Lending a Helping Hand: Jules Anh Tuan Nguyen on Building a Neuroprosthetic

With deep learning, amputees can now control their prosthetics by simply thinking through the motion.

Jules Anh Tuan Nguyen spoke with NVIDIA AI Podcast host Noah Kravitz about his efforts to allow amputees to control their prosthetic limb — right down to the finger motions — with their minds.

Using neural decoders and deep learning, this system allows humans to control just about anything digital with their thoughts, including playing video games and a piano.

Nguyen is a postdoctoral researcher in the biomedical engineering department at the University of Minnesota. His work with his team is detailed in a paper titled “A Portable, Self-Contained Neuroprosthetic Hand with Deep Learning-Based Finger Control.”

Key Points From This Episode:

Nguyen and his team created an AI-based system using receptors implanted in the arm to translate the electrical information from the nerves into commands to execute the appropriate arm, hand and finger movements — all built into the arm.
The two main objectives of the system are to make the neural interface wireless and to optimize the AI engine and neural decoder to consume less power — enough for a person to use it for at least eight hours a day before having to recharge it.

Tweetables:

“To make the amputee move and feel just like a real hand, we have to establish a neural connection for the amputee to move their finger and feel it just like a missing hand.” — Jules Anh Tuan Nguyen [7:24]

“The idea behind it can extend to many things. You can control virtual reality. You can control a robot, a drone — the possibility is endless. With this nerve interface and AI neural decoder, suddenly you can manipulate things with your mind.” — Jules Anh Tuan Nguyen [22:07]

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