Maternal-Fetal Health Research

Pioneering research for healthier pregnancies

We're a team of clinicians, engineers, and AI scientists exploring how continuous monitoring technologies could help detect fetal distress earlier and improve pregnancy outcomes.

Project Stardust
25,000
US stillbirths annually
55%
Preventable with existing tech
25,000
US stillbirths annually
1 in 150 births
55%
Potentially preventable
with existing technology
>70%
Fetal Growth Restriction undiagnosed
until after birth
8x
Higher stillbirth risk
with undetected Fetal Growth Restriction

A critical gap in pregnancy monitoring

Despite advances in prenatal care, stillbirth rates in developed nations have remained largely unchanged for two decades. We know that additional monitoring reduces stillbirths and adverse outcomes - but it's currently only available in-hospital and to a small fraction of parents.

Impact of Antenatal FGR Detection on Stillbirth Rates

Stillbirth rate with and without antenatal fetal growth restriction (FGR) detection:

19.8
per 1,000
Undetected
>50% reduction
9.7
per 1,000
Detected

Improved outcomes in detected cases are largely due to earlier, well-timed delivery (median 10 days earlier than undetected cases).

Source: Gardosi et al., BMJ 2013 (n=92,218 pregnancies)

Why early detection matters

Current prenatal care relies on periodic snapshots; ultrasounds every few weeks, occasional non-stress tests. Yet conditions like fetal growth restriction (FGR) develop gradually, and warning signs often emerge between clinical visits.

Research shows that when FGR is detected early, outcomes improve dramatically; detection roughly halves stillbirth risk. But with limited sonographer availability, most women receive only 2-3 ultrasounds throughout pregnancy, leaving dangerous conditions unidentified.

The Kick Counting Problem

Today, most mothers' primary tool for monitoring their baby is “kick counting”— tracking fetal movements manually. But this method is time-intensive, subjective, and by the time movement patterns change noticeably, it's often too late for intervention.

There is urgent need to improve detection and monitoring of FGR to improve outcomes. Short-term recordings limit their utility.

— Frontiers in Physiology, 2022

Our Goal

Make monitoring continuous, affordable, and universally accessible - not just for high-risk pregnancies, but for every parent who wants peace of mind.

What parents are asking for

50% of mothers worry about fetal movement during pregnancy and ~10% go to hospital at some point just for reassurance. Here's what expectant parents told us they want:

A way for baby to be continuously monitored but also in a way that they are not disturbed. I could then get updates whenever I wanted to check on baby.

Having a keyhole view on what's going on—making sure my baby still has a heartbeat, growing at the rate expected.

A device that tracks kicks FOR you instead of having to sit there and try to keep track of them.

Like one of those diabetes monitors but on my belly.

An easy to use app that tracks my baby’s growth, health stats, and movements in real time.

A wearable that safely tracks the baby’s heartbeat and movements, synced with an app that gives clear daily updates and alerts my doctor if something seems off.

Source: Berkeley Human-Centered Design Parent Interviews, 2024

Exploring new approaches to fetal monitoring

We're investigating how emerging technologies could enable earlier detection of fetal distress through more frequent, accessible monitoring.

Growth Trajectory Analysis

Investigating how individualized growth curves, rather than population-based percentiles, could improve early identification of growth restriction.

Multi-Modal Sensing

Exploring how combining multiple sensor modalities could provide complementary signals for fetal wellbeing assessment in non-clinical settings.

AI-Assisted Interpretation

Researching machine learning approaches to interpreting complex fetal data, enabling detection of subtle patterns that indicate developing complications.

Clinical Integration

Studying how continuous monitoring data could integrate with existing clinical pathways, supporting clinical care.

i

Our research is ongoing. We are currently in early-stage feasibility studies and are not making claims about clinical efficacy. We are committed to rigorous validation through proper clinical trials.

