HoustonPBS UH Moment: Brain-Controlled Exoskeleton Making Strides

Steve Holbert was paralyzed in a dirt bike accident in late 2009.

“I broke five vertebrae and injured my spinal cord and have been paralyzed ever since,” said Holbert.

Brain Machine Interface ResearchHis hope is to completely recover from his spinal cord injury and one day walk again. That’s why he’s agreed to participate in the research of Jose Luis “Pepe” Contreras-Vidal, professor of electrical and computer engineering at the University of Houston’s Cullen College of Engineering and director of the Laboratory for Non-invasive Brain-Machine Interface Systems.  Contreras-Vidal is working on a brain-machine interface (BMI) that would allow patients like Holbert to control prosthetic limbs through their own thoughts. Holbert’s is testing a self-balancing lower limb exoskeleton.

“I am happy to be involved with anything that can help me get better or help others,” said Holbert.

By wearing a cap equipped with as few a dozen non-invasive electrode sensors, Contreras-Vidal can collect information about how Holbert intends to move in the exoskeleton. The cap detects brain signals escaping the scalp.

“When millions of neurons inside your brain fire together in a synchronized way, that signal propagates through the tissue, brain, scalp and skull, and escapes your head,” said Contreras Vidal. “We measure those tiny signals with those sensors.”

So the next time Holbert suits up on this robotic exoskeleton, the brain-machine interface will allow his thoughts to signal the movement of the robotic prosthesis.

“What we are now addressing is ‘what is the best way to allow this close interaction between the machine, the human body and the brain?’ How we can share the control from the machine to the brain and the other way around?” said Contreras-Vidal.

In February, the world’s leading BMI researchers will gather in Houston with a goal of mapping the most efficient way to bring brain-controlled prosthetics to patients. Contreras-Vidal will chair the International Workshop on Clinical Neural Brain-Machine Interface Systems.