• Biotechnology and Bioprocess Engineering:BBE
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• v.9 no.2
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• pp.107-111
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• 2004

A comparative study was performed to evaluate the signal amplification strategies in electrochemical affinity sensing, which included the direct electron transfer and diffusible-group mediated electron transfer between label enzymes that were specifically bound to target proteins and chemically modified electrode surfaces. As a platform surface for affinity recognition reactions, a double functionalized poly(amidoamine) dendrimer monolayer that was modified with ferrocene and biotin groups was constructed on a gold surface. With the chemically modified electrode, a model affinity sensing with avidin was investigated. The advantages of adopting the diffusible-group mediated signaling strategy were demonstrated in terms of signal sensitivity and stability.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.201-208
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• 1995

The information obtained from the analysis of respiratory muscle elecromyographic (EMG) activities provides a mean for studying muscular activity in relation to the ventilatory process. Thus, in order to comprehend the airflow pattern and its brain control, signal processing is required to characterize respiratory muscle activity. This paper presents a computerized method for the analysis of the electrical activity of the respiratory muscles of premature lambs, and focuses upon the automatic determination of respiratory timing points such as onset and cessation points of the burst activity. Based on experimental results, reliable timing points can be obtained using the proposed methodology.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.134-137
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• 1994

In this paper, we describe an approach to ECG data coding based on a fractal theory of iterated contractive transformations defined piecewise. The main characteristic of this approach is that it relies on the assumption that signal redundancy can be efficiently captured and exploited through piecewise self-transformability on a block-wise basis. The variable range size technique is employed to reduce the reconstruction error. Large ranges are used for encoding the smooth waveform to yield high compression efficiency, and the smaller ranges are used for encoding rapidly varying parts of the signal to preserve the signal quality. The suggested algorithm was evaluated using MIT/BIH arrhythmia database. A high compression ratio is achieved with a relatively low reconstruction error.

• Journal of Biomedical Engineering Research
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• v.12 no.4
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• pp.285-294
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• 1991

Two types of the speech signal processores (SSP) for the cochlear a prosthesis are designed. One is designed using the cochlear model and the other is designed using the information (formant, pitch, intensity) extraction method. For these, some cochlear model and acoustic information extraction method are proposed. The result shows the SSP of the cochlear model type contain more acoustic cues than that of information extraction type. On the other hand, stimulus signal is clear and algorithm is simple in the SSP of the information ex traction type.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.101-104
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• 1995

In this paper, we designed a cascade adaptive filter for elimination of the baseline drift and the distortion of the filtered signal. The cascade adaptive filter(CAF) consists of two filters. The first adaptive filter which has the cutoff frequency of 0.3Hz eliminate the noisy signal. The second adaptive filter remove the remnant baseline drift which is not eliminated by the first adaptive filter. Comparing the performance of the CAF with standard filter, recursive notch filter(RNF) and a adaptive impulse correlated filter(AICF), the CAF showed a higher performance in removal of the baseline drift than standard filler, and RNF. Also, considering the distortion of filtered signal, CAF is better than AICF and is comparable to the standard filter.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.109-112
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• 1995

This paper is a study on the detection of the significant point in ECG signal. ECG signal consists of two components; one is high frequency component to be detected and the other is low frequency component to be removed. AR model is appropriate for modelling and removing the low frequency component. AR model coefficients are updated by artificial neural network algorithm. We can remove the background noise(low frequency) by passing through the AR filter. The remaining signals which include high frequency noise are sent to the matched filter to pass only the signal which we want to extract. The template used in matched filter is updated adaptively.

• Journal of Biomedical Engineering Research
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• v.13 no.2
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• pp.125-132
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• 1992

Background EEG signals can be represented as the sum of a conventional AR process and an innovation process. It Is know that conventional estimation techniques, such as least square estimates (LSE) or Gaussian maximum likelihood estimates (MLE-G ) are optimal when the innovation process satisfies the Gaussian or presumed distribution. When the data are contaminated by outliers, however, these assumptions are not met and the power spectrum estimated by conventional estimation techniques may be fatally biased. EEG signal may be affected by artifacts, which are outliers in the statistical term. So the robust filtering estimation technique is used against those artifacts and it performs well for the contaminated EEG signal.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.155-164
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• 1996

In the clinical environment, measurements of some characteristics of the skeletal muscle are currently used to assess the severity of a neuromuscular disease or in some cases to assist in making a diagnosis. But a quantitative method of evaluation has not yet been introduced satisfactorily. In this paper, the skeletal EMG(biceps muscle, masseter muscle) analysis has been processed both in the time and in the frequency domain by designing the digital signal processing system based on pentium PC and transputer (IMS 7805). The experiment have been performed in five normal subjects, and various parameters have been statistically tested and compare4 As a results, the effective parameters obtained for the evaluation of skeletal EMG electrical activity are turn analysis, MiTi, MiTa, IEMG, PDF in the time domain, and are mean frequency, median frequency, skewness, kurtosis, muscle fatigue slope in the frequency domain. The designed H/W and S/W in this study can be used effectively for the establishment of EMG data base and for clinical research.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.05
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• pp.25-27
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• 1990

By designing the gradient pulses to be velocity compensated during one pulse cycle in SSFP (steady state free precession) imaging, the flowing spins can be maintained in the steady state. In the new SSFP sequence the flow signal which might be lost in conventional SSFP imaging sequences can be restored owing to the signal contribution from the preceding pulse cycles. By using the proposed SSFP sequence substantial restoration of the flow signal has been observed for the CSF (cerebro spinal fluid) of the human head.

• Journal of Biomedical Engineering Research
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• v.12 no.4
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• pp.249-254
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• 1991

In the study on the quantitative diagnosis using ultrasound, the stability and precision of tissue characterized parameters are important for the clinical application. We estimate attenuation coefficient introducing homomorphlc process Into the modified spectral differnce method about silicon-madu phantom. We compare the results with those estimated uslng the method used for obtaining the attenuation map image before. Homomorphic process has the effect smoothing the reflected echo signal spectrum, therefore eliminat os the random pattern of the signal spectrum generated by the scatterers. As a result, it Is shown that the stability is enhanced