Xiaokai Chen
Papers
1
Total Citations
36
H-Index
1
About
Xiaokai Chen is a leading researcher in neurorehabilitation, with a primary focus on brain-computer interfaces (BCIs) and robotic systems for post-stroke motor recovery. His most cited work, a 2022 meta-analysis and systematic review, rigorously evaluated the clinical effects of BCI-robot combinations on upper-limb function. By synthesizing data from multiple clinical studies, Chen demonstrated that these integrated systems can significantly induce neurological recovery and improve motor function in stroke survivors. This seminal paper, garnering 36 citations, has become a foundational reference for clinicians and engineers developing next-generation rehabilitation technologies. Chen’s contributions bridge the gap between neural engineering and practical therapy, offering evidence-based insights that guide the design of more effective, patient-centered interventions. His work not only advances the scientific understanding of BCI-driven plasticity but also provides a roadmap for translating these technologies into routine clinical practice. For students and researchers, Chen’s research exemplifies how rigorous meta-analytical methods can validate emerging neurotechnologies, making him a pivotal figure in the quest to restore motor function after neurological injury.
Research Focus
Key Achievements
Top Papers
- 1