Sang Hyeon Jin

Daegu Gyeongbuk Institute of Science and Technology

Papers

4

Total Citations

54

H-Index

3

About

Sang Hyeon Jin is a neuroscience and rehabilitation engineering researcher whose work sits at the intersection of brain-computer interfaces (BCI), neuroimaging, and robotic rehabilitation systems. His research primarily focuses on understanding cortical activation patterns in the context of motor rehabilitation, with particular emphasis on leveraging functional near-infrared spectroscopy (fNIRS) to decode how the brain responds to external robotic stimuli. Jin's most influential contribution, "The Cortical Activation Pattern by a Rehabilitation Robotic Hand: A Functional NIRS Study" (2014), has garnered 43 citations and represents a foundational step in clarifying the relationship between robotic-assisted passive movement and brain response — critical knowledge for designing effective stroke rehabilitation systems. His follow-up work examined how movement speed influences cortical activation, refining the parameters needed to optimize robot-assisted therapy based on principles of neuroplasticity. Beyond neuroimaging, Jin has advanced signal-processing methodologies, applying Common Spatial Pattern (CSP) algorithms to improve classification accuracy of finger-movement-related brain signals. His early BCI-robot integration framework for stroke survivors further demonstrates his commitment to translating neuroscience findings into practical clinical rehabilitation tools, positioning him as a meaningful contributor to the emerging field of brain-guided robotic neurorehabilitation.

Research Focus

Key Achievements

3
H-Index
4
Papers
54
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
The cortical activation pattern by a rehabilitation robotic hand: a functional NIRS study
43 citations · 2014
📈 Most Prolific Year: 2015 (2 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: Daegu Gyeongbuk Institute of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago