Papers
4
Total Citations
33
H-Index
3
About
Juanhong Yu is a pioneering researcher at the intersection of brain-computer interfaces (BCIs) and neurorehabilitation, specializing in multimodal systems that integrate electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Her major contributions lie in developing personalized, hybrid BCI frameworks that harness both electrical and hemodynamic brain signals to improve motor recovery for individuals with neurological conditions. Notably, her 2025 work on a multimodal BCI–soft robotics system for chronic stroke patients (9 citations) demonstrates a practical, closed-loop rehabilitation tool that adapts to individual neural patterns. Earlier, she established the feasibility of calibrating motor imagery BCIs using passive movement (2013, 18 citations), a foundational insight that reduces training burden for users. Her research also extends to challenging populations, as seen in her study on increased theta oscillations during motor imagery in late-stage ALS (2018, 3 citations), highlighting cognitive engagement even in severe paralysis. Through her investigations of cortical activation patterns using fNIRS (2014, 3 citations), Yu has advanced our understanding of sensorimotor function, bridging passive and active movement paradigms. Her work is instrumental in making BCIs more accessible and effective for clinical rehabilitation, earning her recognition as a key innovator in assistive neurotechnology.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4