We are working with the Woolcock Institute to develop improved anomaly detectors for breathing cycles using the forced oscillatory technique . This improves the quality of the data collected and hence the utility of the technique.
 Thuy T. Pham, Cindy Thamrin, Paul D. Robinson, Alistair L. McEwan, and Philip H.W. Leong. Respiratory artefact removal in forced oscillation measurements: A machine learning approach. IEEE Transactions on Biomedical Engineering, 2016. In press.
We developed analog VLSI chips for the low power classification of abnormal heart rhythms from intracardiac leads . The scheme combined morphology and timing information  to achieve better accuracy than previous techniques. The feasibility of this approach for implantable defibrillator devices was demonstrated.
 P. H. W. Leong and M.A. Jabri. A low power VLSI arrhythmia classifier. IEEE Transactions on Neural Networks, 6(6):1435–1445, November 1995.
 P.H.W. Leong and M. Jabri. Matic – an intracardiac tachycardia classification system. Pacing and Clinical Electrophysiology (PACE), 15:1317–1331, September 1992.
 P.H.W. Leong and M.A. Jabri. A method and system for automatically classifying intracardiac electrograms. US Patent 5,280,792, January 25, 1994. University of Sydney.