Wang Meng
Papers
1
Total Citations
11
H-Index
1
About
Wang Meng is a leading researcher in the field of wearable robotics, with a primary focus on exoskeleton control and human-robot interaction. Their most cited work, "Research on Gait Recognition and Prediction of Exoskeleton Robot Based on Improved DTW Algorithm" (2020, 11 citations), introduces a novel approach to real-time gait phase identification using an enhanced Dynamic Time Warping algorithm. This contribution is critical for enabling intuitive follow-up control in lower-limb exoskeletons, allowing robots to accurately match human motion intent. By developing a gait data measurement system that precisely captures and predicts movement patterns, Wang has advanced the practical deployment of assistive devices for rehabilitation and mobility support. Their research bridges the gap between algorithmic efficiency and real-world biomechanical applications, offering a foundation for more responsive and adaptive exoskeleton systems. Wang’s work is particularly notable for its emphasis on real-time performance, a key challenge in wearable robotics, and continues to influence studies in gait analysis and human-robot synchronization.
Research Focus
Key Achievements
Top Papers
- 1