Papers
5
Total Citations
78
H-Index
4
About
Xiaoqin Duan is a leading researcher in rehabilitation robotics and human–machine interaction, whose work focuses on restoring mobility for individuals with stroke and lower-limb motor dysfunction. Her core contributions lie in developing intelligent control systems that enable lower-limb rehabilitation robots to adapt to real-world disturbances and to decode human movement intent from surface electromyography (sEMG) signals. Duan’s pioneering 2021 paper on adaptive iterative learning control, with 35 citations, introduced a human-in-the-loop framework that significantly improves robot stability and patient safety during therapy. She has also advanced neural-network-based methods for continuous motion estimation from incomplete sEMG data—a critical innovation given the prevalence of sensor malfunctions and signal dropouts in clinical settings. Her 2024 work in this area, garnering 18 citations, demonstrates how recurrent neural networks can reliably predict joint movements even with missing inputs. Beyond hardware control, Duan has contributed to the evidence base for computerized cognitive assessment in stroke patients through a systematic review (2023), highlighting her interdisciplinary approach. With a growing citation impact and a clear focus on translating neural engineering into practical rehabilitation solutions, Duan is shaping the future of intelligent, patient-responsive assistive technology.
Research Focus
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Top Papers
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