Organisation Name

Deutsche Welthungerhilfe e.V. (WHH)

Industry

Health services

Organisation Website

https://welthungerhilfe.org/

Country

Germany

Sustainable Development Goals (SDGs)

General Description of the AI tool

The Child Growth Monitor digitalizes growth monitoring and detection of malnutrition in children, replacing manual tools with an AI-driven smartphone app. Easy to use after minimal training, it enables accurate, low-cost anthropometric measurements at scale. Users record a short video; neural networks generate a depth map, then compare results to WHO growth charts to identify stunting and wasting in children 6–59 months, providing immediate, reliable nutrition status data.

Github, open data repository

https://github.com/Welthungerhilfe/ChildGrowthMonitor
https://github.com/Welthungerhilfe

Relevant Research and Publications

• Conkle, J., Navarro-Colorado, C., Hossain, S.M. (2018). Accuracy and reliability of a low-cost, handheld 3D imaging system for child anthropometry. PLOS One, 13(10): e0205320.
• Conkle, J., Tong, A., et al. (2019). A collaborative, mixed-methods evaluation of a low-cost, handheld 3D imaging system for child anthropometry. Field Methods, 31(4), 301–318.
• Bougma, C., Conkle, J., et al. (2022). Accuracy of a handheld 3D imaging system for child anthropometric measurements in population-based household surveys. JMIR Public Health and Surveillance, 8(10): e38057.
• Conkle, J., et al. (2023). Portable digital devices for paediatric height and length measurement: A scoping review and target product profile matching analysis. PLOS One, 18(8): e0288995.
• Grellety, E., Golden, M.H. (2016). The effect of random error on diagnostic accuracy illustrated with the anthropometric diagnosis of malnutrition. PLOS One, 11(12): e0168585.

Needs