Gengliang Lin
Papers
3
Total Citations
11
H-Index
2
About
Gengliang Lin’s research lies at the intersection of assistive robotics, brain-machine interfaces (BMI), and computer vision, with a primary focus on improving the quality of life for stroke survivors. His most impactful work, an assistive mobile robot system published in 2020 (6 citations), introduces a shared control framework that integrates BMI for user intention detection with computer vision for autonomous navigation, enabling patients with severe motor impairments to command a robot with minimal effort. Building on this, Lin developed a vision-based compensation detection approach for robotic stroke rehabilitation therapy (2021, 3 citations), offering a convenient, non-intrusive method to identify compensatory movements that hinder motor recovery—a significant improvement over complex, interference-prone prior systems. Additionally, his design and control of a seven degrees-of-freedom semi-exoskeleton upper limb robot (2021, 2 citations) demonstrates his expertise in creating adaptable, wearable robotic platforms for targeted therapy. With a total of 11 citations across these key papers, Lin’s contributions are notable for their practical, patient-centered approach, directly addressing real-world challenges in rehabilitation and assistive technology.
Research Focus
Key Achievements
Top Papers
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