Predicting Survival in Extracorporeal Membrane Oxygenation Patients With Optical Microcirculation Sensing

In this study, we propose a novel method to use functional near-infrared spectroscopy (NIRS) to monitor patients' lower limb microcirculation with extracorporeal membrane oxygenation (ECMO). We controlled the ECMO system's speed and measured hemodynamics using NIRS devices which attached to both calves at approximately 60% of the tibia length. Features from the collected blood oxygen data were extracted and utilized as machine learning inputs for classification. The patients were divided into two groups based on discharge and mortality. In venovenous (VV) ECMO, we found that the construction of the classification model based on the characteristics of this type with better discriminating ability can effectively distinguish the two groups.