Real-time waveform analysis using artificial neural networks

摘要

A real-time waveform analysis system utilizes neural networks to perform various stages of the analysis. The signal containing the waveform is first stored in a buffer and the buffer contents transmitted to a first and second neural network which have been previously trained to recognize the start point and the end point of the waveform respectively. A third neural network receives the signal occurring between the start and end points and classifies that waveform as comprising either an incomplete waveform, a normal waveform or one of a variety of predetermined characteristic classifications. Ambiguities in the output of the third neural network are arbitrated by a fourth neural network which may be given additional information which serves to resolve these ambiguities. In accordance with the preferred embodiment, the present invention is applied to a system analyzing respiratory waveforms of a patient undergoing anesthesia and the classifications of the waveform correspond to normal or various categories of abnormal features functioning in the respiratory signal. The system performs the analysis rapidly enough to be used in real-time systems and can be operated with relatively low cost hardware and with minimal software development required.