Human-Machine

Imagine playing a racing game like Mario Kart, using only your brain to execute the complex series of turns in a lap.

This is not a video game fantasy, but a real program that engineers at The University of Texas at Austin have created as part of research into brain-computer interfaces to help improve the lives of people with motor disabilities.

Researchers have modified a commercial virtual reality headset, giving it the ability to measure brain activity and examine how we react to hints, stressors and other outside forces.

The research team at The University of Texas at Austin created a noninvasive electroencephalogram (EEG) sensor that they installed in a Meta VR headset that can be worn comfortably for long periods. The EEG measures the brain's electrical activity during the immersive VR interactions.

The world's computing needs have grown exponentially in recent years due to an explosion of technology. To meet the needs for the next technological leap, the scientific community is working to improve current processing capabilities and simultaneously develop entirely new computing methods.

Two new papers from the research group of Jean Anne Incorvia, a professor in the Cockrell School of Engineering’s Chandra Family of Electrical and Computer Engineering, aim to contribute to both of these scientific needs. Together, they offer improvements on current semiconductor technology as well as a nimbler building block to the next generation of computers that think like the human brain.

For decades, scientists have been investigating how to recreate the versatile computational capabilities of biological neurons to develop faster and more energy-efficient machine learning systems. One promising approach involves the use of memristors: electronic components capable of storing a value by modifying their conductance and then utilizing that value for in-memory processing.

In one of the first studies of its kind, several people with motor disabilities were able to operate a wheelchair that translates their thoughts into movement.

The study by researchers at The University of Texas at Austin and published today in the journal iScience is an important step forward for brain-machine interfaces — computer systems that turn mind activity into action. The concept of a thought-powered wheelchair has been studied for years, but most projects have used non-disabled subjects or stimuli that leads the device to more or less control the person rather than the other way around.

Autonomous robots will soon rove the buildings and streets of The University of Texas at Austin campus. But unlike other commercial delivery services, this fleet of robots will help researchers understand and improve the experience of pedestrians who encounter them.

Wearable medical devices are an important part of the future of medicine and a key focus of researchers around the world. They open the door for long-term continuous monitoring of patients outside of the medical setting to give clinicians an accurate picture of what's happening and a better chance to effectively treat their ailments. Researchers at The University of Texas at Austin have developed an electroencefalography (EEG) electrode that patients wear on their head to monitor brain activity. The EEG electrodes system could act as a brain-computer interface (BCI), which can be controlled by brain signals to help repair damage to the brain caused by strokes and other disorders.

Researchers from The University of Texas at Austin developed synaptic transistors for brain-like computers using the thin, flexible material graphene. These transistors are similar to synapses in the brain, that connect neurons to each other. The transistors are biocompatible, which means they can interact with living cells and tissue. That is key for potential applications in medical devices that come into contact with the human body. Most materials used for these early brain-like devices are toxic, so they would not be able to contact living cells in any way.

Hyun Jung Kim has been developing his "gut-on-a-chip" technology for more than a decade. These miniature systems represent accurate models of the patient's own gut, as well as the disease simulation. The aim is to use the patients’ own cells to test drugs and understand disease processes to determine the right treatment for the patient.

Many members of the UT community have rallied around James Sulzer — and his family. In May 2020, Sulzer’s 4-year-old daughter, Livie, was struck by a tree branch. She suffered a traumatic brain injury (TBI) from the incident. And since then, the family has worked tirelessly, not just to take care of their daughter, but also to shine a light on gaps in care for families dealing with TBI.

Researchers from The University of Texas at Austin and MD Anderson Cancer Center are working together to better detect, diagnose and cure some of the most common and fatal types of cancers.

Pneumonia has emerged as a life-threatening complication of COVID-19, accounting for nearly half of all patients who have died from the novel coronavirus in the U.S. since the beginning of the pandemic. Even before the onset of the COVID-19 pandemic, pneumonia was responsible for more than 43,000 deaths in 2019.

The Cockrell School's José del R. Millán is part of an interdisciplinary team led by the Dell Medical School to map the brains of adolescents before and after epilepsy surgery to examine how novel brain-machine interfaces and embodied learning technologies can help the brain rewire itself before surgery, move key functions away from the surgeon's target and recover more quickly afterward.

Electrical and computer engineering assistant professor Edison Thomaz is working with researchers from Penn State University and Stanford University on a project called sipIT, a technology-based intervention to promote fluid intake, increase urine output and reduce risk of kidney stones. The team recently received a five-year, $2.97 million grant from the National Institute of Diabetes and Digestive and Kidney Diseases to further their technology.

Organoids are stem cell-based tissue surrogates that can mimic the structure and function of organs, and they have become a key component of numerous types of medical research in recent years. But researchers from The University of Texas at Austin have uncovered problems with the conventional method for growing organoids for common experiments that may cause misleading results.

When brother and sister Krishan and Koushalya Sachdev witnessed their 23-year-old cousin’s adjustment to life as a paraplegic after suffering a traumatic accident, they wanted to do everything they could to help him.

ClearCam Inc., a medical device spinout company founded by Cockrell School of Engineering associate professor Chris Rylander based on research from his lab, recently announced the closing of $2.6 million in seed round funding.

The contagious nature of COVID-19 puts medical personnel at risk of contracting the virus from the patients they treat. A startup co-founded by University of Texas at Austin engineering professor Andrea Thomaz just landed $10 million in investment to ramp up production of medical robots that could prove a valuable tool in helping doctors and nurses treat patients amid the novel coronavirus outbreak.

The leading cause of death in Texas is heart disease, according to the National Center for Health Statistics, accounting for more than 45,000 deaths statewide in 2017. A new wearable technology made from stretchy, lightweight material could make heart health monitoring easier and more accurate than existing electrocardiograph machines — a technology that has changed little in almost a century.

To model human health and disease, organ-on-a-chip technology mimics the human body’s organ structure, functionality and physiology in a controlled environment. These miniature systems, which serve as accurate models of various organs from the heart and lungs to the gut and the kidneys, can use a patient’s own cells to test drugs and understand disease processes to help determine the right treatment for the right patient.