Zhengxue Cheng
Papers
2
Total Citations
20
H-Index
2
About
Zhengxue Cheng is a researcher whose work centers on the intersection of biomechanics, wearable sensing, and human motion analysis, with a particular focus on gait phase detection. Her major contributions lie in developing innovative, non-invasive methods to identify critical gait events—such as heel-contact and foot-off states—using muscle deformation signals rather than traditional inertial or electromyographic sensors. This approach offers a simpler, more robust alternative for applications like synchronous robotic assistance, rehabilitation training, and health monitoring. Her most-cited paper, "Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration" (2021), has garnered 12 citations, while her earlier work, "Heel-Contact Gait Phase Detection Based on Specific Poses with Muscle Deformation" (2019), has 8 citations, demonstrating a growing impact in the field. Notably, her research addresses a key challenge in gait analysis: achieving accurate, real-time detection without complex calibration or bulky equipment. By leveraging muscle deformation patterns, Cheng’s work paves the way for more intuitive and accessible wearable technologies, making her a promising voice in advancing human-robot interaction and clinical gait assessment.
Research Focus
Key Achievements
Top Papers
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