Find the code that could predict epilepsy Tuesday, 06 September 2016

University of Melbourne engineers are joining a global race to develop an algorithm that can predict epileptic seizures.

The University is joining forces with US analytics and predictive modelling platform Kaggle, dubbed the online 'stadium' of data science, in partnership with the University of Pennsylvania and the Mayo Clinic to crowdsource a solution.

Teams will be able to crunch human brainwave data spanning six months to three years. Until now, international researchers have only been able to work on data taken over a period of two weeks.

Professor David Grayden is Leader of the Bionics Laboratory in the University's Centre for Neural Engineering and part of the team developing the Stentrode device, which can record brain signals from within a blood vessel next to the brain and pass them wirelessly through the skin where they could be used to control an exoskeleton for people with movement issues. He hopes it could also be used to predict and control epilepsy.

“Researchers have until now only had a two-week window to extract brainwave data from electrodes, when people with epilepsy go into hospital,” he said.

“That’s typically allowed access to data from up to 10 seizures. We can now offer data on dozens of seizures measured over a longer period. This is the only dataset with an adequate amount of data to accurately evaluate seizure prediction algorithms in humans.”

The data was obtained using an implantable device developed by Seattle-based startup NeuroVista. The University of Melbourne has hosted the world’s only clinical trial of the device.

The contest is being run by the University in conjunction with the American Epilepsy Society, the National Institutes of Health and US software firm MathWorks, which has developed a tool that will be offered to contestants.

Contestants will vie for up to US$20,000 in prize money. Teams will have just under three months to pore over 60GB of data, taking in intervals both before and between seizures.

The winners will share their algorithms online via Kaggle and the findings will be presented at the next American Epilepsy Society annual meeting in December.

[The data will include measurements of brain activity in the lead up to seizures. Image: University of Melbourne]