Papers

2

Total Citations

32

H-Index

2

About

Pingao Huang is a leading researcher in human-robot interaction and biomedical signal processing, with a focus on advancing prosthetic and rehabilitation technologies. His work centers on developing novel sensing methods for accurate hand gesture and upper-limb movement recognition, addressing critical challenges in human-machine interfaces. Huang’s major contributions include pioneering the use of muscle shape change (MSC) signals as a complementary modality to traditional surface electromyography (sEMG). His 2020 paper on identifying upper-limb movements via MSC signals (19 citations) demonstrated a robust approach to reducing electromagnetic interference, while his 2022 work on a flexible, stretchable hybrid sensor for in-situ sEMG and MSC measurement (13 citations) achieved high-accuracy hand gesture recognition—a key step toward multifunctional prostheses. With a combined citation count exceeding 30 for these foundational studies, Huang’s innovations in sensor fusion and wearable technology are shaping next-generation rehabilitation robots and intuitive human-robot interfaces, offering practical solutions for amputees and patients with motor impairments.

Research Focus

Key Achievements

2
H-Index
2
Papers
32
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Identification of Upper-Limb Movements Based on Muscle Shape Change Signals for Human-Robot Interaction
19 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Chinese Academy of Sciences, Shenzhen Academy of Robotics

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago