The pitch sounds almost too ambitious: sensors placed on a pregnant woman's abdomen that can reconstruct what's happening inside a fetus's developing brain, in real time, without breaking the skin.
Yet Wavelet Medical, a New Haven startup around 17 months old, believes it has cracked a problem that has frustrated researchers for decades. On April 14, the company announced it had raised $7 million in seed funding led by Aegis Ventures, the venture studio serving as both investor and co-creation partner. The money will bankroll clinical trials and early commercialization of what Wavelet describes as the first AI-powered, non-invasive fetal electroencephalography platform.
If it works—and that remains a significant if—the technology could upend how obstetricians monitor babies during labor, a field that has relied on roughly the same toolkit for half a century.
The Limits of Listening to Heartbeats
Current fetal monitoring leans heavily on cardiotocography, a method that tracks fetal heart rate and uterine contractions. It's ubiquitous in delivery rooms. It's also maddeningly imprecise. Interpretation varies widely between clinicians, and false positives are common enough that many experts believe the technology contributes to America's stubbornly high cesarean rate, which hovers around 32 percent—about six times the rate of approximately 5.5 percent in 1970.
The invasive alternative, fetal scalp electrodes, can only be deployed after a woman's membranes have ruptured. They carry infection risks. And crucially, they still measure cardiac activity, not the organ most vulnerable during a difficult birth: the brain itself.
Wavelet's system takes a different tack entirely. Proprietary algorithms process abdominal recordings to reconstruct fetal EEG signals, then analyze auditory-evoked brain responses for signs of neurological distress. It's a technical leap that sets the platform apart from emerging competitors like GE HealthCare's Monica Novii or Raydiant Oximetry's pulse oximetry system, both of which focus on heart rate and oxygenation.
The company points to what it characterizes as grim statistics: more than 35,000 birth-related brain injuries occur annually in the United States, according to Wavelet's estimates. Whether a non-invasive abdominal sensor can reliably predict those injuries before they happen is the billion-dollar question.
Yale Roots and Early Believers
Wavelet was founded in December 2024 by a trio of physician-scientists with deep ties to Yale. CEO Liz Golden leads the team alongside Chief Medical Officer Emily Lee, an assistant professor in maternal-fetal medicine, and Head of Science Jose Cortes-Briones, an assistant professor of psychiatry. The technology grew out of research conducted at the university, with early backing from Yale's Blavatnik Fund for Innovation.
Last year, the startup earned a spot as a MedTech Innovator 2025 Grand Prize finalist, a nod that helped draw Aegis Ventures into the fold. Murray Brozinsky, a partner at Aegis, now serves as executive chair of Wavelet's board. The partnership also grants Wavelet access to Aegis' Digital Consortium—a network Yale New Haven Health joined last September.
Currently, the company is running pilots at three hospitals: Yale University, LA General Hospital/USC, and Yonsei University Health System in South Korea. Wavelet has not disclosed any FDA submissions or clearance timelines, characterizing the work instead as groundwork for expanded trials. That caution is perhaps warranted. Regulatory pathways for novel neuromonitoring devices can be labyrinthine, particularly when clinical claims involve preventing brain injury.
Dr. Ja-Young Kwon, director of Yonsei's Institute for Digital Health, offered measured optimism in the funding announcement, noting that the technology's feasibility "holds promise for broad demand across Asia." A Boston Children's Hospital neonatologist, quoted in the same release, suggested that if the platform proves to have strong predictive value, non-invasive fetal EEG could one day become a new standard of care.
The Long Road to Clinical Utility
Seven million dollars buys time, not certainty. Wavelet plans to funnel the capital into product development, clinical adoption efforts, and the delicate early stages of commercialization. The company enters a market where proving clinical utility at scale has defeated others before.
Abdominal EEG reconstruction is notoriously difficult—fetal signals are weak, maternal tissue distorts them, and movement creates noise. Even if Wavelet's algorithms can reliably isolate fetal brain activity, the platform must then demonstrate that the data meaningfully changes outcomes. Do fewer babies suffer hypoxic brain injuries? Do clinicians gain enough confidence to avoid unnecessary surgical deliveries?
Those questions will take years to answer. But for a startup born in a university lab and still in its infancy, the fact that three major hospital systems are willing to test the technology is no small vote of confidence. Whether that confidence translates into a genuine breakthrough in obstetric care—or joins the long list of promising ideas that never quite scaled—remains to be seen.
For now, Wavelet has bought itself a runway. What happens next depends on whether the science can deliver what the pitch promises.
