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Performance evaluation of AI and IoT enabled Smart Wheelchair


   Computing, Engineering & Physical Sciences

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  Dr M Shakir, Dr Tony Leslie, Dr C Ugbolue  No more applications being accepted  Funded PhD Project (European/UK Students Only)

About the Project

This is a joint PhD program between University of the West of Scotland (UWS) and Phoenix Instinct Ltd. Phoenix Instinct is an award-winning design house for mobility solutions, focusing on the development of user-friendly, practical, and life-enhancing products for wheelchair users. The company has just finished a Knowledge Transfer Partnership (KTP), KTP11724, with UWS on the design of an ultra-lightweight carbon fibre wheelchair with intelligent centre of gravity control. The prototype design won the Global Toyota Mobility Challenge competition in December 2020, along with a prize of $1-m. Find out more at Ultra-Lightweight Intelligent Wheelchair Receives $1M as Winner of Mobility Unlimited Challenge is Announced. The company has just started a further Innovate UK funded KTP, KTP12924 with UWS for integrating the existing hardware such as power assist wheels and intelligent centre of gravity mechanism further with the internet of things enabled sensors and embedded systems for reconfigurable and scalable design.

There is a paucity of research and development on how the newly developed intelligent centre for gravity mechanism and power assisted wheel can improve the user experience for further development. This joint studentship project will evaluate the performance and impact on the user of the centre of gravity and power assisted wheels based on data analysis and apply artificial Intelligence to learn from user’s behaviour such as posture, health vitals and provide guidance on improved user experience when using centre of gravity and power assisted wheels. 

Our vision is to improve the user experience and deliver a fully tested and true smart wheelchair ready for market supporting centre of gravity and power assisted wheels. This project will be one of the first efforts to develop the framework for performance evaluation of the centre of the gravity and power assisted wheels based on electromechanical stress testing and artificial intelligence and advanced data analysis. In this project, we will design and develop artificial intelligence enabled algorithms for predicting comfort of the users based on physiological sensors such as respiratory and metabolism rates, autonomic nervous parameters such as heart rate and blood pressure and 3D coordinate posture parameters such as good or bad and guide the users under various scenarios.  

Candidates should hold a first- or second-class honors or a master’s degree in computer science/computer engineering/electrical and electronic engineering/biomedical engineering or other relevant disciplines or have equivalent industry experiences. It is essential that the applicant has very good skills in computer programming (e.g., Python and C/C++) and good knowledge in electro-mechanical systems, data science, IoT, artificial intelligence and machine learning, and mathematical modelling.

In the first instance, any informal enquiries and resume, research publications, and other documents should be submitted by email to Dr. Muhammad Zeeshan Shakir ([Email Address Removed]). Successful applicants will be asked to submit the application through the UWS online system


Funding Notes

The University of the West of Scotland (UWS) is seeking to attract a PhD candidate of outstanding ability and commitment to join its vibrant and growing programme of internationally excellent research. The successful applicant will receive an annual stipend and payment of tuition fees for 3 years.
The studentship is open to UK citizens and EU applicants with pre-settled or settled status, it is also open to international applicants if they can cover the difference between Home and International fees for the duration of the programme of study.
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