Simon Stuttaford

Email: [email protected]

Project title

Enhancing the control of prosthetic hands

Supervisors

• Dr Kianoush Nazarpour
• Dr Matthew Dyson

Project description

We are investigating factors and situations that affect the ability to control a prosthesis. We are looking at the extent that these factors influence a novel control scheme. The scheme is currently under development.

In an ideal scenario, the controller should be able to learn from the environment in which it is working to adapt accordingly in real-time. We will enhance the quality of upper-limb prosthetic control by developing an adaptive prosthetic limb.

Methodology and objectives

We will test the new control scheme with people who have limb difference. The tests will take place under a variety of conditions. We know that these conditions deteriorate control using clinical and commercially available systems.

We will develop real-time data analytics methods. These methods will identify when detrimental conditions occur. They will also be able to predict effects on prosthesis control.

Based on this information, we will develop adaptive algorithms to improve control in real time.

Result

We will empower users by providing reliable and robust control of their prosthesis, helping to minimise the effect of limb loss. This will dramatically improve their quality of life.

Interests

Neural constraints on learning, machine learning.

Qualifications

• BSc Mathematics, MSc Biomedical Engineering – both from Newcastle University