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.

Keywords

Biomedical Instrumentation, Signal Processing, Medical Electronics, Neonatal Health

Opportunity ID

The opportunity ID for this research opportunity is: 947

Other opportunities with Professor Alistair McEwan

• 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
• Implant electrode optimisation and neurolinguistics
• Subdivided electrodes to improve defibrillators and physiological measurements
• Electrical impedance modelling for implants
• Magnetic resonance electrical impedance tomography
• Development of a microwave catheter for cardiac ablation to treat ventricular tachycardia
• Resuscitation monitors for the neonatal intensive care uni (NICU)
• ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ASSISTED NEWBORN CRITICAL CARE (VIRTUAL CRITICAL CARE MODELING)
• 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
• FPGA-based low latency machine learning

Other opportunities with Associate Professor Craig Jin

• Pattern analysis techniques for sound synthesis
• Interpolation of binaural impulse responses for virtual auditory displays
• Sound field recording and recreation
• Beamforming with acoustic vector sensors - Multiple acoustic source localisation using acoustic vector sensor arrays
• Speech separation and localisation using particle filtering
• 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
• FPGA control of photonic systems
• 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