Research
Multimodal Assessment of Neonatal Pain Using Computer Vision
Infants receiving care in the Neonatal Intensive Care Unit (NICU) experience several painful procedures during their hospitalization. Assessing neonatal pain is difficult because the current standard for assessment is subjective, inconsistent, and discontinuous. The intermittent and inconsistent assessment can induce poor treatment and, therefore, cause serious longterm outcomes. The main aim of this project is to develop a robust and comprehensive automatic system that generates a standardized pain assessment comparable to those obtained by conventional nurse-derived pain scores. The continuous monitoring of pain, using affordable, non-invasive, and easily integrable devices, provides immediate pain detection and intervention, and therefore, contribute to improved long term outcomes; i.e., reduce the outcomes of under- and over-treatment. It can also decrease caregivers鈥� bias and assessment burden. While further research is needed, the preliminary results of our research showed that the automatic assessment of neonatal pain is a viable and more efficient alternative to the manual assessment.