Papers
58
Total Citations
1,631
H-Index
20
About
Qingsong Ai is a distinguished researcher whose work sits at the intersection of rehabilitation robotics, intelligent control systems, and human-machine interaction. Based at the forefront of assistive technology research, Ai has made seminal contributions to robot-assisted rehabilitation for both lower and upper limbs, with his 2015 review on mechanisms and control strategies for lower limb rehabilitation becoming a landmark reference in the field, amassing over 460 citations. His work spans the full spectrum of rehabilitation engineering — from designing compliant, pneumatic muscle-driven ankle rehabilitation robots with advanced backstepping sliding mode control, to developing robust iterative feedback tuning techniques for repetitive training protocols. Ai has pioneered the integration of machine learning and biosignal processing into rehabilitation systems, leveraging EMG-driven musculoskeletal models, brain-computer interfaces, and attention-based deep learning architectures to decode patient movement intention with greater accuracy. His explorations into flexible wearable sensors and muscle fatigue classification further demonstrate a commitment to intelligent, patient-adaptive rehabilitation. Collectively, his publications have garnered over 1,100 citations, underscoring his profound and growing influence on next-generation rehabilitative technologies.
Research Focus
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