Edge AI for Low Power, Real-Time Detection of Fetal Compromise

Abstract

Fetal compromise is a significant global health issue that can result in severe long-term disability and mortality. Current fetal monitoring is predominantly performed using cardiotocography (CTG) machines in healthcare settings, limiting clinical oversight to routine hospital visits or during labor. CTG monitoring typically relies on intermittent visual interpretation, sometimes resulting in inconsistent clinical judgement and delayed intervention. Artificial intelligence (AI) has been proposed to assist in CTG interpretation, but conventional AI models require substantial computational resources, making them impractical for wearable, battery-powered devices designed for continuous monitori..