Papers

3

Total Citations

21

H-Index

3

About

Haiyan Jiang is a researcher advancing the field of biomechatronics and rehabilitation engineering, with a focused expertise in using surface electromyography (sEMG) signals for human motion analysis and joint torque prediction. Her work centers on developing intelligent, non-invasive methods to decode neuromuscular activity, directly contributing to the design of adaptive functional electrical stimulation (FES) systems and powered exoskeletons for limb rehabilitation. Jiang’s major contributions include pioneering the use of cerebellar model neural networks—both standard and recurrent architectures—to classify ankle movements (eversion and inversion) and to predict ankle joint torque from sEMG and angular velocity signals. Her most cited paper (2020, 14 citations) establishes a foundational framework for torque prediction, a critical feedback signal for quantitative rehabilitation assessment. By integrating machine learning with physiological signals, Jiang’s research enables more responsive and personalized assistive devices, bridging the gap between neural intent and robotic actuation. Her work, though early in citation impact, represents a vital step toward smarter, bio-inspired control systems for restoring mobility in patients with neuromuscular impairments.

Research Focus

Key Achievements

3
H-Index
3
Papers
21
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Ankle Joint Torque Prediction Based on Surface Electromyographic and Angular Velocity Signals
14 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Xiamen University, Fujian Medical University, Fuzhou University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago