About

Xilong Hou is a robotics and medical engineering researcher whose work sits at the intersection of robotic systems, medical ultrasound, and human-machine interaction. His research focuses on developing intelligent, robot-assisted platforms for remote and autonomous ultrasound diagnosis, continuum-mechanism-based medical robots, and teleoperation systems designed to enhance clinical precision and accessibility. Hou's most cited work, a 2017 study on a 6DOF robot-assisted ultrasound scanning system (19 citations), pioneered remote diagnostic capabilities by allowing physicians to control ultrasound probes via internet-based interfaces — a significant stride toward telemedicine applications. He has made notable contributions to parallel mechanism design, including Stewart-Gough platform optimization for ultrasound diagnostics and robotic wrists with remote center of motion control. His 2023 work on a novel haptic joystick for continuum medical robots (14 citations) addresses critical gaps in master-slave control interfaces, while his research on transesophageal ultrasound robots demonstrates a commitment to advancing minimally invasive procedural guidance. More recently, Hou has pursued portable, autonomously intelligent ultrasound acquisition devices, reflecting a broader vision of democratizing diagnostic robotics. With a growing body of work accumulating nearly 100 citations, his contributions are shaping the future of surgical assistance and robotic medical imaging.

Research Focus

Key Achievements

7
H-Index
14
Papers
104
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Study of a 6DOF robot assisted ultrasound scanning system and its simulated control handle
19 citations · 2017
📈 Most Prolific Year: 2023 (5 Papers)
🤝 Key Collaborators: 34
🏛 Institutions: Chinese Academy of Sciences, Chinese University of Hong Kong, Shenzhen, Hong Kong Science and Technology Parks Corporation, Shenzhen Institutes of Advanced Technology, Peng Cheng Laboratory

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago