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BACKGROUND-The goal of this study was to determine a set of timing, shape, and statistical features available through non-invasive monitoring of maternal electrocardiogram and photoplethysmography that identifies preeclamptic patients.METHODS-Pregnant women admitted to Labor and Delivery were monitored with pulse oximetry and electrocardiogram for 30 min. Photoplethysmogram features and heart rate variability were extracted from each data set and applied to a sequential feature selection algorithm to discriminate women with preeclampsia with severe features, from normotensive and hypertensive controls. The classification boundary was chosen to minimize the expected misclassification cost. The prior probabilities of the misclassification costs were assumed to be equal.

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