• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.889-890
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• 2006

This paper pertains to introducing the design of adaptive filters for the cancellation of muscle noise among several types of noise sources from the ECG signal. We used EMG signals measured along with ECG at the same time to use it as the reference input to the adaptive filter for the experiments. PSD results showed that the statistical characteristics of ECG are closely correlated with those of EMG.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.151-158
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• 1994

It has been shown that many of physiological systems have nonlinear dynamics. The evidences of these nonlinear behaviors make us analyze physiological systems in the new viewpoint. And, some of these nonlinear dynamics can be represented by chaotic behaviors, which is studied by several methods-correlation dimension, return map, power spectrum analysis, etc. This study is on the analysis of nonlinear characteristics of ECG. After data have been acquired from 20 children (10-13 years old), and 30 students (20-24 years old). We have calculated parameters HR, PR, VAT, TD, TRD, TPD from data, and estimated correlation dimension, return map, power spectrum, time series. Results show the nonlinear and chaotic characteristics of ECG.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.1
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• pp.192-200
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• 2015

Several algorithms have been developed to classify arrhythmia which rely on specific ECG(Electrocardiogram) database. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to classify the pattern by analyzing personalized ECG signal and extracting minimal feature. Thus, QRS pattern Analysis of personalized ECG Signal by Q, R, S peak variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and extract eight feature by amplitude and phase variability. Also, we classified nine pattern in realtime through peak and morphology variability. PVC, PAC, Normal, LBBB, RBBB, Paced beat arrhythmia is evaluated by using 43 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 93.72% in QRS pattern detection classification.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.186-189
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• 2001

본 연구에서는 2종류의 색온도(4000 K, 2700 K)조건 하에서 작업자의 피로도를 평가하기 위하여 피험자에게 검색작업을 부가하고 주관평가 및 생리신호를 측정하였다. 주관평가는 ME(Magnitude Estimation)법의 설문지를 사용했으며, 생리신호는 ECG, 맥파, 피부전도도, 피부온도, 호흡, 뇌파를 측정하여 그중 ECG신호를 분석하였다. ECG신호 파라미터로서 IBI, BPM, 평균 BPM, LF/HF, CSI, CVI, CV-RR를 분석한 결과, 특히 CSI, CVI, CV-RR가 피로도와 상관관계가 높았다.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1268-1270
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• 1987

This paper suggests several simple and efficient algorithms for detecting the ECG Signal by Microcomputer's software. The ECG signal detection was performed with the Linear Approximation and the feature extraction. The linear transformation approximates a given waveform by a piecewise-linear function with a preset upper bound on the absolute error between the functional values of the original function and the approximation. And the feature extraction from ECG signal, the features are different wave amplitudes, durations and interwave intervals, used the slope, the amplitude and time-Duration of ECG Sinal.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.247-249
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• 2006

This paper describes a new method to eliminate the baseline wander for ECG based on waveform morphology analysis. This method uses the descending slope tracing waves[3] to separate the baseline wander from ECG and approximates the separated baseline wander to a corresponding approximated S-waves contour, and finally, subtracts the approximated S-waves contour from the original ECG. To verify its efficacy and validity in practical applications, this method has been applied to MIT/BIH database and compares this method with the other method employing the ascending slope tracing waves to remove a baseline from ECG[4].

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.11
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• pp.471-475
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• 2006

In this paper, we propose a method to eliminate the baseline wander for ECG based on waveform morphology analysis. This method uses the ascending slope tracing waves to approximate the baseline wander in ECG and subtracts these waves from the original ECG to eliminate the baseline wander. This ascending slope tracing waves was developed for efficient enhancement of slope inverting points and sudden slope changing points. This method has been applied to MIT/BIH database to verify its efficacy and validity in practical applications.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.225-228
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• 1996

ECG data are used for the diagnostic purposes with many clinical situations, especially heart disease. In this paper, an efficient ECG data compression technique by wavelet transform and high-speed vector quantization on PMS-B algorithm is proposed. In general, ECG data compression techniques are divided into two categories: direct and transform methods. The direct data compression techniques are AZTEC, TP, CORTES, FAN and SAPA algorithms, besides the transform methods include K-L, Fourier, Walsh, and wavelet transforms. In this paper, we applied wavelet analysis to the ECG data. In particular, vector quantization on PMS-B algorithm to the wavelet coefficients in the higher frequency regions, but scalar quantized in the lower frequency regions by PCM. Finally, the quantized indices were compressed by LZW lossless entropy encoder. As the result of simulation, it turns out to get sufficient compression ratio while keeping clinically acceptable PRD.

• The Journal of the Korea Contents Association
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• v.16 no.2
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• pp.666-672
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• 2016

We extracted 50 LVH patients out of 30'~80's who performing ECG and echocardiography examination. We used Devereux's theory to examinate LVH with echocardiography and used Sokolow-Lyon's theory to examinate LVH with ECG. We used regression and correlation analysis by SPSS, used ROC curve analysis to decide predominance of two ways of .Age, BMI, SBP and DBP whice are the danger factors of LVH and standard value of LVH diagnosis examination seems correlated. Out of 50 LVH patients, 50 patients were diagnosed LVH by echcardiography examination and only 21 patients were diagnosed LVH by ECG examination. Also echocardiography was AUC 99%, sensitivity 96%, singularity 95%, accuracy 95.5%. And ECG was AUC 76%, sensitivity 62%, singularity 76%, accuracy 68%.By comparing accuracy between echocardiography and ECG in diagnosing LVH, we could tell echocardiography was examination with higher accuracy. Therefore, if one was diagnosed with summit on 1st examination with ECG, considering age, body mass index, systolic blood pressure and dilator blood pressure, should offer echocardiography examination.

• The KIPS Transactions:PartD
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• v.19D no.1
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• pp.105-112
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• 2012

Most methods for detecting PVC and APC require the measurement of accurate QRS complex, P wave and T wave. In this study, we propose new algorithm for detecting PVC and APC without using complex parameter and algorithms. Proposed algorithm have wide applicability to abnormal waveform by personal distinction and difference as well as all sorts of normal waveform on ECG. To achieve this, we separate ECG signal into each unit patterns and made a standard unit pattern by just using unit patterns which have normal R-R internal. After that, we detect PVC and APC by using similarity analysis for pattern matching between standard unit pattern and each unit patterns.