Huanghe Zhang
Papers
5
Total Citations
44
H-Index
3
About
Huanghe Zhang is a researcher at the forefront of wearable robotics and autonomous gait analysis, with a focus on improving human locomotion tracking and balance assessment. His major contributions include developing an autonomous gait analysis system that integrates a mobile robot with custom-engineered instrumented insoles, featuring inertial sensors and force-sensitive resistors—a novel approach that addresses the need for real-world, unconstrained monitoring. Zhang also advanced the accuracy of wearable sensors for human locomotion tracking by introducing phase-locked regression models to mitigate sensor drift and IMU-to-segment misalignment, critical for soft robotic systems. His work on mobile robot-assisted gait monitoring enables continuous estimation of the Dynamic Margin of Stability, a key metric for fall risk assessment. With over 44 citations across his top papers, Zhang’s research has significant impact in rehabilitation and assistive technologies. Notable achievements include his 2020 paper on autonomous gait analysis and his 2022 study on dynamic stability estimation, both of which demonstrate his innovative integration of robotics and wearable sensors. His recent work extends to campus security inspection robots using YOLO algorithms and machine learning models for gait phase detection via surface electromyography signals, showcasing his versatility in applying AI to human-robot interaction.
Research Focus
Key Achievements
Top Papers
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- 4Campus Security Inspection Robot Based on YOLO Algorithm2 citations · 2024
- 5