• Progress in Superconductivity
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• v.4 no.1
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• pp.53-58
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• 2002

Noise from electronic instrumentation is invariably present in biomedical signals, although the art of instrumentation design is such that this noise source may be negligible. And sometimes signals of interest are contaminated or degraded by signals of similar type from another source. Biomedical signals are omni-presently contaminated by these background noises that span nearly all frequency bandwidths. In the magneto-cardiogram (MCG), several digital filters have been designed for the elimination of the power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. In addition to the introduced FIR filter, notch, adaptive filter using the least mean square (LMS) algorithm, and recurrent neural network (RNN) filter, a new filtering method for effective noise canceling in MCG signals is proposed in this paper, which is realized by the wavelet packets. The experimental results show that the proposed filter using wavelet packet performs efficiently with respect to noise rejection. To verify this, two characteristics were analyzed and compared with LMS adaptive filter, SNR of filtered signal and attractor pattern using the nonlinear dynamics.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2002.02a
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• pp.127-130
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• 2002

Step-edge dc SQUID magnetometers have been fabricated on sapphire substrate. Ce$O_{2}$ buffer layer and $YBa_{2}$$Cu_{3}$ $O_{7}$(YBCO) films were deposited in-situ on the low angle (~$35^{\circ}$)steps formed on the substrates. Typical 5-$\mu$m-wide junction has $R_{N}$ of 4 $\Omega$ and $I_{c}$ of 60 $\mu$A with $I_{c}$$R_{N}$ product of 240 $\mu$V at 77 K. According to applied bias current, depth of voltage modulation was changed and maximum voltage was measured 100~300 fT/$\checkmark$ Hz at 100 Hz, and about 1.5 pT/$\checkmark$ Hz at 1 Hz. For ac bias reversal method, field noise was decreased in the 1/f region. The QRS peak of magneto-cardiogram was measured 50 pT in the magnetically shielded room.

• Progress in Superconductivity
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• v.5 no.1
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• pp.26-30
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• 2003

Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.