• 한국초전도학회:학술대회논문집
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• v.12
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• pp.45-45
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• 2002

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.444-447
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• 2004

A heart diagnosis system adopts hundreds of Superconducting Quantum Interface Device(SQUID) sensors for precision MCG(Magnetocardiogram) or MEG(Magnetoencephalogram) signal acquisitions. This system requires correct and real-time data acquisition from the sensors in a required sampling interval, i.e., 1 mili-second. This paper presents our hardware design and test results, to acquire data from 256 channel analog signal with 1-ksample/sec speed, using 12-bit 8-channel ADC devices, SPI interfaces, parallel interfaces, and 8-bit microprocessors. We chose to implement parallel data transfer between microprocessors as an effective way of achieving such data collection. Our result concludes that the data collection can be done in 250 ${\mu}sec$ time-interval.

• Progress in Superconductivity
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• v.10 no.2
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• pp.139-143
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• 2009

We have fabricated a low-noise 61-channel axial-type first-order gradiometer system for measuring fetal magnetocardiography(MCG) signals. Superconducting quantum interference device(SQUID) sensor was based on double relaxation oscillation SQUID(DROS) for detecting biomagnetic signal, such as MCG, magnetoencphalogram(MEG) and fetal-MCG. The SQUID sensor detected axial component of fetal MCG signal. The pickup coil of SQUID sensor was wound with 120 ${\mu}m$ NbTi wire on bobbin(20 mm diameter) and was a first-order gradiometer to reject the environment noise. The sensors have low white noise of 3 $fT/Hz^{1/2}$ at 100 Hz on average. The fetal MCG was measured from $24{\sim}36$ weeks fetus in a magnetically shielded room(MSR) with shielding factor of 35 dB at 0.1 Hz and 80 dB at 100 Hz(comparatively mild shielding). The MCG signal contained maternal and fetal MCG. Fetal MCG could be distinguished relatively easily from maternal MCG by using independent component analysis(ICA) filter. In addition, we could observe T peak as well as QRS wave, respectively. It will be useful in detecting fetal cardiac diseases.

• Progress in Superconductivity and Cryogenics
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• v.17 no.4
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• pp.34-37
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• 2015

Developing Magnetoencephalography (MEG) based on Superconducting Quantum Interference Device (SQUID) facilitates to observe the human brain functions in non-invasively and high temporal and high spatial resolution. By using this MEG, we studied alpha rhythm (8-13 Hz) that is one of the most predominant spontaneous rhythm in human brain. The 8-13 Hz rhythm is observed in several sensory region in the brain. In visual related region of occipital, we call to alpha rhythm, and auditory related region of temporal call to tau rhythm, sensorimotor related region of parietal call to mu rhythm. These rhythms are decreased in task related region and increased in task irrelevant regions. This means that these rhythms play a pivotal role of inhibition in task irrelevant region. It may be helpful to attention to the task. In several literature about the alpha-band inhibition in multi-sensory modality experiment, they observed this effect in the occipital and somatosensory region. In this study, we hypothesized that we can also observe the alpha-band inhibition in the auditory cortex, mediated by the tau rhythm. Before that, we first investigated the existence of the alpha and tau rhythm in occipital and temporal region, respectively. To see these rhythms, we applied the visual and auditory stimulation, in turns, suppressed in task relevant regions, respectively.

• Progress in Superconductivity
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• v.5 no.2
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• pp.98-104
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• 2004

We analyzed a noise-sensitivity profile of a specific SQUID sensor system for the localization of brain activity. The location of a neuromagnetic current source is estimated from the recording of spatially distributed SQUID sensors. According to the specific arrangement of the sensors, each site in the source space has different sensitivity, that is, the difference in the lead field vectors. Conversely, channel noises on each sensor will give a different amount of the estimation error to each of the source sites. e.g., a distant source site from the sensor system has a small lead-field vector in magnitude and low sensitivity. However, when we solve the inverse problem from the recorded sensor data, we use the inverse of the lead-field vector that is rather large, which results in an overestimated noise power on the site. Especially, the spatial sensitivity profile of a gradiometer system measuring tangential fields is much more complex than a radial magnetometer system. This is one of the causes to make the solutions of inverse problems unstable on intervening of the sensor noise. In this study, in order to improve the localization accuracy, we calculated the noise-sensitivity profile of our 40-channel planar SQUID gradiometer system, and applied it as a normalization weight factor to the source localization using synthetic aperture magnetometry.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2786-2788
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• 2003

본 논문에서는 생체자기신호의 잡음제거 기법 중 PCA(Principal Component Analysis) 알고리즘을 사용하여 효과적으로 노이즈를 제거하기 위한 방법을 제안하였다. 61 채널 SQUID 시스템을 이용하여 심자도 신호를 측정하였고, 40 채널 SQUID 시스템을 이용하여 뇌자도 신호를 측정하였다. 그리고, 측정한 신호 성분들을 제안한 방법을 이용하여 주성분들을 분리하였고, 이들 중에서 노이즈 성분을 추정하여 측정한 신호에서 제거하였다. 이러한 방법을 이용한 결과, 심자도 신호에 존재하는 펄스 노이즈로 인하여 왜곡된 생체 자기 신호의 노이즈를 감소 시킬 수 있었으며, 뇌자도 신호에 존재하는 외부 노이즈 성분을 제거하여 임상 진단에 유용한 데이터를 얻을 수 있었다.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.213-220
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• 2014

Korean magnetoencephalography (MEG) system had been developed and installed to hospital. The Korean MEG system contains helmet-shaped arrays of 152 first-order double relaxation oscillation SQUID (DROS) sensor. As a clinical application we have measured and analyzed evoked responses in patients with functional brain disease by outer stimulation as follows; 1) auditory evoked field in patients with hemifacial spasm, 2) somatosensory evoked fields in patients with tumor. We confirm that neuromagnetic data by Korean MEG system can provide useful information for pre-surgical planning or functional brain research.