Hui Shen

Tianjin University of Technology and Education, Donghua University, Qingdao University

Papers

Total Citations

H-Index

About

Hui Shen is a researcher whose work bridges bionics, intelligent manufacturing, and brain-computer interfaces (BCI). Her key contributions span three distinct areas: bio-inspired sensor design, digital twin-driven process monitoring, and neural signal processing. In bionics, she developed a low-frequency acceleration sensor inspired by the human vestibular system’s saccule, mimicking Sensory Hair cells to detect gravity accelerations—a novel approach for motion sensing. In manufacturing, she pioneered a digital twin framework for weak rigid drilling systems, enabling real-time monitoring of unstable states and recommending strategies to suppress burr formation, a critical issue in precision machining. Earlier, she advanced BCI technology by applying wavelet packet decomposition to steady-state visual evoked potentials (SSVEP), improving information transmission rates over traditional FFT methods. Her most cited work, a 2009 study on an SSVEP-based multi-DOF manipulator control system (18 citations), demonstrates her early impact in neural control. With a total citation count approaching 30 across her top papers, Shen’s work exemplifies how bio-inspired design and digital twin technologies can solve real-world engineering challenges, from precision drilling to human-machine interaction.