Hao Cui
Papers
1
Total Citations
29
H-Index
1
About
Hao Cui is a researcher focused on the intersection of computer vision, human behavior analysis, and health informatics. His primary research areas include posture recognition, scene understanding, and semantic analysis for assistive technologies and human-robot interaction. Cui’s most notable contribution is his pioneering work on automatic detection of unhealthy sitting postures during screen-reading, which addresses a critical public health concern—prolonged poor posture leading to lumbar disease, cervical issues, and myopia. His 2018 paper, “A Scene Recognition and Semantic Analysis Approach to Unhealthy Sitting Posture Detection during Screen-Reading,” has garnered 29 citations, reflecting its impact on both robotics and healthcare communities. By integrating scene recognition with semantic analysis, Cui developed a vision-based system that can intelligently identify harmful postures without intrusive sensors, advancing non-invasive health monitoring. This work has implications for smart office environments, ergonomic interventions, and robotic systems designed to promote well-being. Cui’s research bridges computer vision and practical health solutions, making him a notable figure in applied behavior analysis and assistive robotics.
Research Focus
Key Achievements
Top Papers
- 1