基于埃尔米特多项式和神经模糊网络的在线心跳识别

IMTC/2002. Proceedings of the 19th IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.00CH37276) Pub Date : 2002-08-07 DOI:10.1109/IMTC.2002.1006834

T. H. Linh, S. Osowski, M. Stodolski

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引用次数: 195

摘要

本文提出了一种基于心电波形的神经模糊方法来识别和分类心律。识别的重要部分是完成QRS复合物的Hermite表征。埃尔米特系数是这一过程的特征。将这些特征应用到模糊神经网络中进行识别。数值实验结果证实了该解的良好性能。

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On-line heart beat recognition using hermite polynomials and neuro-fuzzy network

The paper presents the neuro-fuzzy approach to the recognition and classification of heart rhythms on the basis of ECG waveforms. The important part in recognition fulfills the Hermite characterization of the QRS complexes. The Hermite coefficients serve as the features of the process. These features are applied to the fuzzy neural network for the recognition. The results of numerical experiments have confirmed the very good performance of such a solution.

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IMTC/2002. Proceedings of the 19th IEEE Instrumentation and Measurement Technology Conference (IEEE Cat. No.00CH37276)

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