Yunping Song
Papers
1
Total Citations
29
H-Index
1
About
Yunping Song has made significant contributions to neurorehabilitation, with a primary focus on brain-computer interface (BCI) technology for post-stroke recovery. Their most cited work, a 2025 meta-analysis on BCI-based training for upper-limb rehabilitation, systematically evaluated the efficacy of this emerging intervention, addressing the variability in previous studies. This landmark paper, which has already garnered 29 citations, synthesized evidence to clarify how BCI training can promote motor recovery after stroke, providing crucial guidance for clinicians and researchers. Song’s research addresses a critical gap in stroke rehabilitation, where traditional therapies often yield limited results. By rigorously analyzing clinical outcomes, their work has helped establish BCI as a promising tool for restoring upper-limb function, offering new hope for patients with motor impairments. This meta-analysis stands as a definitive reference in the field, demonstrating Song’s ability to translate complex neurotechnological concepts into actionable clinical insights. Their contributions continue to shape the future of personalized, technology-driven rehabilitation strategies.
Research Focus
Key Achievements
Top Papers
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