Papers
2
Total Citations
18
H-Index
2
About
Liuqing Zhang is a researcher advancing the precision and safety of robotic-assisted vascular interventional surgery, with a focused expertise in physiological tremor suppression and human-robot interaction. Her work addresses a critical challenge in minimally invasive procedures: the involuntary hand tremor surgeons experience during prolonged operations, which can compromise accuracy. Zhang’s most-cited paper, “Recognition and Filtering of Tremor Signals for Vascular Interventional Surgical Robot” (2020, 11 citations), pioneered methods to identify and remove tremor artifacts in real-time, enhancing the fidelity of master-slave surgical robots. Building on this, her 2021 study “Prediction of Physiological Tremor Based on Deep Learning for Vascular Interventional Surgery Robot” (7 citations) introduced a predictive framework that eliminates the need for prior tremor knowledge, enabling adaptive, data-driven tremor cancellation. These contributions are foundational to improving operational accuracy in complex vascular tasks, such as vessel selection and catheter navigation. Zhang’s work has garnered attention for its practical impact on surgical robotics, with her citation counts reflecting growing recognition among peers. By integrating deep learning with robotic control, she is shaping next-generation systems that augment surgeon capability and patient outcomes.
Research Focus
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