How Wearables and AI Are Changing Pregnancy Care By Amelia Roessler
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raditionally, expecting parents might get snapshots of their health at prenatal appointments, followed by a period of anticipation and hoping things are still good. Today, the intersection of technology and maternal healthcare is creating a new world for the in-between. Now, smartwatches, rings, apps, con- tinuous monitors, and AI-powered tools can collect information day and night. But does having more information actually lead to better care—or just more information to worry about? What Pregnancy Wearables Can Actually Track The smartwatch already on your wrist knows quite a bit about you. Depending on the device, it might track your heart rate, sleep, activity, temperature, respiratory rate, and other health trends throughout the day and night. During pregnancy, some of those measurements naturally change—and researchers are investigating whether tracking those changes over time could tell us more about maternal health.
Scientists at Scripps Research have found preliminary evidence that suggests even common wearable devices—such as the Apple Watch, Garmin, and Fitbit— could remotely monitor pregnancy-related health changes by tracking patterns like heart rate that correlate with hormonal fluctuations. Pregnancy-specific technology is taking monitoring even further. Researchers are studying wearable devices capable of tracking fetal heart rate, fetal movement, uterine contractions, and other indicators. Stanford researchers have even developed a wearable ultrasound patch designed to continuously monitor fetal blood flow, with the goal of helping doctors identify potential complications earlier. What Does AI Add to the Equation? Collecting thousands of data points is one thing. Figuring out what they mean is another. That’s exactly where AI could become useful. Instead of expecting a patient or health- care provider to sift through days or weeks of data or readings, AI systems can analyze
large amounts of information to look for patterns or changes that might deserve a closer look. AI and machine learning have expanded rapidly in maternal, fetal, neonatal, and reproductive healthcare. According to the National Library of Medicine, AI promises advances in risk prediction, diagnostics, and treatment optimization. Machine learning models have been applied to predict things such as preeclampsia, preterm birth, gesta- tional diabetes, hemorrhaging, and delivery mode using maternal demographic, clinical, and lab data. But prediction isn’t diagnosis. An algorithm identifying a pattern doesn’t necessarily mean something is wrong, which makes the role of healthcare providers especially important as these technologies become more common. When More Data Creates More Anxiety Imagine it’s 2 a.m. An expecting mom wakes up, checks her ring or watch, and sees her resting heart rate is different from yester- day. She immediately turns to Google: Is something wrong? Is it normal pregnancy
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