Xingchen Yang

Shanghai Jiao Tong University, Imperial College London, Southeast University

Papers

Total Citations

133

H-Index

About

Xingchen Yang is a pioneering researcher at the intersection of neurorobotics, human-machine interaction, and assistive technology. His primary research areas include ultrasound-based neural interfaces, finger motion classification, and artificial empathy in healthcare. Yang's major contribution lies in developing ultrasound sensing models that outperform traditional surface electromyography (sEMG) for decoding complex finger movements—a critical advancement for prosthetic control and rehabilitation. His seminal 2017 paper on ultrasound-based finger motion classification has garnered 110 citations, establishing a foundational approach for non-invasive neural control. He has also authored a comprehensive 2024 review on ultrasound as a neurorobotic interface (21 citations), synthesizing the field's progress for prostheses, exoskeletons, and muscle stimulators. Most recently, Yang has ventured into the emerging domain of artificial empathy, exploring how interpersonal interaction technologies can address healthcare workforce shortages by augmenting emotional support in clinical settings (2025). His work bridges engineering and human-centered design, offering transformative solutions for individuals with motor impairments and reshaping the future of neurorobotic rehabilitation.