Joseph Muguro
Papers
10
Total Citations
89
H-Index
7
About
Joseph Muguro is a robotics and human-machine interaction researcher whose work sits at the intersection of bioelectrical signal processing, assistive technology, and intelligent robot control. His research primarily focuses on harnessing biological signals — including electromyography (EMG), electrooculography (EOG), and electroencephalography (EEG) — to create intuitive, accessible control interfaces for robotic systems and assistive devices. Among his most significant contributions is his pioneering work on mapping EMG signals from human upper-limb movements to robotic arm control, with his foundational 2020 and 2021 studies accumulating 15 and 17 citations respectively. These works established efficient, minimum-process frameworks for translating natural human motion into precise robotic commands. Muguro has extended this expertise toward life-changing assistive applications, developing EMG-based gaming interfaces for tetraplegic patients and an electrooculogram-controlled electric wheelchair system for individuals with severe physical disabilities, reflecting a deeply humanitarian dimension to his research. His more recent explorations into deep reinforcement learning for sim-to-real robot control transfer and flexible manipulator vibration suppression demonstrate a broadening technical scope. With a growing body of work exceeding 85 total citations, Muguro represents an emerging voice in bio-signal-driven robotics and inclusive human-robot cooperation research.
Research Focus
Key Achievements
Top Papers
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- 7Robot control systems using bio-potential signals7 citations · 2020
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