Haoran Cheng
Papers
1
Total Citations
13
H-Index
1
About
Haoran Cheng is a researcher at the forefront of rehabilitation robotics and human-robot interaction, with a focused expertise in biosignal processing and neural network applications for assistive technologies. His key research areas include surface electromyography (sEMG) analysis, lower limb exoskeleton control, and real-time motion estimation. Cheng’s most notable contribution is the development of a real-time knee joint angle estimation method that leverages sEMG signals and Back Propagation Neural Networks (BPNN), a breakthrough aimed at enhancing the continuous motion control of lower limb rehabilitation exoskeletons. This work, published in 2021 and garnering 13 citations, demonstrates his ability to bridge the gap between biological signals and robotic actuation, enabling more intuitive and responsive human-robot interaction. By training BPNN to map sEMG patterns to joint kinematics, Cheng has provided a foundation for adaptive, user-specific rehabilitation devices that can adjust in real time to a patient’s movements. His research holds significant promise for improving the quality of life for individuals with mobility impairments, marking him as an emerging innovator in the field of neurorehabilitation engineering.
Research Focus
Key Achievements
Top Papers
- 1