Yi Fang Chen

Papers

Total Citations

H-Index

About

Yi Fang Chen has made notable contributions to human-robot interaction and intelligent sensing systems, with a particular focus on posture recognition technologies. Their most cited work, "Design of a Kinect Sensor Based Posture Recognition System" (2014), which has garnered 6 citations, pioneered the integration of Kinect 3D sensors with self-organizing maps (SOM) algorithms to create intuitive, gesture-based interfaces for robotic control. This research demonstrated how semaphore signals and depth-sensing technology could enable natural, non-verbal communication between humans and machines—a critical advancement in assistive robotics and interactive systems. Chen’s work stands out for its practical approach to bridging the gap between complex sensor data and real-time, user-friendly applications. By leveraging affordable, off-the-shelf hardware like the Kinect, their research has made posture recognition more accessible for prototyping and educational purposes. While their citation count reflects a focused, early-career impact, the foundational nature of this work continues to inform studies in gesture-based control and adaptive human-robot collaboration. Chen’s contributions exemplify how combining machine learning with sensor fusion can unlock new possibilities in intuitive human-machine interfaces.