LactaLearn: Mobile App for Automated Assessment of Newborn Breastfeeding Efficiency

Program:

Biomedical Engineering

Project Description:

80% of new mothers want to exclusively breastfeed their infant; however, only 41% meet this goal. The most common reason why new mothers cease exclusive breastfeeding is because of concerns over adequate milk intake. At-home timing of feedings is often used to quantify this, but this method can be mentally exhausting and prone to error3. A more accurate assessment can be made using baby scales, but small changes in weight during feedings make it difficult to use a scale accurately without training. There is a need for an accessible solution that allows easy assessment of a newborn’s milk intake at home. We developed a mobile application that uses a deep learning model to estimate milk transfer efficiency. Through the detection of audible rhythmic swallowing, a sign of consistent milk intake, this app can provide parents with reassurance that their newborn is receiving enough milk when breastfeeding.

Team Members

    [foreach 357]

  • [if 397 not_equal=””][/if 397][395]

  • [/foreach 357]

Project Mentors, Sponsors, and Partners

Course Faculty

    [foreach 429]

  • [if 433 not_equal=””][/if 433][431]

  • [/foreach 429]

Project Links

Additional Project Information

Project Photo

Project Photo Caption:

The image shows a cartoon mother using the LactaLearn app to monitor her breastfeeding session. The phone is positioned near the baby’s throat to capture swallowing sounds.

Project Video

https://jh.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=bc62aa1b-ef97-4f59-8e47-b0d0015ca165