• 제목/요약/키워드: Magnetocardiogram

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심자도 데이터의 신경망 분석 (An Analysis of Magnetocardiogram Data using Neural Network)

  • 엄상희
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2016년도 추계학술대회
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    • pp.281-282
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    • 2016

  • 심장에 의해 발생된 전류는 단지 전위뿐만 아니라 자기장을 생성한다. 이 논문은 양자 간섭 장치(SQUID) 시스템의 초전도 61 채널의 심자도(MCG) 시스템의 파라미터를 이용하여 신경회로망 알고리즘으로 심장 질환의 진단을 위한 분석을 수행하였고, 질환 진단에 사용 가능한 결과를 얻었다.

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The latest trend in magnetocardiogram measurement system technology

  • Lee, Y.H.;Kwon, H.;Kim, J.M.;Yu, K.K.
    • 한국초전도ㆍ저온공학회논문지
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    • 제22권4호
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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.

  • https://doi.org/10.9714/psac.2020.22.4.001 인용 PDF KSCI

Magnetocardiogram Topography with Automatic Artifact Correction using Principal Component Analysis and Artificial Neural Network

  • Ahn C.B.;Kim T.H.;Park H.C.;Oh S.J.
    • 대한의용생체공학회:의공학회지
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    • 제27권2호
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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.

  • https://doi.org/10.9718/JBER.2006.27.2.059 인용 PDF KSCI

Multichannel SQUID Systems for Magnetocardiogram

  • Lee, Y.H.;Kim, J.M.;Kim, K.;Kwon, H.;Yu, K.K.;Kang, C,S.;Lee, S.K.;Lim, C.M.;Kim, I.S.;Park, Y.K.
    • 한국초전도학회:학술대회논문집
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    • 한국초전도학회 2006년도 High Temperature Superconductivity Vol.XVI
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    • pp.9-9
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    • 2006

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백서를 이용한 심자도 신호 측정 (Magnetocardiogram Measurement of Laboratory Rat)

  • 김인선;안산;권혁찬;송종현
    • Progress in Superconductivity
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    • 제11권2호
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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.

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