About

Lina Tong is a leading researcher in rehabilitation robotics and human-robot interaction, with a focus on developing intelligent systems that restore mobility and enhance human-machine communication. Her core contributions span lower limb rehabilitation robots, motion intention recognition, and sEMG-based gesture control. Tong pioneered the design of the iLeg—a novel lower limb rehabilitation robot for sitting/lying postures—and advanced its dynamics modeling and identification under motion constraints, enabling model-based recognition of patients’ motion intention for active rehabilitation training. Her work on zero-force control frameworks using fuzzy-PID methods has further improved post-stroke training outcomes. More recently, Tong has expanded into gesture recognition for remote-operated robots in hazardous environments, such as coal mine inspection manipulators, employing multistream CNNs and adaptive channel selection to decode forearm sEMG signals. With over 118 citations across her most-cited papers, her research has been published in leading venues including *Mechanism and Machine Theory* and *IEEE Sensors Journal*. Tong’s interdisciplinary approach—bridging mechanical design, control theory, and machine learning—positions her work at the forefront of assistive and industrial robotics, directly impacting patient rehabilitation and operator safety.

Research Focus

Key Achievements

5
H-Index
6
Papers
118
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
Toward Patients’ Motion Intention Recognition: Dynamics Modeling and Identification of iLeg—An LLRR Under Motion Constraints
45 citations · 2016
📈 Most Prolific Year: 2014 (2 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Shandong Institute of Automation, Chinese Academy of Sciences, China University of Mining and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago