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Visualisation and categorisation of respiratory mechanism using self organising maps

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4 Author(s)
Steuer, M. ; Intelligent Comput. Syst. Centre, Univ. of West of England, Bristol, UK ; Caleb, P. ; Drummond, G.B. ; Black, A.M.S.

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

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Science, Measurement and Technology, IEE Proceedings -  (Volume:147 ,  Issue: 6 )