Meikui Deng
Papers
2
Total Citations
128
H-Index
2
About
Meikui Deng is a leading researcher at the intersection of rehabilitation engineering and risk analysis, whose work is shaping the future of stroke recovery and system safety. Her primary research areas include robot-assisted neurorehabilitation, human-robot embodiment, and advanced risk assessment methodologies. Deng’s most significant contribution is her pioneering integration of mirror visual feedback with robotic training, demonstrating through a randomized controlled study that this approach significantly facilitates motor recovery after stroke by enhancing the patient’s sense of embodiment. This work, cited 34 times, challenges conventional robotic therapy designs. Complementing this, her highly cited 2022 paper (94 citations) introduces a novel risk assessment framework that combines Failure Mode and Effects Analysis (FMEA) with Data Envelopment Analysis (DEA) and cloud models, applied to robot-assisted rehabilitation systems. This dual focus—advancing both therapeutic efficacy and system safety—positions her as a unique voice in the field. Deng’s research not only improves clinical outcomes but also provides engineers with robust tools to evaluate and mitigate risks in complex rehabilitation technologies, making her work essential reading for students and researchers in biomedical engineering and patient safety.
Research Focus
Key Achievements
Top Papers
- 1
- 2