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Dr. Philip A. Warrick obtained a B.A.Sc. (Electrical Engineering) from the University of Waterloo (Waterloo, Canada), and a M.Eng. (Electrical Engineering) and Ph.D. (Biomedical Engineering) from 看片视频 University (Montreal, Canada). His research interests lie in the fields of systems modelling, statistical signal processing, machine learning (including deep learning), decision support systems, cardiology and obstetrics. His interest in novel intra-partum signal modelling and associated diagnostic tools, where he has an active publishing record in the scientific literature, has exposed areas of improvement for current clinical cardiotocography (ultrasound for fetal heart rate and tocography for maternal uterine pressure) that new sensor research and technology has begun to address by providing surface electrode acquisition of both fetal electrocardiography (ECG) and maternal uterine pressure as electrohysterography (EHG). These developments facilitate research into higher quality models, in terms of signal-to-noise ratio and information extraction, to improve intrapartum diagnosis of the fetal state. Many aspects of fetal heart rate interpretation share commonality with other biomedical signals, especially with other currently challenging issues in cardiology. He has directed successful research projects involving fetal ECG detection from abdominal sensors; adult ECG; phonocardiogram classification for early diagnosis of arrhythmias; and arousal detection from polysomnography.

Keywords:
Biomedical Signal Processing
Machine Learning
Cardiology
Obstetrics