Papers
3
Total Citations
19
H-Index
2
About
Zhikai Wei is a rising researcher at the intersection of human-robot interaction, assistive robotics, and neural engineering, whose work is pioneering more intuitive and adaptive control systems for prosthetic and rehabilitation devices. His primary research areas include biofeedback-driven co-adaptation, multimodal intention recognition, and user-centered design for upper-limb prosthetics. Wei’s most cited work, “Bridging Human-Robot Co-Adaptation via Biofeedback for Continuous Myoelectric Control” (2023, 11 citations), introduces a novel framework that dynamically aligns human and robotic learning for robust intent recognition using electrophysiological signals—a critical step toward seamless neural prosthetic control. He further advanced this field with “Learning Multimodal Confidence for Intention Recognition in Human-Robot Interaction” (2024, 6 citations), which enhances reliability in collaborative robotics for elderly assistance. Notably, Wei’s team achieved competitive success at CYBATHLON 2024 with the “HANDSON Hand,” demonstrating practical excellence in assistive technology evaluation. With a growing citation impact and a focus on translating neural signals into real-world robotic assistance, Zhikai Wei is shaping the future of human-robot co-adaptation for inclusive, intelligent assistive systems.
Research Focus
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Top Papers
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