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Neural Network Analysis Of Physiologic Waveforms

We have developed an artificial neural network (ANN)-based waveform analyzer for real-time analysis of events in physiological signals. Events are captured and analyzed on a PC-386 by four ANNs embedded in a C-language executable program. This paper describes the techniques used for: 1) Identification of the event in a time series using ANNs; 2) Normalization of the captured event; 3) ANN classification of the event's morphology; and 4) Contextual interpretation of the output of the classification ANN by an "arbitration" ANN. An anesthesiology monitoring application is presented whereby the respiratory CO, concentration versus time (capnogram) is analyzed in real-time to detect several patient and breathing circuit abnormalities.