• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.580-585
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• 1990

This paper presents a real time FECG signal monitoring system in which an adaptive multichannel noise canceller is implemented using a Texas Instruments TMS32020 digital signal processor. Abdominal ECG signal is applied as the desired output and 3 chest ECG signals as the reference input signals of the adaptive multichannel noise canceller whose coefficients are updated using the LMS algorithms.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.202-208
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• 2012

Fetal heart rate monitoring is important information to assess fetal well-being. Non-invasive fetal ECG (electrocardiography) can be derived from maternal abdominal signal. And various promising signal processing methods have been introduced to extract fetal ECG from mother's composite abdominal signal. However, non-invasive fetal ECG monitoring still has not been widely used in clinical practice due to insufficient reliable measurement and difficulty of signal processing. In application of signal processing method to extract fetal ECG, it might be lower signal to noise ratio due to time varying white Gaussian noise. In this paper, time varying Kalman smoother is proposed to remove white noise in fetal ECG and its feasibility is confirmed. Wiener process was set as Kalman system model and covariance matrix was modified according to white Gaussian noise level. Modified error covariance matrix changed Kalman gain and degree of smoothness. Optimal covariance matrix according to various amplitude in Gaussian white noise was extracted by 5 channel fetal ECG model, and feasibility of proposed method could be confirmed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.7
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• pp.590-598
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• 1991

This paper represents a syntactic peak detection algorithm which detects peak in the ECG signal.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.51-53
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• 2006

This paper proposes a portable ECG monitoring system, which integrates uptodate PDA and RF communication technology. The aim of the study is to acquire the subject's biomedical signal without any constraint. It has two types of transmission mode, which are total signal transmission mode and HR(heart rate)/SC(step count) transmission mode. In audition, wireless communication technology uses Zigbee Wireless PAN and can work in low-power mode, which is one of the advantages of ZiBbee communication technology. The developed system is composed of a transmitter and a receiver. The transmitter has three-axial acceleration sensor. ECG amplifier and Zigbee communication controller. In total signal transmission mode, it can send data 50 packets per second whose transmission speed corresponds to 300 ECG samples and 60 acceleration samples. In HR/SG transmission mode, it can calculate heart rate from EEG data with 216 samples per second and step count from acceleration data and send a packet every cardiac cycle. The receiver forwards the received data to PDA, where the data can be stored and displayed. Therefore, the developed device enables to continuous monitoring for Activities of Daily Living(ADL). Also, this method will reduce medical costs in the aged society.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.817-818
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• 2006

In Magnetic Resonance Imaging(MRI), the QRS complex of ECG is used as a trigger signal for MRI scan. But, gradient and RF(radio frequency) artifacts which are caused to static and dynamic field in MRI scanner cause interference in the ECG. Also, the signal shape of theses artifacts can be similar to the QRS-complex, causing possible misinterpretation during patient monitoring and false gating of the MRI. In case of using general FIR or IIR band-pass filters for minimizing the artifacts, artifact-reduction-ratio is not excellent. So, an adaptive real-time digital filter is proposed for reduction of noise by gradient and RF(radio frequency) artifacts. The proposed filter for MRI-Gating is based on the noise-canceller with NLMS(Normalized Least Mean Square) algorithm. The reference signals of the adaptive noise canceller are a combination of the noisy three channel ECG signals. In conclusions, the proposed method showed the acceptable quality of ECG signal with sufficient SNR for gating the MRI and possibility of real time implementation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.11
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• pp.495-501
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• 2006

Diagnostics of unborn baby is mainly aimed at prediction and detection of occurrence of intrauterine hypoxia. Consequences resulting from fetal hypoxia appear in its heart activity. In this study, we have developed a new non-invasive system for fetal hypoxia diagnosis which provides systolic time interval(STI) parameters on the basis of analysis of electrical and mechanical heart activity together. For this we have worked on 1) the proper lead system for the acquisition of abdominal ECG, 2) the independent component analysis based signal processing and fetal ECG separation, 3) the development of a hardware which consists of an abdominal ECG amplifying module and an ultrasound module and 4) the detection of characteristic points of FECG and Doppler signal and the extraction of diagnostic parameters. The developed system was evaluated by the clinical experiments in which 33 subjects were participated. The acquired STI by the system were distributed within the ranges from the well-established invasive results of other researchers. From this, we can conclude that the developed non-invasive fetal hypoxia diagnosis system is useful.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.118-121
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• 1996

This paper describes ECG signal labeling based on Fuzzy clustering, which is necessary at automated ECG diagnosis. The NPPA(Non parametric partitioning algorithm) compares the correlations of wave forms, which tends to recognize the same wave forms as different when the wave forms have a little morphological variation. We propose to apply Fuzzy clustering to ECG QRS Complex labeling, which prevents the errors to mistake by using If-then comparision. The process is divided into two parts. The first part is a parameters extraction process from ECG signal, which is composed of filtering, QRS detection by mapping to a phase space by time delay coordinates and generation of characteristic vectors. The second is fuzzy clustering by FCM(Fuzzy c-means), which is composed of a clustering, an assessment of cluster validity and labeling.

• 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.7 no.1
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• pp.21-34
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• 1986

In this paper, we described the ECG telemetry system via the Public Telephone Line. The system consist of a signal acquisition and measurement section, a signal processing section, and a signal transmission section. It used 8 bits microprocessor. The transmission section is composed of 3 ch. analog modulators and 1 ct. digital modem. Especially, using the digital modem, signal is transmitted with about 50n data reduction ratio by the TP (Turning Point) algorithm. The acoustic coupler or inductive coil for linking the public telephone line are used. The speed of the digital modem is 300 baud rate. The MCBS (Multi Channel Biotelemetry System) is tested and evaluated through the experiment.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1370-1378
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• 2018

There is a problem to measure neutral bio-signals during sleep because of inconvenience of attaching lots of sensors. In this study, we measured single electrocardiogram(ECG) signal and analyzed the correlation with sleep. After R-peak detection from ECG signal, we extracted 9 features from time and frequency domain of heart rate variability(HRV). Mean of HRV, RR intervals differing more than 50ms(NN50), and divided by the total number of all RR intervals(pNN50) have significant differences in each sleep stage. Specially, the mean HRV has an average of 87.8% accuracy in classifying sleep and awake status. In the future, the measurement ECG signal minimizes inconvenience of attaching sensors during sleep. Also, it can be substituted for the standard sleep measurement method.