As long as our medical understanding of neonatal pain expression is subjective and dependent on unreliable factors, its assessment will always be an impediment. Underestimation of pain levels is a common problem in paediatrics. Improving the quality of pain assessment is paramount to ensure adequate infant health care as incorrect or undertreatment can lead to serious, lasting effects on their physiological, neurological and psychological well-being.
While the existing research on the topic of automated pain assessment for neonates shows great promise, nothing has yet translated into a market-ready solution. Our team is working on bridging this very gap. Furthermore, there is strong evidence that demonstrates how assessment results of AI-driven solutions outperform care-givers in paediatric settings.
Building on this and the on-going research, the results of a series of studies we launched in cooperation with various University clinics to collect high quality data, continuous improvements to our software based on specialist inputs and our team of technical experts, we are building an Automated Infant Pain Assessment Tool.