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Recommended Watching: BLINC Lab aims to create more intuitive artificial limbs

The BLINC Lab – a lab whose goal is to create more natural, intuitive artificial limbs for people with amputations– has recently been profiled in a piece by Edmonton Global.

Co-led by Dr. Jacqueline Hebert, MD (Professor, University of Alberta) and Dr. Patrick Pilarski, PhD (Fellow, Canada CIFAR AI Chair at Amii; Associate Professor, University of Alberta), the interdisciplinary lab explores how to improve sensory motor control and integration of advanced prosthetic and robotic systems. Its multiple lines of complementary research are aimed at improving the science and art of prosthetic restoration and rehabilitation robotics.

"We believe the tool should also learn about the person, and that it should adapt and change and improve as the person uses it during their daily life."

Patrick Pilarski

"The common perspective on artificial limbs is that they’re a tool, and that a person has to learn to use that tool," explains Pilarski. "Here at the BLINC Lab … [we] believe the tool should also learn about the person, and that it should adapt and change and improve as the person uses it during their daily life."

Reinforcement learning – a branch of machine learning that enables AI systems to learn through experience – plays a key role in this research, allowing the artificial limbs to “learn” and adapt, becoming more effective through interactions with the user.

Pilarski also spoke about the work going on at the BLINC Lab in a recent interview with CTV Edmonton. He noted that much of the technology they develop is open source to make collaboration with other researchers as seamless as possible.

"We want people around the world to be able to use it, regardless of their geographic region .. to let people with amputations have devices that truly let them live the lives they want to live," he said.

Learn more about the BLINC Lab and their work in this video by Edmonton Global:


Learn how Amii advances world-leading artificial intelligence and machine learning research: visit our Research page.

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