Sheng Quan Xie

Chair Professor

University of Leeds

United Kingdom

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Sheng Quan Xie is a Chair Professor at the University of Leeds in the UK. His research focuses on rehabilitation robotics, multimodal sensor systems, and privacy-preserving technologies. Recent articles include investigations into knee exoskeletons, pneumatic artificial muscles, and machine learning applications for stroke rehabilitation. He is committed to advancing technologies that improve patient outcomes in rehabilitation.

Articles (20)

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2025

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2023

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2023

Collaborators (6)

Yue Zhang

University of Bath

UNITED KINGDOM

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Zhi-Qiang Zhang

University of Leeds

UNITED KINGDOM

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Manoj Sivan

Associate Clinical Professor in Rehabilitation Medicine

University of Leeds

UNITED KINGDOM

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Zhenhong Li

The University of Manchester

UNITED KINGDOM

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Samit Chakrabarty

Lecturer in Neuroscience

University of Leeds

UNITED KINGDOM

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Yanxin Zhang

University of Auckland

NEW ZEALAND

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Sheng Quan Xie

Research Interests

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About

Articles (20)

Privacy-Preserving Approach for Early Detection of Long-Lie Incidents: A Pilot Study with Healthy Subjects

Analysis of Multimodal Sensor Systems for Identifying Basic Walking Activities

Model Predictive Control with Optimal Modelling for Pneumatic Artificial Muscle in Rehabilitation Robotics: Confirmation of Validity Though Preliminary Testing

A Twisting Mechanism With Parallel Springs for Series Variable Stiffness Actuator

Novel Design on Knee Exoskeleton with Compliant Actuator for Post-Stroke Rehabilitation

The Design and Adaptive Control of a Parallel Chambered Pneumatic Muscle-Driven Soft Hand Robot for Grasping Rehabilitation

VR-Aided Ankle Rehabilitation Decision-Making Based on Convolutional Gated Recurrent Neural Network

A Piecewise Particle Swarm Optimisation Modelling Method for Pneumatic Artificial Muscle Actuators

A Task-Oriented Grasping Framework Guided by Visual Semantics for Mobile Manipulators

A novel scoring approach for the Wolf Motor Function Test in stroke survivors using motion-sensing technology and machine learning: A preliminary study

An EMG-driven musculoskeletal model for estimation of wrist kinematics using mirrored bilateral movement

Boosting Personalized Musculoskeletal Modeling With Physics-Informed Knowledge Transfer

Data-Driven Adaptive Iterative Learning Control of a Compliant Rehabilitation Robot for Repetitive Ankle Training

A Lightweight Series Elastic Actuator With Variable Stiffness: Design, Modeling, and Evaluation

Adaptive Cooperative Control Strategy for a Wrist Exoskeleton Using Model-Based Joint Impedance Estimation

Commercial device-based hand rehabilitation systems for stroke patients: State of the art and future prospects

Computationally Efficient Personalized EMG-Driven Musculoskeletal Model of Wrist Joint

Cross-Subject Transfer Learning for Boosting Recognition Performance in SSVEP-Based BCIs

Design optimization and redundant actuation selection for an efficient assistive robotic exoskeleton

Enhanced compensation control of pneumatic muscle actuator with high-order modified dynamic model

Collaborators (6)

Yue Zhang

Zhi-Qiang Zhang

Manoj Sivan

Zhenhong Li

Samit Chakrabarty

Yanxin Zhang

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