• Journal of Biomedical Engineering Research
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• v.16 no.4
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• pp.403-414
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• 1995

It is very difficult to quantize the ECG analysis because the decision criterion for ECG is different with each other depending on the medical specialists of the heart and there are measured detecting errors for each ECG measurement system. Therefore, we developed the real-time ECG identification system using digital fuzzy processor for STD-BUS, in order to reduce ambiguity generated in the process of ECG identification and to analyze the irregular ECG stastically to ECG's repetition interval. The variables such as AGE (months), width of QRS, average RRI, and RRI were used to classify the ECG, and were applied to ECG signal indentification system which is developed for the purpose of research. It was found that the automatic diagnosis of ECG signal was possible in the real time process which was impossible in general process of algorithm.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.467-468
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• 2007

In this paper, we have proposed a new method to extract the fetal ECG from a pregnant woman's abdominal signal using least square acceleration (LSA) filter and adaptive impulse correlation (AIC) filter. To evaluate the performance, the proposed method and other fetal ECG extraction techniques were processed using the real ECG data and then the results were compared. According to comparative results, the proposed method is powerful and successful for extracting the fetal ECG. It was able to separate perfectly even though the fetal beats overlap with the QRS wave of the maternal beats and to extract fetal ECG using any single-channel abdominal signal measured from pregnant woman's abdominal surface. Also, it could be implemented easily by fast computation time and simple structure. It is sure that our method could be useful for portable fetal monitoring system.

• Journal of Biomedical Engineering Research
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• v.43 no.6
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• pp.399-408
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• 2022

Because arrhythmia occurs irregularly, it should be examined for at least 24 hours for accurate diagnosis. For this reason, this paper developed firmware software for arrhythmia detection and prevented consumption of temporal and human resources and enabled continuous management and early diagnosis. Prior to the experiment, the interval between the R peaks of the QRS Complex was calculated using the Pan-Tompkins algorithm. The developed firmware software designed and implemented an algorithm to detect arrhythmia such as tachycardia, bradycardia, ventricular tachycardia, persistent tachycardia, and non-persistent tachycardia, and a data transmission format to monitor the collected data based on BLE. As a result of the experiment, arrhythmia was found in real time according to the change in BPM as designed in this paper. And the data quality for BLE communication was verified by comparing the sensor's serial communication value with the Android application reception value. In the future, wearable devices for real-time arrhythmia detection will be lightweight and developed firmware software will be applied.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.38-46
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• 2012

Atrial fibrillation is needed to be detected at paroxysmal stage and to be treated. But, paroxysmal atrial fibrillation ECG is hardly obtained with 12-lead electrocardiographs but Holter systems. Presently, the averaged beat subtraction(ABS) method is solely used to estimate atrial fibrillatory waves even with somewhat large residual error. As an alternative, in this study, we suggested an ESAF(event-synchronous adaptive filter) based algorithm, in which the AF ECG was treated as a primary input and event-synchronous impulse train(ESIT) as a reference. And, ESIT was generated so to be synchronized with the ventricular activity by detecting QRS complex. We tested proposed algorithm with simulated AF ECGs and real AF ECGs. As results, even with low computational cost, this ESAF based algorithm showed better performance than the ABS method and comparable performance to algorithm based on PCA(principal component analysis) or SVD(singular value decomposition). We also proposed an expanded version of ESAF for some AF ECGs with multi-morphologic ventricular activities and this also showed reasonable performance. Ultimately, with Holter systems including our proposed algorithm, atrial activity signal can be precisely estimated in real-time so that it will be possible to calculate atrial fibrillatory rate and to evaluate the effect of anti-arrhythmic drugs.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.251-260
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• 1998

The Holter monitoring system is a widely used noninvasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we design a high performance intelligent holter monitoring system which is characterized by the small-sized and the low-power consumption. The system hardware consists of one-chip microcontroller(68HC11E9), ECG preprocessing circuit, and flash memory card. ECG preprocessing circuit is made of ECG preamplifier with gain of 250, 500 and 1000, the bandpass filter with bandwidth of 0.05-100Hz, the auto-balancing circuit and the saturation-calibrating circuit to eliminate baseline wandering, ECG signal sampled at 240 samples/sec is converted to the digital signal. We use a linear recursive filter and preprocessing algorithm to detect the ECG parameters which are QRS complex, and Q-R-T points, ST-level, HR, QT interval. The long-term acquired ECG signals and diagnostic parameters are compressed by the MFan(Modified Fan) and the delta modulation method. To easily interface with the PC based analyzer program which is operated in DOS and Windows, the compressed data, that are compatible to FFS(flash file system) format, are stored at the flash memory card with SBF(symmetric block format).