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International Conference on Brain Informatics and Health

BIH 2014: Brain Informatics and Health pp 400–411Cite as

Application of Artificial Neural Networks for the Diagnosis of the Condition of the Arterio-venous Fistula on the Basis of Acoustic Signals

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8609))

Abstract

The paper presents an innovative method for the diagnosis of the arterio-venous fistula based on recorded acoustic signals. A fistula is an artificial connection between an artery and a vein made to obtain a suitably large blood flow for haemodialysis. If the fistula does not work properly, thrombosis or other health- or life-threatening conditions may develop. Based on the analysis of sound generated by blood flowing through the fistula, the occurrence of pathological conditions may be diagnosed. An artificial neural network implemented using an FANN (Fast Artificial Neural Network) library has been used to evaluate the fistula condition.

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References

  1. Ranachowski, Z.: Metody pomiaru i analiza sygnau emisji akustycznej. Prace IPPT PAN, l, Warszawa (1997)

    Google Scholar 

  2. Grosse, C., Ochtsu, M. (eds.): Acoustic Emission Testing. Basic for Research - Applications in Civil Engineering. Springer, Berlin (2008)

    Google Scholar 

  3. Rutowski, B.: Dializoterapia w praktyce lekarskiej MAKmedia, Gdask (2004)

    Google Scholar 

  4. Daugirdas, J.T., Blake, P.G., Ing, T.S.: Handbook of dialysis. Lippincott Williams & Wilkins (2007)

    Google Scholar 

  5. Steffen Nissen, FANN reference manual

    Google Scholar 

  6. Bedregal1, B.C., Reiser, R.H.S., Dimuro, G.P.: Xor-Implications and E-Implications: Classes of fuzzy implications based on fuzzy Xor LSFA (2008)

    Google Scholar 

  7. http://sourceforge.net/projects/kissfft

  8. Chu, E., George, A.: Inside the FFT BLACK BOX - Serial and Parallel Fast Fourier Transform. CRC Press LLC (2000)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Technology, University of Rzeszów, al. Rejtana 16, 35-310, Rzeszów, Poland

    Marcin Grochowina & Lucyna Leniowska

  2. Nefron Sp z o.o., Rzeszów, Poland

    Piotr Dulkiewicz

Authors
  1. Marcin Grochowina
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  2. Lucyna Leniowska
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  3. Piotr Dulkiewicz
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Editor information

Editors and Affiliations

  1. University of Warsaw and Infobright Inc., Poland

    Dominik Ślȩzak

  2. School of Computer Engineering, Nanyang Technological University, Nanyang Avenue, Singapore

    Ah-Hwee Tan

  3. Computational Intelligence Laboratory, ECE Department, University of Manitoba, R3T 5V6, Winnipeg, MB, Canada

    James F. Peters

  4. Institute of Computer Science, University of Rostock, Rostock, Germany

    Lars Schwabe

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© 2014 Springer International Publishing Switzerland

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Cite this paper

Grochowina, M., Leniowska, L., Dulkiewicz, P. (2014). Application of Artificial Neural Networks for the Diagnosis of the Condition of the Arterio-venous Fistula on the Basis of Acoustic Signals. In: Ślȩzak, D., Tan, AH., Peters, J.F., Schwabe, L. (eds) Brain Informatics and Health. BIH 2014. Lecture Notes in Computer Science(), vol 8609. Springer, Cham. https://doi.org/10.1007/978-3-319-09891-3_37

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  • DOI: https://doi.org/10.1007/978-3-319-09891-3_37

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09890-6

  • Online ISBN: 978-3-319-09891-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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