Presentation
Continuous Stress-Monitoring and Personalized Interventions for Expecting Mothers: Wireframe
SessionPoster Session 1
DescriptionContinuous stress during pregnancy can negatively affect both maternal and fetal health, increasing risks such as postpartum depression, maternal mortality, and developmental delays. To address this, we designed a mobile application prototype that integrates wearable sensors, machine learning, and personalized interventions to help expecting mothers monitor and manage their stress in real time. The app wireframe captures physiological signals—like heart rate variability—and applies predictive algorithms to classify current stress levels and forecast next-day stress. When elevated stress is detected or predicted, the app offers tailored coping strategies, including guided mindfulness exercises and brief cognitive-behavioral techniques. Developed through iterative user-centered design and informed by existing research on bio-signal–based stress prediction, the prototype emphasizes ease of use and sustained engagement. By delivering continuous insights and timely recommendations, our approach empowers both users and healthcare providers to intervene proactively, potentially improving pregnancy outcomes and long-term well-being. Preliminary usability testing suggests the wireframe is intuitive and accessible, laying a foundation for future trials to evaluate effectiveness across diverse populations. This work highlights the promise of combining wearable technology and predictive analytics to support personalized maternal health.
Event Type
Poster
TimeTuesday, October 14th5:30pm - 6:30pm CDT
LocationRiverside East
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