Heng‐An Lin
Papers
2
Total Citations
56
H-Index
2
About
Heng-An Lin is a leading researcher in human-robot interaction, specializing in intuitive, muscle-driven control systems. His work centers on developing muscle-gesture-computer interfaces (MGCI) that translate surface electromyography (sEMG) signals into real-time commands for robotic systems. In his highly cited 2016 paper, Lin introduced a novel method for five-fingered robotic hand control using a commercial MYO armband, combining wavelet transform features with a neural network classifier to decode complex hand gestures from eight sEMG channels. This work, with 29 citations, demonstrated a practical, wearable solution for dexterous prosthetic and robotic manipulation. His foundational 2015 study, cited 27 times, extended this approach to mobile robot navigation, enabling users to control a three-wheeled omnidirectional robot through intuitive arm gestures. By leveraging off-the-shelf hardware and advanced signal processing, Lin has made brain-machine interfaces more accessible and robust. His contributions are pivotal for assistive robotics, rehabilitation technology, and natural human-robot collaboration, establishing a framework that bridges biological signals and machine control.
Research Focus
Key Achievements
Top Papers
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