Abstract
This paper proposes a new method to discriminate the vascular conditions from biological signals by using a probabilistic neural network, and develops the diagnosis support system to judge the patient’s conditions on-line. For extracting vascular features including biological signals, we model the dynamic characteristics of an arterial wall by using mechanical impedance and estimate the impedance parameters ”beat-to-beat”. As a result, this system can be utilized for the actual surgical operation, and the vascular conditions can be discriminated with high accuracy using the proposed method.
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Sakane, A., Tsuji, T., Tanaka, Y., Shiba, K., Saeki, N., Kawamoto, M. (2004). Realtime Monitoring of Vascular Conditions Using a Probabilistic Neural Network. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_78
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DOI: https://doi.org/10.1007/978-3-540-28648-6_78
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
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