• 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.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1326-1328
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• 1987

This paper describes the design of digital signal processing system for the automatic diagnosis of ECG. The system comprises analog hardware, digital hardware, and control system by microcomputer. Also, since digital signal processing system can be equipped easily in microcomputer for the compact size(Single board), We expect to develop the Portable ECG Automatic Diagnosis System using this System.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.3
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• pp.553-558
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• 1999

The ECG signal is very important information for diagnosis of patient and a cardiac disorder That signal is hard to filter the noise because that is mixed with a lot of noise, and the error of the filtering will distort the ECG signal. The existing method for the filtering of the ECG signal has structure that has many steps for filtering, so that structure is complex and the processing speed is slow. For the improvement of that problem, we propose the method of filtering that has simple structure using the RBF neural networks and have good results.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.3
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• pp.104-109
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• 2018

A non-intrusive ECG and BCG measurement system is introduced. The system is built on a auxiliary backrest of a chair. The developed system is aimed to non-intrusive assessment of cardiovascular dynamic indices such as pulse arrival time(PAT) and pre-ejection period (PEP). In the system, capacitive active electrodes and capacitive grounding were used for the non-intrusive indirect-contact ECG measurement, and EMFi pressure sensor was used for the non-intrusive BCG measurement. The capacitive active electrodes and the EMFi sensor were attached on the backrest. Using the system, ECG and BCG were successfully acquired. The measured BCG showed peaks that following ECG R peaks. It was shown that the time interval between Q wave in ECG and first peak in BCG correlates Pre-ejection period measured by impedance-cardiogram. The results showed that the introduced system can be used for the non-intrusive various cardiovascular information including ECG, PAT, PEP.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.302-308
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• 2001

SVD(Singular Value Decomposition) filter for the suppression of EMG in multi-lead stress ECG is studied. SVD filter consists of two parts. In the first part, the basis vectors were chosen from the averaged singular vectors obtained from the decomposed noise-free ECG. The singular vector is computed from the stress ECG and is compared itself with basis vectors to know whether the noise exist in stress ECG. In the second part, the existing elimination method is used, when one(or two) channels is(or are) contaminated by noise. But the proposed enhanced SVD filter is used in case of having the noise in the many channels. During signal decomposition and reconstruction, the noise-free channel or the least noisy channel have the weight of 1, the next less noisy channel has the weight of 0.8. In this way, every channel was weighted by decreased of 0.2 in proportion to the amount of the added noise. For the evaluation of the proposed enhanced SVD filter, we compared the SNR computed by the enhanced SVD filter with the standard average filter for the noise-free signal added with artificial noise and the patient data. The proposed SVD filter showed better in the SNR than the standard average filter. In conclusion, we could find that the enhanced SVD filter is more proper in processing multi-lead stress ECG.

• 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 KIEE Conference
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• 1991.07a
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• pp.905-907
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• 1991

One of the general methods to diagnose abnormalities of heart is stethoscopy. This method needs special skill and experiment of doctors and it lacks for objectivity. Electrocardiography(ECG) is another biomedical method which is commonly used to diagnoss abnormalities of heart. The development of PCG is required in recent years to improve objectivity of stethoscopy method. In this paper, PCG is implemented on personal computer and ECG is also included to help the analysis of PCG waveform. Time analysis is used so far, but in this paper the frequency analysis is also considered to improve the accuracy of disgonosis. As future research, recognition of PCG and ECG signal and the Expert System is required to improve the accuracy of diagnosis.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.356-357
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• 2007

In this paper, we developed an integrated miniaturized device which acquires and transmits the signal of ECG an interested heartbeat and body's temperature and humidity. Using an amplifier circuit on the electrodes and the radio frequency transmission, the developed system dispenses with the use of cables among the electrodes, amplifier, and the post processing system. The sensor signals are transmitted to the RF-wireless terminal that was developed using the micro controller Aduc812, LCD, RF-module (frequency 424MHz, 9600-bps). In results, the developed system improves not only the signal-to-noise ration in dynamic ECG & and body's temperature and humidity measurement, but also the user convenience.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.33-40
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• 2016

Previous works for detecting arrhythmia have mostly used nonlinear method to increase classification accuracy. Most methods require accurate detection of ECG signal, higher computational cost and larger processing time. But it is difficult to analyze the ECG signal because of various noise types. Also in the healthcare system based IOT that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose R wave detection considering complexity and arrhythmia classification based on binary coding. For this purpose, we detected R wave through SOM and then RR interval from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. R wave detection and PVC, PAC, Normal classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41%, 97.18%, 94.14%, 99.83% in R wave, PVC, PAC, Normal.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.96-101
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• 2011

In recent days, the demand for the remote ECG monitoring system has been increasing and the automation of the monitoring system is becoming quite of a concern. Automatic detection of the abnormal ECG beats must be a necessity for the successful commercialization of these real time remote ECG monitoring system. From these viewpoints, in this paper, we proposed an automatic detection algorithm for the abnormal ECG beats using QRS width and RR interval patterns. In the previous research, many efforts have been done to classify the ECG beats into detailed categories. But, these approaches have disadvantages such that they produce lots of misclassification errors and variabilities in the classification performance. Also, they require large amount of training data for the accurate classification and heavy computation during the classification process. But, we think that the detection of abnormality from the ECG beats is more important that the detailed classification for the automatic ECG monitoring system. In this paper, we tried to detect the VEB which is most frequently occurring among the abnormal ECG beats and we could achieve satisfactory detection performance when applied the proposed algorithm to the MIT/BIH database.