Design of Neonatal Seizure Diagnosis Methods Using Time-Frequency Signal Processing Techniques [ 2006-09-18 - 2009-12-31 ]

Research Grant

Researchers: Prof Boualem Boashash (Chief Investigator) ,  Professor Paul Colditz (Chief Investigator)

Brief description Design of Neonatal Seizure Diagnosis Methods Using Time-Frequency Signal Processing Techniques. Seizures occur in approximately 0.5% of all newborns. They are often the only indicator of an early dysfunction in central nervous system (CNS). Their occurrence raises concerns about the underlying cause, its effect on the brain, and the appropriate treatment. Newborn seizures are mostly sub-clinical and only detected through the Electroencephalogram. For an efficient diagnosis, seizure classification systems were proposed based on visual observations. This project proposes developing a novel approach to automate the classification process using time-frequency (TF) signal processing techniques based on the multi-channel characteristics of the seizure; namely: A) TF signature B) origin, and C) propagation behaviour.

Funding Amount $190,000

Funding Scheme Linkage Projects

View this grant in the ARC Data Portal