Innovation with Impact: BU Engineering Students Develop Preecamplsia Detection Device Informed by Social Science
This article written by Lindsay Griesman (CAS’27) , 2026 CISS Summer Writing Internship Program intern. She is majoring in anthropology with a specialization in Health & Medicine.
Maternal health disparities in the United States are higher than ever, the CDC says. Yet data suggest that more than 80% of pregnancy-related deaths are preventable. Important strides have been made as organizations like March of Dimes (which focuses on both advocacy and funding research) and Every Mother Counts (outreach and education-based) have been established, and legislation has been passed to standardize care. While these policy and non-profit initiatives have successfully improved state-level data tracking of maternal mortality rates, systemic gaps in care and technology access still leave thousands of mothers at risk. For eight Boston University Engineering students, the current work was not enough. It became a call to action.
When Ashiyana Chikani (ENG’27), Dakota Wang (ENG’27), Julio Reyes (ENG’27), Marcelo Jose Villafuerte (ENG’28), Mikayla Grimes (ENG’27), Neel Sajja (ENG’27), Thanaisawan Hill (ENG’27), and Tobias Maluf-Mas (ENG’27), heard about the NIH’s DEBUT challenge — a design competition for biomedical engineering undergraduate students to develop solutions under different healthcare categories— they knew this was their opportunity to make an impact.
“It was a chance for me to get hands-on experience with designing a biomedical device and working in a multidisciplinary team,” said Hill. “It was a rare experience to collaborate in such a large group on a device with so many different parts and factors to consider…a chance to foster new ideas.” After all, it’s not every day undergraduate students get to team up and engineer a device from the ground up that can contribute significantly to closing the equity gap in maternal care.
For Maluf-Mas, the team leader, the project represented more than a competition. It was a chance to inspire, innovate, and positively impact underserved communities.
“With Boston University’s last documented recognition in the NIH DEBUT Challenge occurring more than a decade ago, we hope this project helps inspire a renewed culture of undergraduate innovation and design,” he said. “You never truly know what you are capable of achieving until you take the opportunity to challenge yourself and see where it leads.”
The team focused on preeclampsia, a pregnancy complication characterized by high blood pressure that remains one of the leading causes of maternal and fetal morbidity and mortality worldwide. Affecting approximately three to eight percent of pregnancies, preeclampsia is especially dangerous because many cases are not diagnosed until symptoms have already developed. It is a condition that is ubiquitous to all communities.
Hill explained that the team “chose to focus on preeclampsia because improving early detection could help healthcare providers screen for [preeclampsia] before the onset of clinical disease.” Earlier detection could allow for intervention, treatment, and preventive measures before further complications arise. In underserved communities where access to quality care is limited, so is the ability to have regular blood pressure checks, which is one of the key diagnostic tools for preeclampsia.
The issue’s significance is also personal for team member Neel Sajja, whose interest in health equity stems from experiences within his own family. He saw the project as an opportunity to address broader disparities in healthcare. Coming from a family of all women, he is passionate about advocating for maternal and reproductive health and fighting against women’s underrepresentation in healthcare.
“No person deserves to be discriminated against and denied coverage just because they don’t fill out the boxes for care on the surface,” he said.
The United States medical system tends to be more readily available to higher-income communities, especially in fields such as reproductive care. Those living in underserved areas are not ensured quality healthcare for a number of reasons. Systemic inequities, imparted biases in care, and pre-existing conditions like diabetes and obesity (due to lack of nutritious food from poorly stocked food banks, far distances to travel, and/or high prices), all increase the risk of developing preeclampsia. Additionally, some pregnant people are simply dismissed when they attempt to advocate for themselves. There is much room for growth in the realm of preventative and equitable care in maternal health.
And thus, Preeclampsia Early Assessment of Risk with Longitudinal monitoring (PEARL) was born. The team, named SEBU (Societal Engineers of Boston University *not yet affiliated), as a nod to the College of Engineering’s signature phrase, “Building the Societal Engineer,” developed the device thoughtfully to address these gaps in care.
“PEARL is a machine learning-powered risk assessment tool designed to help identify patients who may be at risk of developing preeclampsia in pregnancy” according to Grimes.
Their project incorporates multiple factors known to influence the risk of preeclampsia, including blood pressure trends, medical history, and demographic information like race. A machine learning model analyzes these data points to generate a personalized risk score and identify the factors contributing most significantly to a patient’s risk. The system combines cardiovascular acquisition bands, a Raspberry Pi computer, and a touchscreen interface that allows healthcare providers to enter information and view results. The model itself was trained using data from thousands of pregnancies, allowing it to identify patterns that may be difficult to recognize through traditional screening methods alone.
The students’ approach was not solely shaped by engineering principles. “Conversations surrounding race and maternal health completely shifted how we developed PEARL,” Wang noted.
As they learned more about the disproportionate burden of maternal mortality experienced by underserved populations (racial minorities, low-income communities, and low-education groups), they began designing PEARL with equity and access as a central consideration. Their machine learning model was trained using the nuMoM2b (Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be) dataset, which contains data from more than 10,000 first-time pregnancies. This data was invaluable to the team’s process: “Our work would not have been possible without the Research Triangle Institute and their ongoing research efforts.” SEBU also intentionally incorporated patient race and age into the model to better account for differences in preeclampsia risk across diverse populations and to support impartial risk assessment.
Those same conversations additionally influenced technical design choices. PEARL does not rely on a cloud-based infrastructure, and instead processes information locally using the Raspberry Pi computer. This allows the device to function in settings like clinics or homes with limited or unreliable internet access. Since “PEARL was designed with the goal of expanding access to early preeclampsia risk assessment, particularly for communities that face barriers (geographic, financial, and access-based) to consistent prenatal care,” the team also designed the system with usability in mind so that frontline healthcare workers could operate it in resource-constrained settings. With these considerations in mind, the team also designed the device to monitor blood flow at the wrist rather than using a traditional arm cuff, which increases accessibility and ease of use.
The result is a device that not only predicts risk but expands access to care. It is not only cost-effective, with a projected mass production cost of around $300 per unit, but also energy-efficient, operating off a rechargeable battery with a life of 1.5-2.5 hours. In that time, between 15 and 20 assessments can be completed. That’s one full assessment every 10 minutes.
I asked the team if they had any takeaways from this project. Their answer? “We learned that true equity requires engineering a device that works reliably in any environment.” They envision PEARL being used in rural clinics, community health centers, federally qualified health centers, and global maternal health programs where specialized testing and advanced diagnostic infrastructure may not be readily available.
“I hope people see that addressing health disparities requires more than developing new technology,” Gymes said. “It means understanding the barriers that prevent people from accessing care and designing solutions with those challenges in mind.” The WHO reports that 16% of maternal deaths globally are due to hypertensive disorders like preeclampsia.
For Chikani, a pre-PA student, “this project has reinforced why [I] chose to combine engineering and healthcare. Early preeclampsia risk assessment should be accessible to every pregnant patient, not just those with access to specialized testing or large healthcare systems. Working on PEARL showed me that meaningful improvements in patient care can happen long before a provider enters the exam room.”
These intelligent, driven students are a prime example of a Boston University success story. They are confident, bold, and curious in their work, and PEARL’s success demonstrates that engineering solutions can be strengthened when created with a deep understanding of the social factors that shape health outcomes. Their work is a reminder that innovation is not just about creating new or exciting technologies; it’s about expanding the positive impact of such technologies and ensuring that they reach the vulnerable populations who need them most.
If no one has said it yet, let me be the first to say congratulations to these incredible students. What they’ve accomplished in the last year is truly impressive and no small feat.