Xiuqi Cao

Chinese Academy of Sciences

Papers

1

Total Citations

11

H-Index

1

About

Xiuqi Cao is a leading researcher at the intersection of flexible electronics and human–machine interfaces, with a primary focus on developing advanced tactile sensors for gesture recognition and somatosensory applications. Her most-cited work, "A Hybrid Microstructure Piezoresistive Sensor with Machine Learning Approach for Gesture Recognition" (2021, 11 citations), represents a significant contribution to the field by integrating microstructural design with hybrid functional materials. This innovative approach overcomes key limitations in traditional tactile sensors, enhancing sensitivity and enabling more accurate, real-time gesture detection. By coupling these sensor advancements with machine learning algorithms, Cao has pioneered methods that transform raw tactile data into meaningful interaction signals, pushing the boundaries of wearable technology and smart interfaces. Her research is particularly notable for its practical implications in prosthetics, robotics, and virtual reality systems. With a growing citation impact, Cao’s work is increasingly recognized as foundational for next-generation, adaptive human–machine systems, establishing her as a rising authority in flexible sensor engineering and intelligent tactile perception.

Research Focus

Key Achievements

1
H-Index
1
Papers
11
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A Hybrid Microstructure Piezoresistive Sensor with Machine Learning Approach for Gesture Recognition
11 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Chinese Academy of Sciences

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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