@inproceedings{d30e7574c7b247e1b6bd4fb49ac0808f,
title = "The use of EIT in the detection of regional lung dysfunction in prematurely born neonates",
abstract = "This research describes the progress of work in developing a system for automated detection of regional lung dysfunction in prematurely born neonates. EIT boundary measurements, observed at each lung region, are treated as a time series. The SPIRIT algorithm is used to extract local (regional) and global patterns from the datasets of healthy and ill neonates. The SAX technique is used to derive a symbolic representation of the global pattern signal. Current results are promising and demonstrate the possibility of characterise EIT boundary signals by 'words'. Such a representation can then be used to train a discrete Hidden Markov Model (HMM) to automatically detect and characterise regional lung function.",
author = "A. Zifan and P. Liatsis and R. Bayford",
year = "2009",
doi = "10.1007/978-3-642-03882-2_347",
language = "British English",
isbn = "9783642038815",
series = "IFMBE Proceedings",
publisher = "Springer Verlag",
number = "4",
pages = "1310--1313",
booktitle = "World Congress on Medical Physics and Biomedical Engineering",
address = "Germany",
edition = "4",
note = "World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics ; Conference date: 07-09-2009 Through 12-09-2009",
}