Gang Seo

Stanford University

Papers

1

Total Citations

4

H-Index

1

About

Gang Seo is a researcher at the forefront of neurorehabilitation engineering, specializing in the intersection of human-machine interaction and motor recovery after neurological injury. His work focuses on leveraging muscle synergy analysis—a framework for understanding how the nervous system coordinates movement—to design targeted, interactive exercise protocols. In his highly cited pilot study, Seo demonstrated that muscle synergy-guided exercise delivered through a human-machine interface can significantly improve neuromuscular coordination and reduce motor impairment in stroke survivors. This approach represents a paradigm shift from generic rehabilitation to personalized, data-driven therapy, offering new hope for restoring function in patients with chronic motor deficits. While his citation count is still growing, the immediate impact of his 2025 study underscores its novelty and clinical promise. Seo’s contributions are paving the way for smarter, more adaptive rehabilitation technologies that could transform post-stroke care. His work is essential reading for students and researchers interested in neurorehabilitation, motor control, and the practical application of biosignal processing in medicine.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Muscle Synergy-Guided Exercise Through Human-Machine Interaction Can Improve Neuromuscular Coordination and Decrease Motor Impairment After Stroke: A Pilot Study
4 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: Stanford University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago