Yueting Yuan
Papers
2
Total Citations
6
H-Index
2
About
Yueting Yuan is a researcher at the forefront of brain-computer interface (BCI) technology, with a focused expertise in decoding human movement intentions from electroencephalography (EEG) signals. Her primary research areas include neural signal processing, gait analysis, and the development of intelligent rehabilitation and assistive robotics. Yuan’s major contributions lie in advancing the detection of sitting and standing intentions, which are fundamental yet challenging actions for hybrid rehabilitation systems. She has pioneered the use of dynamical region connectivity and entropy-based complexity measures to analyze EEG features, enabling more reliable classification of these basic gait intentions. Her work, notably detailed in her 2023 paper “Sitting and Standing Intention Detection Based on Dynamical Region Connectivity and Entropy of EEG” (4 citations) and her 2022 study on EEG signal complexity (2 citations), directly addresses the core challenge of predicting user intent in real-time for intelligent walking aid robots. By improving the accuracy and robustness of intention detection, Yuan’s research is paving the way for more responsive, user-centric assistive technologies that can significantly enhance mobility and independence for individuals with motor impairments.
Research Focus
Key Achievements
Top Papers
- 1
- 2