Nuvo, a maternal-fetal health technology company, has announced a pregnancy data solution built from real-world use of its FDA-cleared INVU wearable monitoring device. The company says the dataset includes more than 350,000 minutes of monitoring across over 25,000 sessions collected from pregnancies in both clinical and home settings.
The dataset combines synchronized maternal and fetal physiological signals including native fetal electrocardiography (fECG), fetal phonocardiography (fPCG), maternal ECG, and maternal phonocardiography, along with motion data and structured pregnancy information. ECG measures the heart’s electrical activity while phonocardiography captures acoustic signals.
“The INVU pregnancy monitoring wearable solution has enabled Nuvo to build a large-scale, multimodal, longitudinal dataset grounded in real-world use, thereby creating a foundation for AI-driven pregnancy insights that simply has not previously existed,” said Laurence Klein, CEO of Nuvo. “This is about redefining how the health of both mother and child during pregnancy can be measured, modeled, and understood over time.”
Unlike traditional pregnancy monitoring, which typically relies on brief clinic visits or single measurements, Nuvo’s approach captures multiple signal types simultaneously over time. The company says combining electrical signals with mechanical heart sounds allows each signal to validate and help interpret the others, improving signal quality and reducing motion artifacts.
Nuvo has received approval from an independent Institutional Review Board (IRB) to conduct retrospective analyses of its pregnancy monitoring data, allowing the company and partners to study de-identified data for patterns in maternal and fetal health.
The INVU platform currently supports FDA-cleared, AI-powered Non-Stress Tests incorporating fetal and maternal heart rate and uterine activity. Nuvo says the data streams could support additional insights including earlier indicators of fetal distress and changes in maternal cardiovascular function.