World-class expertise in medicine, AI, and product

A multidisciplinary team combining clinical expertise in maternal-fetal medicine, experience building medical devices, and cutting-edge AI research.

K Kathryn
Kathryn
Hardware
Stanford MBA Physicist Harvard MPA

Serial founder of AI-enabled medical wearables. Led healthcare AI at GoogleX.

Google McKinsey Stanford
H Hector
Hector
Consumer
Oxford MMathPhil Stanford MBA

Founder, consumer hardware and marketing specialist. Former Apple partnerships lead.

Capital One Apple Stanford
N Noel
Noel
Medical Innovation
Stanford MD Stanford MBA

Fellowship-trained surgeon focused on healthcare technology innovation.

Stanford Medicine Harvard
A Aris
Aris
Fetal Medicine
Professor, Fetal Medicine, Oxford

AI pregnancy imaging leader. Co-founder of Intelligent Ultrasound (acq'd).

Oxford OMPHI
J Jann
Jann
AI & Data Science
Assoc. Prof., Stanford GSB Harvard PhD

Expert in causal inference and AI for targeting interventions.

Stanford Harvard

Built on peer-reviewed science

Our work builds on decades of research in maternal-fetal medicine, ultrasound imaging, and AI-assisted diagnostics.

Saving babies and families from preventable harm: a review of the current state of fetoplacental monitoring and emerging opportunities

Ranaei-Zamani N, David AL, Siassakos D, Dadhwal V, Melbourne A, Aughwane R, Russell-Buckland J, Tachtsidis I, Hillman S, Mitra S

NPJ Women's Health

2024

Fetal growth restriction and stillbirth: Biomarkers for identifying at risk fetuses

King VJ, Bennet L, Stone PR, Clark A, Gunn AJ, Dhillon SK

Frontiers in Physiology

2022

Fetal weight projection model to define growth velocity and validation against pregnancy outcome

Hugh O, Gardosi J

Ultrasound in Obstetrics & Gynecology

2022

Prediction of preterm birth using artificial intelligence: a systematic review

Akazawa M, Hashimoto K

Journal of Obstetrics and Gynaecology Research

2022

Prenatal Care Services, Maternal Morbidity, and Perinatal Mortality With the Advanced Maternal Age Cutoff

Geiger CK, Clapp MA, Cohen JL

JAMA Health Forum

2021

International standards for fetal growth based on serial ultrasound measurements: the Fetal Growth Longitudinal Study of the INTERGROWTH-21st Project

Papageorghiou AT, Ohuma EO, Altman DG, Todros T, Cheikh Ismail L, Lambert A, Jaffer YA, Bertino E, Gravett MG, Purwar M, Noble JA, Pang R, Victora CG, Barros FC, Carvalho M, Salomon LJ, Bhutta ZA, Kennedy SH, Villar J

The Lancet

2014

Perinatal morbidity and mortality in early-onset fetal growth restriction: cohort outcomes of the trial of randomized umbilical and fetal flow in Europe (TRUFFLE)

Lees C, Marlow N, Arabin B, Bilardo CM, Brezinka C, Derks JB, Duvekot J, Frusca T, Diemert A, Ferrazzi E, Ganzevoort W, Hecher K, Martinelli P, Ostermayer E, Papageorghiou AT, Schlembach D, Schneider KTM, Thilaganathan B, Todros T, van Wassenaer-Leemhuis A, Valcamonico A, Visser GHA, Wolf H

Ultrasound in Obstetrics

2013

Join our mission

We're building a network of researchers, clinicians, and advocates committed to improving pregnancy outcomes. If you share our mission, we'd love to connect.

Clinical Collaboration

Partnerships with maternal-fetal medicine specialists for future studies.

Research Partnerships

Collaboration with aligned groups in AI, sensing, and medical devices.

Advisory

Guidance from experts in regulatory, clinical, and business domains.

Open Roles

Interested in joining the team? Please see our job listings on LinkedIn.