially available sEMG armbands—once confined to medical diagnostics—can be repurposed for real-time robotic control. By developing an adaptive algorithm that compensates for signal variability across users and sessions, Marcheix significantly improved the reliability of gesture-based commands, making hands-free robotic operation more practical for non-specialists. His research has implications for assistive technologies, prosthetics, and industrial automation, where intuitive control is critical. Though early in his career, Marcheix’s focus on democratizing advanced control systems positions him as a promising voice in the field of human-robot interaction, with future work likely to explore deeper integration of machine learning for adaptive, user-specific interfaces.
Research Focus
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Top Papers
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