Developing a hidden Markov model for assessing the health of preterm babies
Degree GrantorUniversity of Canterbury
Degree NameBachelor of Science with Honours
Premature babies, because of their underdeveloped biological systems, often display cardiorespiratory instabilities. Yet, at the same time, many paediatric illnesses also affect cardiorespiratory functions. For a certain baby, it can therefore be difficult to determine the cause of such instabilities, and this ramifies on treatment decisions. We look to develop a Hidden Markov Model for modelling the health of preterm babies, as this is useful for uncovering information on the hidden states of a system - in this case, the health of a premature baby. First, we provide a background for the study of Hidden Markov Models; meanwhile, we develop the variants of Hidden Markov Models that are most desirable for our application, and describe how inference can be made in each case.
SubjectsField of Research::01 - Mathematical Sciences::0102 - Applied Mathematics::010202 - Biological Mathematics
- Engineering: Reports