PhD Research Studentships

Bio-Signals based Control of Soft Assistive Robots

Supervisor: Thilina DULANTHA LALITHARATNE
Apply by:29 January 2025
Start in:September (Semester 1)

Description

Adaptability, resilience, flexibility, and inherent safety in soft robotics approaches, in contrast to their rigid robotic counterparts, offer significant benefits for developing assistive robots. This project aims to investigate how soft assistive robots, such as soft exoskeletons for motion assistance, rehabilitation, and prosthetics, can be designed, developed, and controlled using the user’s motion intention. Among the different methods to detect motion intention, we will explore how bio-signals, such as muscle signals (Electromyography (EMG)) and/or brain signals (using Electroencephalography (EEG)), can be used to detect motion intention and ultimately control soft assistive robots.

Funding

Funded by: China Scholarship Council
Candidate will need to secure a CSC scholarship.
Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses and one return flight ticket to successful applicants.

Eligibility

  • The minimum requirement for this studentship opportunity is a good honours degree (minimum 2(i) honours or equivalent) or MSc/MRes in a relevant discipline.
  • If English is not your first language, you will require a valid English certificate equivalent to IELTS 6.5+ overall with a minimum score of minimum score of 6.0 in each of Writing, Listening, Reading and Speaking).
  • Candidates are expected to start in September (Semester 1).

Contact

For informal enquiries about this opportunity, please contact Thilina DULANTHA LALITHARATNE.

Apply

Start an application for this studentship and for entry onto the PhD Mechanical Engineering full-time programme (Semester 1 / September start):

Apply Now »

Please be sure to quote the reference "SEMS-PHD-644" to associate your application with this studentship opportunity.

Related website:https://www.sems.qmul.ac.uk/staff/t.dulanthalalitharatne
SEMS Research Centre:
Bioengineering
Keywords:Artificial Intelligence, Human Computer Interaction, Machine Learning, Cybernetics, Mechatronics, Robotics, Neural Engineering