Guanghui Yan

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About

Guanghui Yan is a researcher at the forefront of brain-computer interfaces (BCI) and neural signal processing, with a focus on decoding human intention for rehabilitation robotics. His work centers on using electroencephalography (EEG) to analyze brain activity patterns, particularly in the contexts of pain empathy and gait intention detection. Yan’s major contributions include pioneering the use of functional connectivity analysis to explore how humans empathize with pain in both humans and robots—a study that has garnered 15 citations and opened new avenues in human-robot interaction. He has also advanced BCI-based rehabilitation systems by developing methods to detect sitting and standing intentions from EEG signals, employing dynamical region connectivity and entropy measures to improve classification accuracy. His research on the complexity of EEG signals for action intention prediction has laid groundwork for intelligent walking aid robots. With a growing citation impact, Yan’s work bridges neuroscience and engineering, offering practical solutions for assistive technologies. His achievements highlight a commitment to enhancing mobility and quality of life for individuals with motor impairments through innovative neural decoding techniques.