Seizure detection in neonates: Improved classification through supervised adaptation (original) (raw)

Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008

Abstract

The goal of neonatal seizure detection is the development of a patient independent system to alert staff in the neonatal intensive care unit of ongoing seizures. This study demonstrates the potential in adapting a patient independent classifier using patient specific data. Supervised adaptation is investigated using the basic gradient descent algorithm and least mean squares procedures. An increase in mean

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