CSBS Small Grant Success Story: Nancy McElwain

Nancy McElwain
Professor Nancy McElwain

Nancy McElwain, PhD, is a professor in the Department of Human Development & Family Studies and the Beckman Institute for Advanced Science and Technology, with affiliate appointments in the Center for Social and Behavioral Science (CSBS), the Family Resiliency Center, and the Personalized Nutrition Initiative in the Carle R. Woese Institute for Genomic Biology. Prof. McElwain’s research advances the understanding of the dynamic early-life interactions between parents and children that shape children’s developing abilities to regulate stress. She adopts an interdisciplinary approach that combines neuroscience, psychophysiology, linguistics, and developmental psychology. Through investigating stress regulation during early development, she aims to promote healthy parent-child relationships and children’s long-term social and emotional well-being.

What motivated you to apply for a CSBS small grant?
Broadly, my research focuses on early social and emotional development during infancy and toddlerhood, and particularly, how children learn to regulate stress. Over the course of many studies here at Illinois, laboratory observations have been a mainstay of my research. Yet, these methods have limitations. Lab observations tend to be brief and may not represent children’s everyday experiences. Observational data also require manual coding, which is very time and labor intensive, particularly if it involves coding multiple behavior second by second. So, with these limitations in mind, I wanted to explore innovative ways to assess young children’s social and emotional development in real time and in their real-world environments. A seed grant from CSBS provided the support needed to start up this line of research.

Tell us briefly about your research project.
Over the past several years, our research team has worked to develop and validate a wearable platform, LittleBeats, designed specifically for use with infants and young children. LittleBeats is worn in the front pocket of a specially designed shirt and synchronously records children’s movements, stress physiology, and vocalizations in the home. As part of the LittleBeats platform, we’ve developed machine learning algorithms to measure infant babbling, crying, and body position, as well as vocal turn-taking with family members as they unfold moment by moment over the course of the day. By collecting large-scale, multimodal data via LittleBeats, we are able to obtain more fine-grained and ecologically valid assessments of development than have not been possible using more traditional methods.

In what ways did the CSBS Small Grant Program help you to connect with interdisciplinary collaborators at Illinois?
The CSBS Small Grants Program was critical to initiating collaborations with engineers to develop the LittleBeats hardware and software. Most notably, Professors Mark Hasegawa-Johnson and Romit Roy Choudhury in the Department of Electrical and Computer Engineering, along with their graduate students Jialu Li and Ashutosh Dhekne (now at Georgia Tech) and postdoc Bashima Islam (now at Worcester Polytechnic Institute) have been key members of the LittleBeats team. Although our primary focus has been developing LittleBeats to assess the infants’ and young children’s stress regulation in their natural environments, our interdisciplinary collaborations are growing in exciting directions, including researchers and clinicians both on and off campus, to further develop the LittleBeats platform for use in research on developmental delays, physical activity and sedentary behavior, and sleep.

What did the interdisciplinary collaboration allow you to do that you would not have been able to do on your own or with collaborators from your own discipline?
Simply put, our LittleBeats projects would not be possible without strong interdisciplinary collaborations with engineering faculty and students. Although there have been tremendous advances in wearable technology and related machine learning algorithms to monitor individuals’ behavior and physiology, very few wearables have been developed specifically with infants and young children. Conducting this sort of research with children, especially infants and toddlers, poses unique challenges. For instance, the hardware needs to be extremely compact, lightweight, and child-proof. Also, infants’ movements and vocalizations differ qualitatively from adults’ behavior, so the algorithms developed for adults cannot be directly applied to infant data but require training on infant data specifically. Our LittleBeats collaborations have led to innovations in both behavioral sciences and engineering precisely because of the interdisciplinary nature of the work, and that has been very rewarding.

How did the initial CSBS Small Grant funding aid in your external funding efforts?
Initial CSBS funding aided our ability to obtain external funding in several ways. In a basic but important way, we were able to demonstrate a record of collaboration among a highly interdisciplinary team. Through our small grant research activities, we also generated preliminary data to demonstrate “proof of concept” and feasibility of the LittleBeats data collection procedures and data processing steps. Last but not least, we have several peer-reviewed publications reporting the validity of our machine learning algorithms.

What advice do you have for Illinois faculty and staff who may be interested in applying for a CSBS Small Grant?
Take advantage of this small grant opportunity to move your research forward in exciting directions that you might otherwise not consider. Use it as an opportunity to initiate or strengthen a collaboration with a researcher from another discipline. Focus on a “proof of concept” project that will help strengthen an application for external funding.