Jianfei Song

Papers

1

Total Citations

16

H-Index

1

About

Jianfei Song is a leading researcher in neurorehabilitation, with a focus on stroke recovery and the integration of advanced technologies to restore motor function. His work bridges the fields of brain stimulation, robotics, and functional neuroimaging, particularly through the use of intermittent theta burst stimulation (iTBS) and robot-assisted training. In his most cited study (2024, 16 citations), Song demonstrated that combining robot-assisted upper limb training with iTBS significantly enhances cortical activation in stroke patients, as measured by functional near-infrared spectroscopy (fNIRS). This pioneering research provides critical mechanistic insight into how multimodal therapies can promote neuroplasticity more effectively than robot training alone. By elucidating the neural correlates of recovery, Song’s contributions are shaping evidence-based protocols for post-stroke rehabilitation. His work is highly regarded for its translational impact, offering a clearer path toward personalized, technology-driven therapies that improve patient outcomes.

Research Focus

Key Achievements

1
H-Index
1
Papers
16
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
Effects of robot-assisted upper limb training combined with intermittent theta burst stimulation (iTBS) on cortical activation in stroke patients: A functional near-infrared spectroscopy study
16 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 11

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago