Towards Personalized and Non-Invasive Labour Detection using Bloomlife Pregnancy Tracker

Marco Altini1, Michael Johannes Rooijakkers, Elisa Rossetti2, Julien Penders2

  • 1Bloom Technologies, USA - ACTLab, University of Passau, DE
  • 2Bloom Technologies

Details

15:15 - 15:45 | Tue 6 Mar | Treasure Island E | TuBT2.3

Session: BHI Special Session # 4 – Digital Phenotyping: Towards Data-Driven Behavior Change

Abstract

Labour is the physiological process during which the fetus is expelled from the uterus and is normally clinically diagnosed. However, the process leading to labour, typically involving an increase in contractions frequency and intensity can be monitored non-invasively using electrohysterography (EHG) and heart rate (HR). Despite recent technological improvements, diagnosing or detecting labour outside of the hospital environment remains challenging due to much inter-personal variability and lack of data collected in free-living settings. In this abstract we present preliminary results of the deployment of the Bloomlife pregnancy tracker, a unique sensor able to capture EHG, HR and accelerometer data. A sample of 51 women wore the sensor between pregnancy week 26 and 40 (or a subset of such period), including 12 labour recordings. We show that labour probability models developed in the lab can effectively provide information on the odds of delivering and could potentially be used in real-life situations to improve decision making as delivery approaches.