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Expert capnogram analysis

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4 Author(s)
Bao, W. ; Vanderbilt Univ., Nashville, TN, USA ; King, P. ; Zheng, J. ; Smith, B.E.

A real-time expert system that deciphers CO/sub 2/ waveforms (capnograms) is described. The Capnogram Analyzer Expert System (CAES) was designed using both traditional pattern-recognition methods and an artificial intelligence (AI) approach for signal description and classification. The pattern-recognition technique is used to extract features from the digitized CO/sub 2/ waveforms. The AI approach involves abstracting CO/sub 2/ waveforms from numeric representation to higher-level symbolic representation and a so-called reasoning step to analyze the symbolic data. The CAES consists of three essential components: segmentation, single breath cycle identification and waveform classification. Each component is an expert in itself and is responsible for abstracting the waveform information from a lower level to a higher level using its own domain-specific knowledge base.<>

Published in:

Engineering in Medicine and Biology Magazine, IEEE  (Volume:11 ,  Issue: 1 )