Dr Stephanie Baker ~ Lecturer, Electronic Systems and Internet of Things Engineering

Dr Stephanie Baker received her PhD from James Cook University in 2021, with her dissertation focusing on the use of machine learning for health monitoring. Prior to that, Stephanie graduated with a Bachelor of Engineering (Computer Systems) degree from James Cook University in 2016.

Stephanie is now continuing to research in the field of healthcare, while also expanding into areas including remote sensing and accessibility. She has a broad range of research interests, with primary focus placed on machine learning and software.

Teaching

• EE2300: Electronics 1 (Level 2; CNS)
• EG1002: Computing and Sensors (Level 1; CNS)
• EG1012: Electric Circuits (Level 1; CNS)

Research Disciplines

• Health services and systems (4203)
• Biomedical engineering (4003)
• Communications engineering (4006)

Socio-Economic Objectives

• Public health (2004)
• Clinical health (2001)

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles

• Baker S, Xiang W and Atkinson I (2021) A hybrid neural network for continuous and non-invasive estimation of blood pressure from raw electrocardiogram and photoplethysmogram waveforms. Computer Methods and Programs in Biomedicine, 207, Article: 106191, DOI:10.1016/j.cmpb.2021.106191.
• Baker S, Xiang W and Atkinson I (2021) Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates. Computers in Biology and Medicine, 134, Article: 104521, DOI:10.1016/j.compbiomed.2021.104521.
• Baker S, Xiang W and Atkinson I (2021) Determining respiratory rate from photoplethysmogram and electrocardiogram signals using respiratory quality indices and neural networks. PLoS ONE, 16 (4), Article: e0249843, DOI:10.1371/journal.pone.0249843.
• Baker S, Xiang W and Atkinson I (2020) Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach. Scientific Reports, 10, Article: 21282, DOI:10.1038/s41598-020-78184-7.
• Baker S, Xiang W and Atkinson I (2017) Internet of Things for smart healthcare: technologies, challenges, and opportunities. IEEE Access, 5, pp. 26521-26544, DOI:10.1109/ACCESS.2017.2775180.