• Title/Summary/Keyword: QRS-complex

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Design of neural network based ALE for QRS enhancement (QRS 파의 증대를 위한 신경망 ALE 설계)

  • 원상철;박종철;최한고
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.217-220
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    • 2000
  • This paper describes the application of a neural network based adaptive line enhancer (ALE) for enhancement of the weak QRS complex corrupted with background noise. Modified fully-connected recurrent neural network is used as a nonlinear adaptive filter in the ALE. The connecting weights between network nodes as well as the parameters of the node activation function are updated at each iteration using the gradient descent algorithm. The real ECG signal buried with moderate and severe background noise is applied to the ALE. Simulation results show that the neural network based ALE performs well the enhancement of the QRS complex from noisy ECG signals.

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Real-Time QRS Detection Using Wavelet Packet Transform

  • Bholsithi, Wisarut;;Hinjit, Watcharapong;Dejhan, Kobchai
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1880-1884
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    • 2004
  • The wavelet packet transform has been applied for QRS detection with squaring, window integration, and impulse filter techniques to cut down the false detection of QRS complex. This real time QRS detection has been performed on Simulink and Matlab. The correct QRS detection rates have reached to 99.75% in the experiment with 15 sets of ECG data from European ST-T database which are kept in Physionet.

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An u-healthcare system using an wireless sensor node with ECG analysis function by QRS-complex detection (QRS검출에 의한 ECG분석 기능을 갖춘 무선센서노드를 활용한 u-헬스케어 시스템)

  • Lee, Dae-Seok;Bhardwaj, Sachin;Chung, Wan-Young
    • Journal of Sensor Science and Technology
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    • v.16 no.5
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    • pp.361-368
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    • 2007
  • Small size real-time ECG signal analysis function by QRS-complex detection was put into sensor nodes. Wireless sensor nodes attached on the patient’s body transmit ECG data continuously in normal u-healthcare system. So there are heavy communication traffics between sensor nodes and gateways. New developed platform for real-time analysis of ECG signals on sensor node can be used as an advanced diagnosis and alarming system for healthcare. Sensor node does not need to transmit ECG data all the time in wireless sensor network and to server PC via gateway. When sensor node detects suspicion or abnormality in ECG, then the ECG data in the network was transmitted to the server PC for further powerful analysis. This system can reduce data packet overload and save some power in wireless sensor network. It can also increase the server performance.

Efficient R Wave Detection based on Subtractive Operation Method (차감 동작 기법 기반의 효율적인 R파 검출)

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.4
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    • pp.945-952
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    • 2013
  • The R wave of QRS complex is the most prominent feature in ECG because of its specific shape; therefore it is taken as a reference in ECG feature extraction. But R wave detection suffers from the fact that frequency bands of the noise/other components such as P/T waves overlap with that of QRS complex. ECG signal processing must consider efficiency for hardware and software resources available in processing for miniaturization and low power. In other words, the design of algorithm that exactly detects QRS region using minimal computation by analyzing the person's physical condition and/or environment is needed. Therefore, efficient QRS detection based on SOM(Subtractive Operation Method) is presented in this paper. For this purpose, we detected R wave through the preprocessing method using morphological filter, empirical threshold, and subtractive signal. Also, we applied dynamic backward searching method for efficient detection. The performance of R wave detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41% in R wave detection.

Improvement of ECG P wave Detection Performance Using CIR(Contextusl Information Rule-base) Algorithm (Contextual information 을 이용한 P파 검출에 관한 연구)

  • 이지연;김익근
    • Journal of Biomedical Engineering Research
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    • v.17 no.2
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    • pp.235-240
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    • 1996
  • The automated ECG diagnostic systems that are odd in hospitals have low performance of P-wave detection when faced with some diseases such as conduction block. So, the purpose of this study was the improvement of detection performance in conduction block which is low in P-wave detection. The first procedure was removal of baseline drift by subtracting the median filtered signal of 0.4 second length from the original signal. Then the algorithm detected R peak and T end point and cancelled the QRS-T complex to get'p prototypes'. Next step was magnification of P prototypes with dispersion and detection of'p candidates'in the magnified signal, and then extraction of contextual information concerned with P-waves. For the last procedure, the CIR was applied to P candidates to confirm P-waves. The rule base consisted of three rules that discriminate and confirm P-waves. This algorithm was evaluated using 500 patient's raw data P-wave detection perFormance was in- creased 6.8% compared with the QRS-T complex cancellation method without application of the rule base.

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Effects of Sodium Bicarbonate on Electrocardiogram in Hyperkalemia (과칼륨혈증의 심전도변화와 중조(重曹)투여가 이에 미치는 영향)

  • Cho, Young-Ho;Chae, E-Up
    • The Korean Journal of Physiology
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    • v.16 no.1
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    • pp.41-50
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    • 1982
  • The effects of $NaHCO_3$ on the electrocardiogram of rats were studied in the induced hyperkalemia. The subjects were divided into 4 groups: the group 1 was normal control and the data on this normal control had teen obtained from the following three groups before administration of KCl or $NaHCO_3$, the group 2 (KCl) was administered 40 ml per kg body weight of the 10 per cent KCl solution, the group 3 $(NaHCO_3)$ was administered 40 ml per kg body weight of the 10 per cent $NaHCO_3$ solution, and the group 4 $(KCl+NaHCO_3)$ was received 10 per cent KCl, which was followed by administration of 10 per cent $NaHCO_3$ at one and half hours later. In KCl, the heart rate was decreased rapidly, and then maintained its level, later rapid decreasing heart rate was followed by the cardiac stand still. The mean electrical axis of QRS complex became progressively deviated to the left. The amplitude of T wave was increased transiently but was not changed thereafter. There was prolongation of the P-Q interval and the Q-T interval at the beginning and then they were shortened. In $NaHCO_3$, the heart rate was decreased rapidly at the beginning, later showed a tendency of recovery. The mean electrical axis of QRS was not changed initially, but later became deviated to the left. The amplitude of T wave was not changed. There was prolongation of the P-Q interval and the Q-T interval at the beginning and then they were shortened. In $KCl+NaHCO_3$, there were a tendency of recovery of both the amplitude of the T wave and the electrical axis of the QRS complex after administration of $NaHCO_3$ but the heart rate was not recovered. There was prolonged P-Q interval, but the Q-T interval was relatively unchanged.

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A Study on Real Time Automatic Diagnosis of Arrhythmias (실시간 부정맥 자동진단에 관한 연구)

  • Shin, Ho-Yong;Shin, Kun-Soo;Lee, Byung-Chae;Lee, Myoung-Ho
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1276-1279
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    • 1987
  • Cardiac arrhythmias are associated with electrical Instability and, hence, with abnormal mechanical activity of the heart in many cases, arrhythmias can be treated with drugs or electric shock to control and/or stop them. Hence fast arrhythmia detection is very important. In this paper RR interval, QRS width, and morphology are used for diagnosis and QRS complex is detected by hardware system. hence diagnosing time is shorten. Moreover doctors or nurses who have little knowledge of computer manipulation can get the Information of Patient's ECG by showing characteristics of abnormal waveform and by mapping graphs of RR interval .vs. QRS width and RR interval .vs. morphology on screen.

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