Hanghang Ma

China University of Mining and Technology

Papers

1

Total Citations

17

H-Index

1

About

Hanghang Ma is a leading researcher at the intersection of intelligent mining technology and human-robot interaction, with a primary focus on enhancing the safety and efficiency of underground operations. His most notable contribution is the development of a pioneering sEMG-based gesture recognition method for coal mine inspection manipulators, detailed in his highly cited 2023 paper (17 citations). This work addresses a critical need in remote-operated rescue robotics by enabling operators to convey emergency commands through forearm surface electromyography (sEMG) signals. Ma designed a wireless six-channel sEMG acquisition device and implemented a multistream convolutional neural network (CNN) to accurately interpret these signals, significantly improving response times in hazardous environments. His research bridges biomedical signal processing with industrial robotics, offering a robust solution for hands-free control in confined or dangerous spaces. By advancing human-robot collaboration in mining, Ma’s work directly contributes to safer, more responsive rescue operations, marking him as an innovator in applied intelligent systems for extreme conditions.

Research Focus

Key Achievements

1
H-Index
1
Papers
17
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
sEMG-Based Gesture Recognition Method for Coal Mine Inspection Manipulator Using Multistream CNN
17 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: China University of Mining and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago