The effort is led by Yue Liao, an associate professor of kinesiology at UT Arlington who directs the university’s Physical Activity and Wearable Sensors Lab. The project is supported by a five-year, $3.82 million grant from the National Institute on Minority Health and Health Disparities, a component of the National Institutes of Health that funds research aimed at reducing health disparities among populations that carry a disproportionate burden of disease. Liao argues that the field’s dominant tools for measuring stress are, in a fundamental sense, looking in the wrong place.

“A lot of studies have investigated the relationship between stress experiences and cardiovascular risk. But most focus on either lifetime exposure to stressful events or a person’s recall of their usual exposure,” Liao said. “New measures are needed to better capture people’s daily experiences, which can be very different from traditional measures of stress.” The distinction matters because the two dominant approaches to stress measurement, cumulative lifetime exposure and retrospective self-report, both rely on memory and aggregation, and both can wash out exactly the dynamics that physiologists believe matter most for the heart.

The stakes are considerable. Heart disease remains the leading cause of death in the United States. In 2023, more than 919,000 people died from it, accounting for one in every three deaths, according to the Centers for Disease Control and Prevention. High blood pressure, which affects nearly half of American adults, is among the most significant modifiable risk factors for heart disease and stroke, and a growing body of research links repeated stress responses, including transient surges in blood pressure and heart rate, to the long-term development of hypertension and vascular damage.

The UT Arlington project unfolds in two phases. The first is devoted to building a new survey instrument designed to capture people’s day-to-day experiences with stress, including their immediate emotional reactions and the coping strategies they deploy in the moment. Rather than asking participants to summarize months or years of hardship, the tool is intended to probe the texture of ordinary days: what happened, how it felt, and what the person did about it. The researchers will apply a psychometric methodology known as item response theory, which allows a survey to be tailored to each participant’s demographic and personal characteristics. In practical terms, item response theory lets researchers calibrate which questions carry the most informational weight for a given individual, improving measurement precision without burdening respondents with endless questionnaires.

Once the measure is established, the team will recruit participants who will be monitored intensively for 14 days. During that window, participants will complete brief daily surveys on their smartphones while wearing devices that track physiological responses such as heart rate. This design belongs to a family of methods often called ecological momentary assessment, in which data are collected repeatedly in the flow of everyday life rather than in a single laboratory session. The approach minimizes recall bias, captures within-person variability that population averages obscure, and allows researchers to align what a person reports feeling with what their body is doing at nearly the same moment.

The third component brings the work back under controlled conditions. The researchers will compare the real-world measurements with participants’ responses to stress-inducing tasks conducted in a laboratory setting, where physiological reactivity can be observed with greater precision and standardized provocation. The goal is to understand how well snapshots of daily stress, gathered passively and repeatedly, correspond to the laboratory responses that have traditionally served as the gold standard for measuring cardiovascular reactivity. If the two diverge, that divergence itself could be informative, suggesting that everyday stress operates through patterns that a brief laboratory challenge cannot reproduce.

“Our study is really focusing on day-to-day experiences,” said Liao. “The idea is to capture in-the-moment experiences of stress, perceptions, feelings, social environments and related factors that will allow us to get snapshots of people’s experiences.” She hopes the research will reveal how daily social experiences and behaviors influence physiological responses, and, ultimately, help researchers develop more targeted strategies to reduce cardiovascular risk. Such strategies could range from timing interventions to moments of highest vulnerability to identifying which coping behaviors are genuinely protective when they occur in natural settings rather than in theory.

The project is deliberately multidisciplinary. The coinvestigators include Rebecca Lee, a community health psychologist at Arizona State University, and Salene Jones, a clinical psychologist at the Fred Hutch Cancer Center, bringing expertise in how social contexts and clinical populations shape stress experiences. On the physiological side, Paul Fadel, associate dean for research at UT Arlington and a researcher in cardiovascular physiology, joins the team, along with Daisha Cipher, a biostatistician and nursing professor at UT Arlington, whose work will underpin the analysis of intensive longitudinal data. The combination reflects the reality that linking subjective experience to cardiovascular outcomes requires simultaneous competence in psychology, sensor-based measurement, physiology and statistics.

The project will also establish a six-member community advisory board representing the study population, a structure intended to keep the research grounded in the priorities and lived realities of the communities whose cardiovascular health it aims to improve. That emphasis aligns with the mission of the National Institute on Minority Health and Health Disparities, which has long emphasized that stress exposure and cardiovascular risk are unevenly distributed across populations, and that measurement tools validated in one group may not transfer cleanly to another. By tailoring its survey instrument to participants’ characteristics and involving community representatives from the outset, the team is betting that better measurement, gathered in the moments where stress actually lives, will be the first step toward interventions that reach the people who need them most.

Subject of Research: Real-time measurement of daily stress using smartphones, wearables and laboratory testing to study cardiovascular health

Article Title: UT Arlington study tracks stress in real time

Article References: UT Arlington study tracks stress in real time. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: stress, cardiovascular health, wearable technology, smartphone surveys, item response theory, hypertension, ecological momentary assessment, heart disease, health disparities, UT Arlington, physiological monitoring, National Institutes of Health

The clinical stakes are considerable. The aorta is the body’s largest blood vessel, the highway that carries oxygen-rich blood from the heart to every organ and limb. When this vessel is pinched or narrowed as it exits the heart, a hallmark of coarctation of the aorta, blood flow to the lower body is restricted and the fetal heart must pump harder to push blood through the constriction. The condition accounts for an estimated 6% to 8% of all cardiac birth defects, making it one of the more frequently encountered diagnoses a fetal cardiologist must consider. Yet despite its prevalence, coarctation remains one of the most challenging defects to identify prenatally.

The reason for that difficulty lies in the limitations of current screening tools. Standard prenatal testing relies primarily on anatomic information, essentially static pictures of the heart’s structure, rather than on dynamic blood-flow data, to assess fetal heart health. Standard ultrasound and even specialized echocardiograms, noninvasive tests that use sound waves to create images and generate data about a fetus, often fail to detect anatomical and blood flow abnormalities in a developing heart. Worse, ultrasound-based tests sometimes produce false positives, suggesting that an abnormality is present when no such defect actually exists. “Standard prenatal testing and even specialized imaging often fail to detect anatomical problems in the fetal aorta,” Wei says. “By integrating detailed blood flow parameters, we will give doctors a more precise tool to use when diagnosing congenital heart defects.”

The consequences of a missed diagnosis can follow a child for a lifetime. If coarctation of the aorta is not diagnosed early and repaired with surgery, infants can suffer long-term health problems such as high blood pressure, or in severe cases, die. Early detection changes the entire trajectory of care. When clinicians and families know before birth that a defect is present, they can plan for delivery at a center equipped for immediate intervention, schedule surgical repair, and monitor the newborn closely from the first hours of life. “Surgeons can repair many heart problems in babies, but the first, and most important, step is detecting problems,” Wei said. “The earlier we can identify a condition, the more time clinicians and families have to plan for the baby’s care.”

Wei’s answer to this diagnostic gap is a digital twin: a viewable digital replica of an individual patient’s cardiovascular system that can be interrogated on a computer the way a clinician might examine a patient at the bedside. The model will integrate multidimensional, patient-specific data to support clinical decision-making, including assessment of whether a fetal heart defect is present. Rather than relying on a single snapshot of anatomy, the digital twin will simulate how blood actually behaves inside a particular fetus’s aorta, capturing the hemodynamic signatures that a narrowing leaves on pressure, velocity, and wall stress even when the structural change is too subtle for imaging to resolve.

The raw material for this model comes from an unusually rich data source. Wei’s team will draw on fetal heart data collected at more than 15 cardiology programs across North America that are part of the Fetal Heart Society. The database includes information gathered during two-dimensional and three-dimensional ultrasound tests performed on hundreds of racially and ethnically diverse pregnant women, including some whose babies were confirmed after birth to have heart defects. That breadth matters both scientifically and clinically: a model trained on diverse populations is more likely to perform reliably across the full spectrum of patients a prenatal clinic will see, and the inclusion of confirmed postnatal diagnoses gives the researchers ground truth against which their predictions can be checked.

Wei and his team have already used information in the database to create a model representing blood flow in healthy fetal hearts, establishing a baseline of normal hemodynamics. Going forward, the new model will focus on a set of physically meaningful measurements that reflect how the cardiovascular system responds to obstruction. These include the forces exerted on the walls of fetal blood vessels, the pressure and flow characteristics through a narrowed fetal artery, and the resistance that arises when freshly pumped blood collides with blood already moving through the vessel. Each of these parameters encodes information about the geometry and elasticity of the aorta in ways that a static image cannot, which is precisely why the researchers believe flow-based metrics will outperform anatomy-only assessment.

Building a model is only half the challenge; proving that it is trustworthy is the other half. To validate their computational predictions, the researchers will conduct laboratory experiments using 3D-printed silicone models of fetal aortas, paired with fluid and pumping mechanisms that recreate the mechanical conditions of the fetal circulation. These physical phantoms allow the team to compare what the digital twin predicts against what actually happens in a controlled, measurable system with known geometry. Finally, data from the Geisinger healthcare system’s database will be used to evaluate blood flow metrics for better diagnosis of aorta narrowing in the future, closing the loop between computation, experiment, and real clinical outcomes.

The project is a deliberately interdisciplinary effort. Wei is working with Professor Zhongqiang Zhang and Associate Professor Fangfang Wang, both of WPI’s Department of Mathematical Sciences, whose expertise in computational mathematics underpins the numerical machinery of the digital twin, and with Dr. Shuping Ge, a pediatric cardiologist and researcher with the Geisinger healthcare system in Pennsylvania, who brings the clinical perspective needed to ensure the model answers questions doctors actually face. The work also builds on Wei’s broader research program in computational and experimental models of blood flow mechanics. His fetus-related research has been supported by the American Heart Association’s Second Century Faculty Independence Award and a National Institute of Biomedical Imaging and Bioengineering Trailblazer Award, honors recognizing the innovation and potential clinical impact of his work, and he has previously collaborated on pediatric medical devices and 3D-printed blood vessels for heart bypass surgery.

For Wei, the ultimate measure of success is not a publication or a patent but a change in how early and how confidently fetal heart defects are caught. He says that development of a validated digital twin model for coarctation of the fetal aorta will lay a solid foundation for future human studies that could lead to more accurate screening tools and better health outcomes for children with the birth defect. “The goal of my lab is to improve the detection and treatment of cardiovascular disease and, ultimately, to help ensure that patients receive the right care at the right time,” Wei said. If the project succeeds, the faint hemodynamic whispers of a narrowed aorta, invisible to today’s ultrasound screens, may become impossible for medicine to miss.

Subject of Research: Development of a blood flow-based digital twin model for prenatal detection of fetal aortic coarctation

Article Title: Worcester Polytechnic Institute researcher is seeking clues to problems in tiny hearts

Article References: Worcester Polytechnic Institute researcher is seeking clues to problems in tiny hearts. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: fetal heart defects, coarctation of the aorta, digital twin, blood flow modeling, prenatal diagnosis, echocardiography, computational fluid dynamics, 3D printing, National Institutes of Health, Worcester Polytechnic Institute, congenital heart disease, biomedical engineering