The study's findings mostly validated clinician conclusions. 'We hope our findings help support parents struggling to breastfeed and improve long-term health outcomes.' 'It's reassuring for me to rely on scientific data to back up my assessments,' said co-senior author of the study, Erin Walsh, a speech-language pathologist and lactation consultant at UC San Diego Health. Prior studies have shown that non-nutritive suckling on a pacifier produces data that can be used to evaluate breastfeeding. Two different machine learning algorithms analyze the data and flag abnormal patterns if they are present. The software records data as an infant sucks on the pacifier and compares that data with information from other infants. The second component is software that both displays the data and uses machine learning algorithms to identify abnormalities and outliers. 'We wanted to keep the technology as simple as possible with off-the-shelf, cost-effective components to facilitate adoption in the clinic,' said Friend, who is a faculty member at the UC San Diego Jacobs School of Engineering. One is a device made up of a simple pacifier, connected to a 36-inch-long tube connected in turn to a vacuum sensor and a chip that collects the data from the sensor. 'The method we developed with our clinical partners replaces this subjective assessment with objective data,' said James Friend, a professor in the Department of Mechanical and Aerospace Engineering and the Department of Surgery at UC San Diego and one of the paper's senior authors. One is objective: is the baby gaining enough weight? The other is more subjective: clinicians put a finger in the baby's mouth and evaluate how well the baby is sucking on that finger. The results, published in the April 18 online edition of IEEE Journal of Translational Engineering in Health and Medicine, give researchers objective data that shows standard assessments can be improved and could potentially prevent surgical interventions.Ĭurrently, to determine if an infant is feeding properly, clinicians rely on two measures. Specifically, the researchers from the University of California San Diego measured if babies are generating enough suckling strength to breastfeed and whether they are suckling in a regular pattern based on eight independent parameters.

Things for newborns