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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© 2014 Springer International Publishing Switzerland
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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
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