• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1287-1294
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• 2001

As size of waveform is very small, ECG(electrocardiogram) signal is difficult to analyze for noise which is occurred when it measures. In order to obtain ECG clearly, it must eliminate that power line interference, baseline wandering, noise of muscle constriction. In ECG, the worst problem which is recorded signal of ECG is the baseline wandering elimination, which is occurred by rhythm of respiration and muscle constriction of part from attaching to an electrode. Such the baseline is roughly irregular wandering and shaking up and down therefore the part of the baseline wandering elimination is very important because it is difficulty of ECG diagnosis. In this study, as implementation of real-time signal processing digital filter it is applicable to analyze patient's heart disease by way of design of the baseline wandering elimination system.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.32-34
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• 2005

This paper describes a new baseline wandering elimination algorithm for ECG based on waveform morphology analysis. The algorithm uses two slope tracing waves to separate the baseline wandering from ECG and approximates the separated baseline wandering to a corresponding sinusoid, and finally, subtracts the approximated sinusoid from the original ECG. The two slope tracing waves, the descending slope tracing wave and the ascending slope tracing wave, were developed for efficient determination of slope inverting points and sudden slope changing points. The algorithm has been applied to MIT/BIH database to verify its efficacy and validity in practical applications.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.48-50
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• 2006

In this paper, we propose a method to minimize the baseline wandering that make hard to detect R wave in ECG. This method uses a different signal between ECG and ascending slope tracing waves to minimize the baseline wandering. When the slope of ECG signal maintains the value or falls, the ascending slope tracing wave fellows ECG signal directly, and this wave holds that value of ECG signal when the slope begins to rises in a certain time(=hold time). After this hold time, this wave traces ECG signal again. To evaluate this minimizing method for baseline wandering, the experiments are carried out with 5 ECG data in the database of MIT/BIH. R waves in the proposed different signal are detected by using descending slope trace waves and compared with the annotation file. The results show that the proposed method Is sure to minimize the baseline wandering in ECG.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.512-515
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• 2001

The heifer electrocardiograph is a widely progressing research which is used in judgement to existence for a heart disease and analyzes electric potential changes of heart movement during continuous living of everyday after attaching to body portable holler recorder for twenty-four hours. In order to obtain electrocardiogram clearly, it must eliminate that 60Hz power line interference, baseline wandering, noise of muscle constriction. In holter electrocardiogram, the most big problem which is recorded signal of ECG(electrocardiogram) is a baseline wandering elimination, which is occurred by rhythm of respiration and muscle constriction of part from attaching to an electrode. Such baseline is roughly irregular wandering and shaking up and down therefore the part of baseline wandering elimination is very important because it is difficult of ECG diagnosis. In this study, it is stabilized baseline wandering in analog part as implementation f real-time signal processing digital filter so it is applicable to analyze patient's heart disease by way of design of baseline wandering elimination system.

• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.517-524
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• 1995

This paper is a study on the design of the cascade adaptive filter (CAF) for baseline wandering elimination in order to enhance the performance of the detection of ST segments in ECG. The CAF using Least Mean Square (LMS) algorithm consists of two filters. The primary adaptive filter which has the cutoff frequency of 0.3Hz eliminates the baseline wandering in raw ECG The secondary adaptive filter removes the remnant baseline wandering which is not eliminated by the primary adaptive filter. The performance of the CAF was compared with the standard filter, the recursive filter, and the adaptive impulse correlated filter (AICF). As a result, the CAF showed a lower signal distortion than the standard filter and the AICF. Also, the CAF showed a better perf'ormance in noise elimination than the standard filter and the recursive filter. In conclusion, considering the characteristics of the noise elimination and the signal distortion, the CAF shows a better performance in the removal of the baseline wandering than the other three Otters and suggests the high performance in the detection of ST segment.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.1 no.1
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• pp.7-12
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• 2008

This paper studies a method to minimize the baseline wandering that make hard to extract R-wave in ECG. This method uses a difference signal between ECG and ascending slope tracing waves to minimize the baseline wandering. When the slope of ECG signal maintains the value or falls, the ascending slope tracing wave follows ECG signal directly, and this wave holds that value of ECG signal when the slope begins to rises in a certain time(=hold time). After this hold time, this wave traces ECG signal again. This method has been applied to MIT/BIH database to verify its efficacy and validity in practical applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2105-2112
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• 2010

The noise component of electrocardiogram is not distributed in a certain frequency band. It is expressed in various types of signals by rater's physical and environmental conditions. Particularly, since the baseline wander is occurred by the mixture of the original signal and 0 ~ 2 [Hz] range of the frequency components according to muscle constraction of part attaching to an electrode and respiration rythm, it makes the ECG signal analysis difficult. Several methods have been proposed to eliminate the wandering effectually. However, they have some problems. In some methods, the high processing time is required due to the computational complexity, while in other cases ECG signal morphology can be distorted. This paper suggests a simple and effective algorithm that eliminates baseline wander with low computational complexity and without distorting signal morphology. First, the algorithm detects and segments a baseline wandering interval using slope analysis and curve point detection, second, approximates the wandering in the interval as a sinusoid, and then subtracts the sinusoid from signal. Finally, ecg signals without baseline wander are obtained. In order to evaluate the performance of the algorithm, several ECG signals with baseline wandering in MIT/BIH ECG database 101, 111, 113, 234 record were chosen and applied to the algorithm. It is found that the algorithm removes baseline wanders effectively without significant morphological distortion.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.80-88
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• 1997

This paper describes a design of a Wavelet Adaptive Filter(WAF) for the removal of the baseline wandering and the minimization of the signal distortion using by wavelet transform and adaptive filter in the ECG signal. WAF consists of two parts. The first part is wavelet transform that decomposes the ECG signal into seven frequency bands using Vaidyanathan and Hoang wavelet. The second part is adaptive filter that uses the signal of seventh low frequency band among the wavelet transformed signals as primary input and a unit impulse sequence as reference input. For the evaluation of the performance of WAF, we used several baseline wandering elimination filters such as commerical standard filter with cutoff frequency of 0.5Hz and general adaptive filter. We made use of MIT/BIH database and real patient data for the evaluation. In conclusion, WAF showed a lower ST segement distortion than standard filter and adaptive filter and has a higher eliminated noise power than standard filter and adaptive filter.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.475-476
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• 2007

Electroglottography (EGG) is a technique used to register laryngeal behavior indirectly by a measuring the change in electrical impedance across the throat during speaking. However, EGG waveform is affected by laryngeal muscles which fluctuate the vocal cords, and which result in baseline wander. It is required to reduce baseline wander in EGG waveform, because EGG waveform is used for input signal of nonlinear speech synthesizer in next chapter. In vocal cords, the abduction-adduction of glottis is mainly controlled by the posterior cricoarytenoid (abductor) and interarytenoid (adductor) muscles respectively. Empirical Mode Decomposition method was adopted in cancellation of EGG waveform baseline wandering, and showd better performance than that of high pass filter with 500 order.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.141-144
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• 1993

This paper propose a two pole phase compensated titer to remove baseline wandering and preserve ST-segment accuracy in real time environment. Bilinear transformed null phase filter(ideal filter), Standard FIR filter and Cubic spline filter are evalauated in the same condition. The proposed phase compensated filter shows better performance than standard filter in real ECG test and triangular pulse test.