Signal processing applications in clinical newborn medicine to improve health outcomes

Signal processing offers real opportunities to improve diagnosis and management of clinical medical conditions. The gap between basic science research and how this knowledge can be used to impact on clinical medical outcomes through the translational research process is receiving international focus. Signal processing has already impacted in the translational research setting and I discuss several clinical problems in my own area of specialization where signal processing applications have had a positive impact. Sick babies are at risk of brain injury and require accurate diagnosis, monitoring and prognostication. The electroencephalogram (EEG) provides continuous physiological functional data and I describe an approach to automated analysis of abnormalities. Unexpected death in utero in late pregnancy is another significant clinical problem. We have developed an accelerometer based system with automated analysis that holds potential to reduce fetal death (stillbirth). Applications and opportunities for signal processing to improve health outcomes are presented and the desirable features of successful multi-disciplinary research teams are outlined and discussed.