Medical diagnostics for neonates in the developing world
Summary
There is an urgent clinical need to develop diagnostic devices to assess the health of newborns. For example the World Health Organisation estimates that malnutrition contributes to more than half of child deaths in the developing world (Bryce et. al., Lancet, 2005) and calls for a low cost device to measure malnutrition. While in both developing and the developed world jaundice is common in over 70% of newborns but trained examiners make poor estimations of severity (Madlon-Kay et. al. Paediatrics 1997). Devices exist for assessing these conditions however they are typically too expensive for the developing world. With the School of Public Health and RPA, this project involves assessing basic physical measurements to identify the optimal low cost methods for assessing the health of newborns and developing medical devices to implement these methods.
Supervisor(s)
Professor Alistair McEwan, Associate Professor Craig Jin, Professor Philip Leong
Research Location
Electrical and Information Engineering
Program Type
Masters/PHD
Synopsis
There is an urgent clinical need to develop diagnostic devices to assess the health of newborns. For example the World Health Organisation estimates that malnutrition contributes to more than half of child deaths in the developing world (Bryce et. al., Lancet, 2005) and calls for a low cost device to measure malnutrition. While in both developing and the developed world jaundice is common in over 70% of newborns but trained examiners make poor estimations of severity (Madlon-Kay et. al. Paediatrics 1997). Devices exist for assessing these conditions however they are typically too expensive for the developing world. With the School of Public Health and RPA, this project involves assessing basic physical measurements to identify the optimal low cost methods for assessing the health of newborns and developing medical devices to implement these methods.
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Keywords
Biomedical Instrumentation, Signal Processing, Medical Electronics, Neonatal Health
Opportunity ID
The opportunity ID for this research opportunity is: 947
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- Mapping 2D Images to 3D Shape
- New technique for studying human brain activity
- Next Generation Audio Coding
- Spherical multi-modal scene analysis
- Statistical models of ear shape and ear acoustics
- Binaural signal processing algorithms for hearing aids
- Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
- Impedance tomography for cardiac imaging: high speed tomography
- Novel Electrodes for rapid electrophysiological recording
- FPGA-based low latency machine learning
Other opportunities with Professor Philip Leong
- FPGA-based low latency machine learning
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- Mapping 2D Images to 3D Shape
- New technique for studying human brain activity
- Next Generation Audio Coding
- Spherical multi-modal scene analysis
- Statistical models of ear shape and ear acoustics
- Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
- Impedance tomography for cardiac imaging: high speed tomography
- Novel Electrodes for rapid electrophysiological recording
- Binaural signal processing algorithms for hearing aids