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Visualisation and categorisation of respiratory mechanism using self organising maps

Caleb, P.; Black, A. M.S.; Caleb-Solly, Praminda; Steuer, M.; Black, A. M. S.; Drummond, G. B.

Authors

P. Caleb

A. M.S. Black

Praminda Caleb-Solly

M. Steuer

A. M. S. Black

G. B. Drummond



Abstract

In post-operative patients it is sometimes necessary to push morphine-like analgesics to their limits for pain relief. Unfortunately, this can sometimes bring a significant risk of disrupting the control of breathing, and of precipitating life-threatening conditions. A possible way of monitoring patients is by studying the correlation between analgesia, airway obstruction and hypoxia. The first step towards achieving this objective is by visualising the relationship between different pairs of signals involved in respiratory mechanics. Based on previous work, where self-organising maps (SOMs) were used for representing these relationships on a breath by breath basis, it is demonstrated how it is now possible to automatically label nodes in the SOMs based on classification of the signals by a clinician. The use of a majority voting configuration of SOMs enables results to be presented with a confidence measure which enhances the medical applicability of the system. In addition, the ability to now visualise the transition between categories will enable further research into the significance of transition between the categories and the presence of possible new sub-categories. © IEE, 2000.

Citation

Black, A. M., Caleb, P., Steuer, M., Caleb-Solly, P., Drummond, G. B., & Black, A. M. S. (2000). Visualisation and categorisation of respiratory mechanism using self organising maps. IEE Proceedings Science Measurement and Technology, 147(6), 339-344. https://doi.org/10.1049/ip-smt%3A20000856

Journal Article Type Article
Publication Date Dec 1, 2000
Journal IEE Proceedings: Science, Measurement and Technology
Print ISSN 1350-2344
Publisher Institution of Engineering and Technology (IET)
Peer Reviewed Peer Reviewed
Volume 147
Issue 6
Pages 339-344
DOI https://doi.org/10.1049/ip-smt%3A20000856
Keywords medical signal processing, patient monitoring, pneumodynamics, self-organising feature maps, surgery, airway obstruction, breathing control disruption, clinician, morphine-like analgesics, pain relief, post-operative patients, respiratory mechanics, respi
Public URL https://uwe-repository.worktribe.com/output/1095976
Publisher URL http://dx.doi.org/10.1049/ip-smt:20000856