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Embolic signals characterization using wavelet networks
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Orientador(es)
Resumo(s)
Cerebral embolism represents a major cause of
stroke. While embolic signal can be detected using transcranial Doppler (TCD) ultrasound, there are limitations in this technique that makes it difficult to differentiate between gaseous and solid emboli and artifacts.
In this paper, we report the application of emergent signal processing techniques in the analysis and classification of embolic signals. The Wavelet Neural Network (WNN) is used to approximate the signals and the parameters from the wavelets that best fit each signal are used as inputs to train a
Neural Network (NN) for classifying them as
normal signals, or gaseous or solid embolic signals.
Descrição
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Contexto Educativo
Citação
Matos, S.; Ruano, M. G.; Ruano, A. E.; Evans, D. H. Embolic Signals Characterization using Wavelet Networks, Trabalho apresentado em 6th Portuguese Conference on Biomedical Engineering (BioEng’2001), In 6th Portuguese Conference on Biomedical Engineering (BioEng’2001), Faro, 2001.