Infant sleep patterns and emotional regulation are important for healthy development, but it is challenging to get real-time insights into infant behavior. Researchers at the University of Illinois Urbana-Champaign received two major grants from the National Institutes of Health to study infant development with innovative technology.

The principal investigators are Nancy McElwain, professor of human development and family studies in the College of Agricultural, Consumer and Environmental Sciences, and Mark Allan Hasegawa-Johnson, professor of electrical and computer engineering. Both are also affiliated with the Beckman Institute at Illinois.

For both studies, the researchers will use LittleBeats, a small, wearable device developed by the research team. Featuring a microphone, electrocardiogram, and motion sensors, it collects a wealth of information in the infant’s natural environment with minimal effort from participants. The infant wears the device in the pocket of a specially designed shirt.

McElwain and Hasegawa-Johnson will combine the innovative wearable technology with cutting-edge deep learning algorithms to provide detailed assessments of infant behavior in real-world settings. 

The first grant, from the NIH’s National Institute on Drug Abuse, addresses infant-parent interactions and how they affect the infant’s emotional regulation. The findings from this study will be particularly relevant to assessing and intervening with infants who have experienced prenatal substance exposure.

“Lab methods to measure parent-infant interactions provide limited insights. Our multi-modal technology provides a granular level of detail on parent-infant interaction, infant heart rate, and physical activity. This information can greatly enhance our understanding of the dynamic processes that are integral to infant development and help identify protective factors for optimal outcomes,” McElwain said.

The second grant, from the NIH’s National Institute of Diabetes and Digestive and Kidney Diseases, focuses on infant sleep/wake patterns and health outcomes. Current sleep monitoring tools are typically developed for adults and older kids, and are less suitable for infants. The LittleBeats technology allows for continuous monitoring of infant sleep/wake states, physical activity, sedentary behavior, and household noise.

The data will provide insight into the interdependencies among infant health behaviors and the environments in which they occur. Ultimately, these intensive, personalized data obtained in natural environments will be used to aid in early detection, monitoring, and intervention among infants at risk for sleep disturbances, obesity, and other poor health outcomes.

The first grant, “Validation of a virtual still face procedure and deep learning algorithms to assess infant emotion regulation and infant-caregiver interactions in the wild,” is funded by the National Institute on Drug Abuse, through the NIH Helping to End Addiction Long-term Initiative, or NIH HEAL Initiative, award no. R01DA059422.

The second grant, “Automated assessment of infant sleep/wake states, physical activity, and household noise using a multimodal wearable device and deep learning models,” is funded by the National Institute of Diabetes and Digestive and Kidney Diseases, award no. R01DK138866.

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.