Papers
2
Total Citations
22
H-Index
2
About
Peiwen Fu is a rising researcher in the field of rehabilitation robotics and human-machine interaction, with a focus on lower-limb exoskeletons and assistive devices. Their key research areas include locomotion mode prediction, human-exoskeleton alignment, and adaptive control strategies for walking-assistive technologies. Fu’s most notable contribution is the development of a multidimensional feature learning framework from surface electromyography (sEMG) signals to predict continuous locomotion modes, such as level walking and stair ascent, enabling more intelligent and transparent control of robotic exoskeletons. This work, published in 2024, has already garnered 19 citations, reflecting its timely impact on advancing proactive control in assistive robotics. Additionally, Fu addressed a critical safety concern in rehabilitation by designing an RPR (revolute-prismatic-revolute) mechanism-based device to reduce human-exoskeleton knee joint misalignment, a common cause of discomfort and injury. This 2022 study, with 3 citations, underscores Fu’s commitment to improving wearer safety and natural movement. By bridging signal processing, biomechanics, and mechanical design, Fu’s research holds promise for enhancing the autonomy and comfort of next-generation exoskeletons, making them more practical for clinical and daily use.
Research Focus
Key Achievements
Top Papers
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