System and method for noninvasive detection of arterial stenosis

Surgery – Truss – Pad

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128668, 128687, 128713, A61B 500

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active

056388233

ABSTRACT:
A system and method for noninvasively detecting coronary artery disease. The system and method utilize a vasodilator drug to increase the signal-to-noise ratio of an acoustic signal that represents diastolic heart sounds of a patient. A wavelet transform is performed on the acoustic signal to provide parameters for a feature vector. Scaled clinical examination parameters such as a patient's sex, age, body weight, smoking condition, blood pressure, and family history are also included in the feature vector. The feature vector is used as an input pattern to neural networks. The output of the neural networks represent a diagnosis of coronary stenosis in a patient.

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M. Akay et al., "Acoustical Detection of Coronary Occlusions Using Neural Networks", Nov. 1993, J. Biomed. Eng., pp. 469-473.
M. Akay et al., "Investigating the Effects of Vasodilator Drugs on the Turbulent Sound Caused by Femoral Artery Stenosis Using Short-Term Fourier and Wavelet Transform Methods", Oct. 1994, IEEE Transactions, vol. 41, pp. 921-928.
M. Akay, "Noninvasive Diagnosis of Coronary Artery Disease Using a Neural Network Algorithm", (1992), Biological Cybernetics, pp. 361-367.
S. Mallat et al., "Characterization of Signals from Multiscale Edges", Jul. 1992, IEEE Transactionson Pattern Analysis and Machine Intelligence, vol. 14, pp. 710-732.

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