Prediction of Acute Hypotension Episodes in Patients Taking Pressor Medication Using Modeling of Arterial Blood Pressure Waveforms

This paper presents an effective technique for solving the prediction problem presented in Event-1 of Physionet Challenge 2009. In this challenge, the prediction of occurrence of an Acute Hypotension Episode (AHE) is to be made (in patients receiving pressor medication) using clinical data and medical signals prior to the start of a forecast window. The technique proposed in this paper uses time domain features along with principal components of the Arterial Blood Pressure (ABP) waveform averaged over beats lying in each non-overlapping 60s interval for 1.5 hours prior to the start of the forecast window. Classification is performed with a simple Linear Support Vector Classifier (LSVC) after feature selection through genetic algorithms. This method uses only 5 features to give a perfect score of 10/10 over data in event-1 test set.