A unique innovation from the University of Houston has the potential to help stroke victims recover mobility. Photo courtesy of UH

A University of Houston professor has taking a huge step in advancing his game-changing stroke recovery tech.

Jose Luis Contreras-Vidal, the director of the UH BRAIN Center, recently published his work on a noninvasive brain-machine in a summer issue of the journal Sensors. InnovationMap first reported on Contreras-Vidal's technology in 2022, when it was being tested.

Contreras-Vidal's device uses a wireless, mobile dry-electrode headset placed on the scalp to convert electroencephalography (EEG) recordings (or measurements of electrical activity in different parts of the brain) to interface with a closed-loop brain–computer (BCI) and communicate with exoskeleton devices. Together, the technology triggers robotic movement based on the wearer's brain activity.

The technology has potential to boost cortical plasticity after a stroke, which can improve motor skills recovery.

According to a statement from UH, a patent is pending on Contreras-Vidal's BCI algorithm and the self-positioning dry electrode bracket used on the scalp. The technology has also now been validated and tested at the University of Houston.

Contreras-Vidal says the technology makes stroke recovery easier for the user and even possible at home.

“Most commercial EEG-based BCI systems are tethered to immobile processing hardware or require complex programming or set-up, making them difficult to deploy outside of the clinic or laboratory without technical assistance or extensive training," he says in a statement. "A portable and wireless BCI system is highly preferred so it can be used outside lab in clinical and non-clinical mobile applications at home, work, or play.”

Additionally, the technology uses off-the-shelf components and is adjustable to fit about 90 percent of the population, according to UH.

"Current commercial EEG amplifiers and BCI headsets are prohibitively expensive, lack interoperability, or fail to provide a high signal quality or closed-loop operation, which are vital for BCI applications,” Contreras-Vidal adds.

The development of this technology was originally funded in part by an $813,999 grant from the National Science Foundation’s Division of Translational Impacts. UH reports that about 795,000 people in the United States suffer from a stroke annually.

Other leaders in Houston’s medical industry have tapped into innovative ways to treat and rehabilitate stroke patients in recent years. Baylor St. Luke's Hospital began using AI to reduce the time it takes to treat patients who've suffered from a stroke in 2021.

Stroke patients have a new hope for arm rehabilitation thanks to a team from UH. Photo courtesy of UH

Robotic device created at the University of Houston helps stroke patients to rehabilitate

next-gen recovery

Almost 800,000 people in the United States suffer from a stroke annually — and the affliction affects each patient differently. One University of Houston researcher has created a device that greatly improves the lives of patients whose stroke affected motor skills.

UH engineering professor Jose Luis Contreras-Vidal developed a next-generation robotic arm that can be controlled by the user's brainwaves. The portable device uses a brain-computer interface (BCI) developed by Contreras-Vidal. Stroke patient Oswald Reedus, 66, is the first person to use a device of this kind.

Reedus lost the use of his left arm following a stroke that also caused aphasia, or difficulty speaking. While he's been able to recover his ability to speak clearly, the new exoskeleton will help rehabilitate his arm.

When strapped into the noninvasive device, the user's brain activity is translated into motor commands to power upper-limb robotics. As patients like Reedus use the device, more data is collected to improve the experience.

“If I can pass along anything to help a stroke person’s life, I will do it. For me it’s my purpose in life now,” says Reedus in a news release from UH. His mother and younger brother both died of strokes, and Reedus is set on helping the device that can help other stroke patients recover.

Contreras-Vidal, a Hugh Roy and Lillie Cranz Cullen distinguished professor, has led his device from ideation to in-home use, like with Reedus, as well as clinical trials at TIRR Memorial Hermann. The project is funded in part from an $813,999 grant from the National Science Foundation’s newly created Division of Translational Impacts.

"Our project addresses a pressing need for accessible, safe, and effective stroke rehabilitation devices for in-clinic and at-home use for sustainable long-term therapy, a global market size expected to currently be $31 billion," Contreras-Vidal says in the release. "Unfortunately, current devices fail to engage the patients, are hard to match to their needs and capabilities, are costly to use and maintain, or are limited to clinical settings."

Dr. Gerard E. Francisco, chief medical officer and director of the Neuro Recovery Research Center at TIRR Memorial Hermann, is leading the clinical trials for the device. He's also chair and professor in the Department of Physical Medicine and Rehabilitation at McGovern Medical School at UTHealth Houston. He explains that TIRR's partnership with engineering schools such as the Cullen College of Engineering at UH and others around the nation is strategic.

“This is truly exciting because what we know now is there are so many ways we can induce neuroplasticity or how we can boost recovery,” says Francisco in the release. “That collaboration is going to give birth to many of these groundbreaking technologies and innovations we can offer our patients.”

Both parts of the device — a part that attaches to the patient's head and a part affixed to their arm — are noninvasive. Photo courtesy of UH

Baylor St. Luke's Hospital is using a new Bay Area technology to provide treatment to stroke patients. Photo courtesy Baylor St. Luke's

Houston hospital taps artificial intelligence to boost stroke treatment

health tech

For neurologists and neurocritical care providers like Dr. Chethan Rao, medical director of Neuroscience ICU at Baylor St. Luke's Hospital, time is incredibly important when it comes to brain-related recoveries.

"For every minute that you don't treat a patient with a stroke, 2 million nerve cells die. In the normal aging process, you lose about 35,000 cells a year or so," Rao says. "In other words, you age about 10 years every minute you don't get a treatment for stroke."

This is why his team is using new technologies, softwares, and innovation to drastically reduce the time it takes to treat patients who've suffered from a stroke starting from the moment they enter through the doors of their hospital.

