• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.281-282
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• 2016

The electrical current generated by heart creates not only electric potential but also a magnetic field. In this study, the signals obtained magnetocardiogram (MCG) using 61 channel superconducting quantum interference device(SQUID) system the clinical significance of various parameters has been developed MCG. Neural network algorithm was used to perform the analysis of heart disease.

• 한국초전도학회:학술대회논문집
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• v.14
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• pp.66-66
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• 2004

• 한국초전도학회:학술대회논문집
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• v.15
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• pp.54-54
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• 2005

• Progress in Superconductivity and Cryogenics
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• v.22 no.4
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• pp.1-5
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• 2020

Heart consists of myocardium cells and the electrophysiological activity of the cells generate magnetic fields. By measuring this magnetic field, magnetocardiogram (MCG), functional diagnosis of the heart diseases is possible. Since the strength of the MCG signals is weak, typically in the range of 1-10 pT, we need sensitive magnetic sensors. Conventionally, superconducting quantum interference devices (SQUID)s were used for the detection of MCG signals due to its superior sensitivity to other magnetic sensors. However, drawback of the SQUID is the need for regular refill of a cryogenic liquid, typically liquid helium for cooling low-temperature SQUIDs. Efforts to eliminate the need for the refill in the SQUID system have been done by using cryocooler-based conduction cooling or use of non-cryogenic sensors, or room-temperature sensors. Each sensor has advantage and disadvantage, in terms of magnetic field sensitivity and complexity of the system, and we review the recent trend of MCG technology.

• Journal of Biomedical Engineering Research
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• v.27 no.2
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• pp.59-63
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• 2006

Magnetocardiogram (MCG) topography is a useful diagnostic technique that employs multi-channel magnetocardiograms. Measurement of artifact-free MCG signals is essenctial to obtain MCG topography or map for a diagnosis of human heart. Principal component analysis (PCA) combined with an artificial neural network (ANN) is proposed to remove a pulse-type artifact in the MCG signals. The algorithm is composed of a PCA module which decomposes the obtained signal into its principal components, followed by an ANN module for the classification of the components automatically. In the experiments with volunteer subjects, 97% of the decisions that were made by the ANN were identical to those by the human experts. Using the proposed technique, the MCG topography was successfully obtained without the artifact.

• 한국초전도학회:학술대회논문집
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• v.16
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• pp.9-9
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• 2006

• 한국초전도학회:학술대회논문집
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• v.14
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• pp.54-54
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• 2004

• Progress in Superconductivity
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• v.11 no.2
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• pp.147-151
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• 2010

We have developed a high-$T_c$ SQUID magnetocardiogram (MCG) system for small laboratory animals. White noise of the measurement system was about 30 fT/$Hz^{1/2}$ when measured in a magnetically shielded room. We optimized the measurement position to obtain clear MCG wave from rat's small heart by using grid measurements. With the optimization, the MCG signal was successfully detected with the peak amplitude of about 30 pT. We could observe well defined P-, QRS-, and T-waves from the rat MCG. The results suggest that the developed system has a strong potential to monitor the progress of the heart disease model by using a laboratory rat.

• 한국초전도학회:학술대회논문집
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• 2009.07a
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• pp.73-73
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• 2009

• 한국초전도학회:학술대회논문집
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• v.15
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• pp.11-11
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• 2005