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

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Project Mentors, Sponsors, and Partners

• Azadeh Farzin, MD

• Monique Solieau-Burke, MD

• Elizabeth Logsdon, PhD

• Unnathi Annapurna Shashikumar

Course Faculty

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Project Links

• Project Poster Image

• Project Poster PDF

Additional Project Information