An upper-limb rehabilitation exoskeleton robot based on AI and cloud computing.

The project

The aim of the project is to develop a new generation of robotic exoskeleton that will benefit stroke patients by providing advanced functionality to enable remote but active rehabilitation.

This will be achieved by the integration of artificial intelligence, virtual reality and cloud computing. The project will introduce novel sensors to recognise post-stroke patients’ motion intention. The signals collected from the patients will be sent to a cloud-based data processing centre where the centralised database AI service can be accessed by all functional units.

This will guide the robot movements, monitor the patient’s progress and can be used to provide expert assistance remotely. The project will have a virtual reality interface for performing activities of daily living which will be trialled on stroke patients and can be used in addition to conventional therapy to increase treatment intensity for improved recovery.

Our focus

Our focus is to provide more engaging rehabilitation with the use of a new generation of upper-limb exoskeleton to improve efficiency and provide additional intervention that has the potential to improve outcomes and independence. The objective is to benefit post-stroke patients through the intensive training in the typical activities of daily living. The goal is to reduce long-term dependency on rehabilitation care and improving the cost-efficiency of treatment.

Logo of the European cross-border cooperation programme, Interreg France (Channel) England

AiBle is a 3-year UK/France cross-border EU Interreg project to improve the recovery experience of stroke patients with better treatment effects and efficiency by developing an upper-limb rehabilitation exoskeleton robot based on AI and cloud computing.

The total amount of EU Financial Funding received is: €4,875,139.99 of which €3,333,849.26 has been co-financed by the European Regional Development Funds.

The project aims to:

  • help stroke patients to benefit from remote and active rehabilitation
  • increase the intensity and repetitions through the use of the robot which will lead to improved upper limb outcomes
  • contribute to the wellbeing of stroke patients and social care in the Channel region
  • increase the delivery and uptake of novel robot-enhanced rehabilitation for stroke patients in hospitals and rehabilitation centres

Principle Investigator

Image of Dr Zhaojie Ju

Dr Zhaojie Ju

  • Job Title Reader in Machine Learning and Robotics
  • Email Address
  • Department School of Computing
  • Faculty Faculty of Technology
  • PhD Supervisor PhD Supervisor

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