One of the latest advancements at Baylor St. Luke's is the adoption of the San Francisco-based artificial intelligence app called Viz.ai across its stroke care teams.

The app received FDA approval in February 2020 and uses deep learning algorithms to analyze CAT scans for suspected large vessel occlusion (LVO) strokes. Baylor purchased the software about a year ago and is the first Houston-area hospital to use artificial intelligence for this type of treatment.

Viz.ai instantly allows doctors to determine salvageable and unsalvageable brain tissue, creating what Dr. Rao describes as a "map" for any potential procedures. Determining the viability of this type of treatment traditionally would take about 15 to 20 minutes, according to Rao.

"That's the reason artificial intelligence and automated technology has become extremely important. Because the more you've reduced the time it's required to make decisions and to provide treatments for stroke, that benefit is humungous for the patient," he says.

Rao says that his team uses the software about every day and has treated roughly 140 stroke patients with guidance from the tool.

Next the hospital aims to connect Viz.ai with additional automated systems it has adopted to speed up processes for stroke patients and manage their care, including TigerConnect for internal HIPAA-approved messaging and Decisio, a Houston-based product that captures key time stamps.

And Rao adds that the hospital is researching ways to extend the use of Viz.ai for select patients—to salvage more brain matter and analyze additional neurological events.

"More exciting things will be coming out of it," he says. "We're also working on helping it analyze aneurysms, not just blockages. Can we locate the bleeds, so that we can create different alert systems and then create different treatment pathways immediately?"

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Houston researcher builds radar to make self-driving cars safer

eyes on the road

A Rice University researcher is giving autonomous vehicles an “extra set of eyes.”

Current autonomous vehicles (AVs) can have an incomplete view of their surroundings, and challenges like pedestrian movement, low-light conditions and adverse weather only compound these visibility limitations.

Kun Woo Cho, a postdoctoral researcher in the lab of Rice professor of electrical and computer engineering Ashutosh Sabharwal, has developed EyeDAR to help address such issues and enhance the vehicles’ sensing accuracy. Her research was supported in part by the National Science Foundation.

The EyeDAR is an orange-sized, low-power, millimeter-wave radar that could be placed at streetlights and intersections. Its design was inspired by that of the human eye. Researchers envision that the low-cost sensors could help ensure that AVs always pick up on emergent obstacles, even when the vehicles are not within proper range for their onboard sensors and when visibility is limited.

“Current automotive sensor systems like cameras and lidar struggle with poor visibility such as you would encounter due to rain or fog or in low-lighting conditions,” Cho said in a news release. “Radar, on the other hand, operates reliably in all weather and lighting conditions and can even see through obstacles.”

Signals from a typical radar system scatter when they encounter an obstacle. Some of the signal is reflected back to the source, but most of it is often lost. In the case of AVs, this means that "pedestrians emerging from behind large vehicles, cars creeping forward at intersections or cyclists approaching at odd angles can easily go unnoticed," according to Rice.

EyeDAR, however, works to capture lost radar reflections, determine their direction and report them back to the AV in a sequence of 0s and 1s.

“Like blinking Morse code,” Cho added. “EyeDAR is a talking sensor⎯it is a first instance of integrating radar sensing and communication functionality in a single design.”

After testing, EyeDAR was able to resolve target directions 200 times faster than conventional radar designs.

While EyeDAR currently targets risks associated with AVs, particularly in high-traffic urban areas, researchers also believe the technology behind it could complement artificial intelligence efforts and be integrated into robots, drones and wearable platforms.

“EyeDAR is an example of what I like to call ‘analog computing,’” Cho added in the release. “Over the past two decades, people have been focusing on the digital and software side of computation, and the analog, hardware side has been lagging behind. I want to explore this overlooked analog design space.”

12 winners named at CERAWeek clean tech pitch competition in Houston

top teams

Twelve teams from around the country, including several from Houston, took home top honors at this year's Energy Venture Day and Pitch Competition at CERAWeek.

The fast-paced event, held March 25, put on by Rice Alliance, Houston Energy Transition Initiative and TEX-E, invited 36 industry startups and five Texas-based student teams focused on driving efficiency and advancements in the energy transition to present 3.5-minute pitches before investors and industry partners during CERAWeek's Agora program.

The competition is a qualifying event for the Startup World Cup, where teams compete for a $1 million investment prize.

PolyJoule won in the Track C competition and was named the overall winner of the pitch event. The Boston-based company will go on to compete in the Startup World Cup held this fall in San Francisco.

PolyJoule was spun out of MIT and is developing conductive polymer battery technology for energy storage.

Rice University's Resonant Thermal Systems won the second-place prize and $15,000 in the student track, known as TEX-E. The team's STREED solution converts high-salinity water into fresh water while recovering valuable minerals.

Teams from the University of Texas won first and second place in the TEX-E competition, bringing home $25,000 and $10,000, respectively. The student winners were:

Companies that pitched in the three industry tracts competed for non-monetary awards. Here are the companies named "most-promising" by the judges:

Track A | Industrial Efficiency & Decarbonization

Track B | Advanced Manufacturing, Materials, & Other Advanced Technologies

  • First: Licube, based in Houston
  • Second: ZettaJoule, based in Houston and Maryland
  • Third: Oleo

Track C | Innovations for Traditional Energy, Electricity, & the Grid

The teams at this year's Energy Venture Day have collectively raised $707 million in funding, according to Rice. They represent six countries and 12 states. See the full list of companies and investor groups that participated here.

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This article originally appeared on our sister site, EnergyCapitalHTX.com.