Algorithms aid prosthetics development

Engineers from Cambridge University, along with neuroscientists at Stanford University in the US, believe that current decoding approaches are not capable of producing a clinically viable prosthetic device with the speed and accuracy comparable to a healthy human arm.

Principal investigator Zoubin Ghahramani, a professor of information engineering at Cambridge, said the challenge is that neural prosthetic designers do not completely understand how movements are represented in the brain.

‘Neurons are noisy information channels,’ he said. ‘So you get activity from many, many neurons spiking and it is a challenge to infer the desired action and direction of movement.

‘There have been advances in the field over the last decade or so but the methods people have used have generally been fairly simple linear filtering methods for decoding neural activities.

‘The main thing we’re hoping to contribute is much more advanced machine-learning methods.’

The £410,000 EPSRC-funded research project will create an intelligent algorithm that is more adaptive than current decoding mechanisms.