Probabilistic Patient Monitoring with Multivariate, Multimodal Extreme Value Theory - Hugueny, S; Clifton, D; Tarassenko, L (2011)
Conventional patient monitoring is performed by generating alarms when vital signs exceed pre-determined thresholds, but the false-alarm rate of such monitors in hospitals is so high that alarms are typically ignored. We propose a principled, probabilistic method for combining vital signs into a multivariate model of patient state, using extreme value theory (EVT) to generate robust alarms if a patient's vital signs are deemed to have become sufficiently "extreme". Our proposed formulation operates many orders of magnitude faster than existing methods, allowing on-line learning of models, leading ultimately to patient-specific monitoring. © 2011 Springer-Verlag Berlin Heidelberg.