Muhammad Syaiful Amri bin Suhaimi
National Institute of Technology, Gifu College, Gifu University, Sebelas Maret University
Papers
8
Total Citations
79
H-Index
6
About
Muhammad Syaiful Amri bin Suhaimi is a researcher specializing in human-robot interaction, bio-signal processing, and assistive robotics, with a particular focus on leveraging biological signals to enable intuitive robotic control systems. His most significant contributions center on the use of electromyography (EMG) and electrooculography (EOG) signals to develop sophisticated control interfaces for robotic arms and assistive technologies. His most-cited work, published in 2021 with 17 citations, introduced a minimum-mapping framework that classifies upper arm movements from just three EMG signals to control a 2-DoF robotic arm, demonstrating an elegant efficiency in human-robot cooperation. Complementary research from 2020 (15 citations) further established robust EMG-based control schemes enabling collaborative human-robot tasks. Notably, his work extends beyond robotics into accessibility technology, developing neck EMG-based gaming interfaces specifically designed for individuals with upper limb impairments and tetraplegic patients, reflecting a meaningful commitment to inclusive design. With contributions spanning EOG-guided object grasping, multi-modal bio-signal integration combining EEG, EOG, and EMG, and machine learning-enhanced signal classification, Suhaimi has accumulated over 79 citations across his published works. His research sits at a meaningful intersection of biomedical engineering and robotics, offering promising pathways for rehabilitation and assistive technology development.
Research Focus
Key Achievements
Top Papers
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- 3Robot Control System Based on Electrooculography and Electromyogram12 citations · 2015
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- 6Robot control systems using bio-potential signals7 citations · 2020
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