Papers
1
Total Citations
101
H-Index
1
About
Yunli Fan is a leading researcher at the intersection of neural engineering and rehabilitation robotics, with a primary focus on developing brain-computer interface (BCI) systems for post-stroke motor recovery. Her most cited work, the 2022 study on an SSVEP-based BCI-controlled soft robotic glove for hand function rehabilitation (101 citations), represents a significant contribution to assistive technology. This research demonstrates how combining steady-state visual evoked potentials with soft robotics can create intuitive, real-time control systems for neural rehabilitation. Fan's work addresses a critical gap in stroke therapy by enabling patients with severe motor impairments to actively engage in hand function training through direct brain-to-device communication. Her approach integrates non-invasive EEG signal processing with compliant robotic actuators, offering a safer and more adaptable alternative to rigid exoskeletons. By validating this system's effectiveness in improving hand motor function, Fan has provided a practical pathway for translating BCI technology from laboratory settings to clinical rehabilitation. Her research continues to push boundaries in human-machine interfaces, with potential applications extending beyond stroke recovery to broader neuroprosthetic and assistive device domains.
Research Focus
Key Achievements
Top Papers
- 1