Classificação de sinais EGG combinando Redes Neurais e Análise de Componentes Independentes
Resumo
Identificar características digestivas de pessoas através da Eletrogastrografia (EGG) é importante pois esta costuma ser uma opção barata, não-invasiva e incomoda menos que o tradicional procedimento de Endoscopia. Este trabalho avalia o comportamento do aprendizado das redes neurais artificiais diante de componentes extraídas por algoritmos de Análise de Componentes Independentes (ICA). Foi realizado um experimento com análise estatística cujo objetivo foi apresentar a relação entre a visualização de imagens neutras, negativas ou positivas e as reações digestivas. Os resultados mostraram que extrair apenas a componente do sinal do estômago deve reduzir a taxa de erro do aprendizado das redes neurais artificiais diante do experimento realizado.Referências
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Fausset, L. (1994). Fundamentals of neural network: architectures, algorithms and applications, Prentice Hall.
Gopu, H., Neelaveni, R., Porkumara, K. (2009) Analysis of EGG Signals for Digestive System Disorders Using Neural Networks.
Haykin, S. (1999) Neural Networks A Comprehensive Foundation, Second Edition, Pearson Prentice Hall.
Hubka, P., Rosik, V., Zidnak, J., Tysler, M., Hulin, I. (2005) Independent Component Analysis of Electrogastrographic Signals. Measurement Science Review, Volume 5.
Hyvärinen, A. (1999). Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Networks, Vol10, pp.626-634.
Hyvärinen, A., Karhunen,J., Oja, E. (2001). Independent Component Analysis, Wiley Interscience Publication.
Hyvärinen, A. (1997). A Fast Fixed-Point Algorithm for Independent Component Analysis, Neural Computation.
Komorowski, D., Pietraszek. S. (2009); Preprocessing for Spectral Analysis of Electrogastrogram. WC 2009, IFMBE Proceedings 25/IV.
Kovacs, Z. l. (1996). Redes neurais artificiais: fundamentos e aplicações, um texto básico, Editora Livraria da Física.
Shorack, G. R., Wellner, J. A. (1986). Empirical Processes with Applications to Statistics. Wiley. p. 239.
Todd, M.J. (1976). The computation of fixed points and applications. Springer, Berlin.
Wang, Z., Chen, Z. (1997) Blind EGG Separation Using ICA Neural Networks. 19th International Conference IEEE/EMBS.
Wu, X., Lu, J., Chen, K., Long, Z., Wang, X., Shu, H., Li, K., Liu, Y., Yao, L. (2009) Multiple neural networks supporting a semantic task.
Yu, S., Chou, K. (2006) Combining Independent Component Analysis and Backpropagation Neural Network for ECG Beat Classification. Proceedings of the 28th IEEE EMBS Annual International Conference.
Basili, V. R., Selby, R.W., Hutchens, D. H. (1986). Experimentation in software engineering, IEEE Transactions in Software Engineering 12 (7) 733-743.
Corder, G. W., Foreman, D. I. (2009). Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach.
Comm, P. (1994). Independent component analysis—A new concept? Signal Processing. Vol. 36, pp. 287-314.
Fausset, L. (1994). Fundamentals of neural network: architectures, algorithms and applications, Prentice Hall.
Gopu, H., Neelaveni, R., Porkumara, K. (2009) Analysis of EGG Signals for Digestive System Disorders Using Neural Networks.
Haykin, S. (1999) Neural Networks A Comprehensive Foundation, Second Edition, Pearson Prentice Hall.
Hubka, P., Rosik, V., Zidnak, J., Tysler, M., Hulin, I. (2005) Independent Component Analysis of Electrogastrographic Signals. Measurement Science Review, Volume 5.
Hyvärinen, A. (1999). Fast and robust fixed-point algorithms for independent component analysis. IEEE Trans. Neural Networks, Vol10, pp.626-634.
Hyvärinen, A., Karhunen,J., Oja, E. (2001). Independent Component Analysis, Wiley Interscience Publication.
Hyvärinen, A. (1997). A Fast Fixed-Point Algorithm for Independent Component Analysis, Neural Computation.
Komorowski, D., Pietraszek. S. (2009); Preprocessing for Spectral Analysis of Electrogastrogram. WC 2009, IFMBE Proceedings 25/IV.
Kovacs, Z. l. (1996). Redes neurais artificiais: fundamentos e aplicações, um texto básico, Editora Livraria da Física.
Shorack, G. R., Wellner, J. A. (1986). Empirical Processes with Applications to Statistics. Wiley. p. 239.
Todd, M.J. (1976). The computation of fixed points and applications. Springer, Berlin.
Wang, Z., Chen, Z. (1997) Blind EGG Separation Using ICA Neural Networks. 19th International Conference IEEE/EMBS.
Wu, X., Lu, J., Chen, K., Long, Z., Wang, X., Shu, H., Li, K., Liu, Y., Yao, L. (2009) Multiple neural networks supporting a semantic task.
Yu, S., Chou, K. (2006) Combining Independent Component Analysis and Backpropagation Neural Network for ECG Beat Classification. Proceedings of the 28th IEEE EMBS Annual International Conference.
Publicado
28/07/2014
Como Citar
SANTOS, Hallan; MONTESCO, Carlos A. E.; C. JÚNIOR, Methanias.
Classificação de sinais EGG combinando Redes Neurais e Análise de Componentes Independentes. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 14. , 2014, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2014
.
p. 1724-1733.
ISSN 2763-8952.
