Papers
2
Total Citations
39
H-Index
2
About
Te Pi is a leading researcher in neural-driven robotics, specializing in the estimation of human movement intention from electromyography (EMG) signals for advanced prosthetic and robotic control. Their work focuses on decoding complex, multijoint kinematics—particularly of the human hand—to enable simultaneous and proportional myocontrol of robotic hands, a critical step toward natural human-robot interaction. Pi’s most cited paper (2020, 36 citations) pioneered methods for estimating multijoint kinematics from EMG during daily grasping tasks, addressing the biomechanical complexity of the hand as the primary human effector. Their subsequent 2022 study refined continuous estimation techniques for real-world applications, pushing toward more intuitive and efficient prosthetic control. By bridging neural signal processing and robotic actuation, Pi’s contributions are foundational for developing intelligent prostheses that respond seamlessly to user intent. Their work not only advances human-centered robotics but also holds promise for restoring dexterous hand function in amputees, marking a significant achievement in the field of neural-machine interfaces.
Research Focus
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Top Papers
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