Papers
13
Total Citations
167
H-Index
7
About
Yali Liu is a robotics and rehabilitation engineering researcher whose work spans human-robot interaction, exoskeleton systems, and the emerging frontier of industrial metaverse technologies. With expertise bridging biomechanics and intelligent robotics, Liu has made significant contributions to upper limb rehabilitation robotics, developing end-effector systems that deliver customizable training for hemiplegic stroke patients and quantitative motor function assessment tools — work that has collectively garnered over 37 citations. Liu's research into lower-limb exoskeletons is particularly notable, encompassing locomotion mode recognition using hierarchical support vector machines, IMU-based gait event detection, and continuous joint torque prediction — demonstrating a comprehensive systems-level approach to assistive robotics. Complementary biomechanical investigations, such as analyzing backpack load effects on muscle activation during slope walking, reflect a strong grounding in human movement science. More recently, Liu has pioneered XR-based human-robot collaborative assembly systems within industrial metaverse frameworks, including multi-agent trust evaluation mechanisms, earning 57 citations across these cutting-edge contributions. With over 160 total citations, Liu represents a researcher successfully connecting clinical rehabilitation, intelligent control systems, and next-generation human-machine collaboration paradigms.
Research Focus
Key Achievements
Top Papers
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- 3Effects of Backpack Loads on Leg Muscle Activation during Slope Walking23 citations · 2020
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- 5FSM-HSVM-Based Locomotion Mode Recognition for Exoskeleton Robot13 citations · 2022
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- 10Continuous Prediction of Lower-Limb Joint Torque Based on IPSO-LSTM6 citations · 2022