A research team at the University of Alberta's Bionic Limbs for Improved Natural Control lab is developing an artificial arm using AI/machine learning aimed at trying to blur the lines between the person who 'needs assistive technology and the assistive technology itself.'
Lead Research Engineer Michale Rory Dawson, left, sets up a task for research participant Chris Neilson to perform with the Bento Arm, centre, while Patrick Pilarski, who is the Canada Research Chair in machine Intelligence for Rehabilitation, gives it a cup to hold at the University of Alberta's BLINC lab in Edmonton, Alberta, on Thursday March 14, 2019.
"They may have lost a limb through injury or illness and the technology itself is in some ways trying to replace that body part," says Pilarski, Canada research chair in machine intelligence for rehabilitation. With Neilson's current artificial limb, he operates the hand's open-close and grip functions by contracting bicep or tricep muscles. Sensors measure electrical changes in the skin, sending signals to trigger movements in the hand.
Calling manual control of an artificial limb a painstaking process, he explains that the idea of an AI-enhanced bionic arm is to remove some of the burden from the wearer by making complex hand movements more automatic. Its Centre for Healthcare Analytics Research and Training was created to design and implement innovative programs using AI/machine learning to streamline certain hospital systems and to improve care, from decreasing emergency department wait times to predicting which patients could take a turn for the worse -- and when.
All the data was fed in to create an algorithm -- a set of rules telling a computer how to perform a task -- using a combination of methods that included machine learning, he says. "And we found that we could predict with well over 90 per cent accuracy our patient volumes ... in six-hour intervals, three days in advance.
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