IET Peter Wells Memorial Lecture

Synopsis

With the increasing popularity of AI, machine learning is considered the most likely candidate to enable the control of next-generation multi-articulated prosthetic hands.

Dr Nazarpour will explore why it has been challenging to translate machine learning-based prosthetic control beyond the laboratory. He will offer a parallel human-learning prosthetic-control paradigm that offers much more flexibility than existing machine learning algorithms. With supporting early results, he will discuss why the development of human-in-loop machine learning for prosthetic control is possible and timely and how we have set out to achieve it.