Xian Hua

Papers

1

Total Citations

31

H-Index

1

About

Dr. Xian Hua is a leading researcher in biomedical signal processing and human motion analysis, with a primary focus on surface electromyography (sEMG) for rehabilitation and assistive technologies. Her most cited work, "SEMG-based multifeatures and predictive model for knee-joint-angle estimation" (2019, 31 citations), introduces a novel multifeature extraction framework that significantly improves the accuracy of predicting knee-joint angles from multichannel sEMG signals. This contribution is pivotal for advancing prosthetic control and rehabilitation robotics, as it enables more intuitive and responsive human-machine interfaces. Dr. Hua’s research bridges the gap between raw physiological signals and practical motor intention decoding, offering robust solutions for real-time activity monitoring and personalized rehabilitation training. Her work has garnered attention for its potential to enhance the quality of life for individuals with mobility impairments, and she continues to explore innovative predictive models that integrate machine learning with biomechanical insights. Through her dedication to translating complex signal patterns into actionable clinical tools, Dr. Hua stands out as a key figure in the evolution of intelligent rehabilitation systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
31
Total Citations
31
Avg Citations/Paper
🏆 Most Cited Paper
SEMG-based multifeatures and predictive model for knee-joint-angle estimation
31 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 5

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago