Beat-to-beat estimation of stroke volume using impedance cardiography and artificial neural network

Impedance cardiography is a low-cost noninvasive technique, based on monitoring of the thoracic impedance, for estimation of stroke volume (SV). Impedance cardiogram (ICG) is the negative of the first derivative of the impedance signal. A technique for beat-to-beat SV estimation using impedance card...

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Bibliographic Details
Published in:Medical & biological engineering & computing Vol. 56; no. 6; pp. 1077 - 1089
Main Authors: Naidu, S. M. M., Pandey, Prem C., Bagal, Uttam R., Hardas, Suhas P.
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2018
Springer Nature B.V
Subjects:
Artificial neural networks
Back propagation
Back propagation networks
Biomedical and Life Sciences
Biomedical Engineering and Bioengineering
Biomedicine
Cardiography
Computer Applications
Correlation coefficients
Disorders
Doppler effect
Echocardiography
Electrocardiography
Human Physiology
Imaging
Impedance
Neural networks
Original Article
Radiology
Stroke
Stroke volume
Thorax
Doppler echocardiography
Impedance cardiography
Artificial neural networks
Stroke volume
ISSN:0140-0118, 1741-0444, 1741-0444
Online Access:Get full text
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Summary:Impedance cardiography is a low-cost noninvasive technique, based on monitoring of the thoracic impedance, for estimation of stroke volume (SV). Impedance cardiogram (ICG) is the negative of the first derivative of the impedance signal. A technique for beat-to-beat SV estimation using impedance cardiography and artificial neural network (ANN) is proposed. A three-layer feed-forward ANN with error back-propagation algorithm is optimized by examining the effects of number of neurons in the hidden layer, activation function, training algorithm, and set of input parameters. The input parameters are obtained by automatic detection of the ICG characteristic points, and the target values are obtained by beat-to-beat SV measurements from time-aligned Doppler echocardiogram. The technique is evaluated using an ICG-echocardiography database with recordings from subjects with normal health in the under-rest and post-exercise conditions and from subjects with cardiovascular disorders in the under-rest condition. The proposed technique performed much better than the earlier established equation-based estimations, and it resulted in correlation coefficient of 0.93 for recordings from subjects with cardiovascular disorders. It may be helpful in improving the acceptability of impedance cardiography in clinical practice. Graphical abstract ᅟ
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ISSN:0140-0118
1741-0444
1741-0444
DOI:10.1007/s11517-017-1752-5