Yingxin Yu
Papers
2
Total Citations
12
H-Index
2
About
Yingxin Yu is a pioneering researcher in the field of brain–machine interfaces (BMIs), with a specific focus on power augmentation systems for upper limbs. Her work centers on decoding neural signals to enhance human physical capabilities, bridging the gap between assistive technology for disabled individuals and performance augmentation for healthy users. Yu’s most cited paper, “EEG-Based EMG Estimation of Shoulder Joint for the Power Augmentation System of Upper Limbs” (2020, 10 citations), introduces a novel method for estimating electromyographic activity from electroencephalography (EEG) signals, enabling intuitive control of external devices. This contribution addresses critical limitations in current BMI systems by improving signal reliability and real-time responsiveness. In her pilot study on neurofeedback training (2021, 2 citations), Yu explores how targeted EEG band modulation can enhance users’ ability to generate consistent control signals, laying groundwork for more effective BMI training protocols. Her research has significant implications for rehabilitation robotics, exoskeletons, and human augmentation technologies. By combining neurofeedback techniques with BMI control, Yu is advancing the practical deployment of wearable neural interfaces, making her a rising voice in the intersection of neuroscience and engineering.
Research Focus
Key Achievements
Top Papers
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- 2