Wenlong Yu

Chinese Academy of Sciences, Shenzhen Technology University

Papers

Total Citations

H-Index

About

Wenlong Yu is a leading researcher in human-machine interaction (HMI), specializing in the fusion of biosignal sensing and machine learning for advanced prosthetic and rehabilitation robotics. His work centers on accurately decoding hand motion intentions by integrating surface electromyography (sEMG) with novel sensing modalities. Yu’s most impactful contribution is the development of a flexible, stretchable hybrid sensor that simultaneously measures sEMG and muscle shape change (MSC) signals, achieving 13 citations for its breakthrough in in-situ hand gesture recognition. This work directly addresses a critical bottleneck in multifunctional prostheses by providing richer, more reliable control inputs. He further advanced the field by pioneering the Attention-MLP model, a deep learning architecture that estimates continuous finger joint angles from sEMG alone, demonstrating a powerful approach for intuitive robotic arm control. With a research portfolio that bridges sensor engineering and intelligent algorithms, Yu is recognized for pushing the boundaries of non-invasive HMI, enabling more natural and dexterous control of assistive devices.