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

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.6
• /
• pp.67-75
• /
• 1993

ECG pattern was classified using a back-propagation neural network. An improved feature extractor of ECG is proposed for better classification capability. It is consisted of preprocessing ECG signal by an FIR filter faster than conventional one by a factor of 5. QRS complex recognition by moving-window integration, and peak extraction by quadratic approximation. Since the FIR filter had a periodic frequency spectrum, only one-fifth of usual processing time was required. Also, segmentation of ECG signal followed by quadratic approximation of each segment enabled accurate detection of both P and T waves. When improtant features were extracted and fed into back-propagation neural network for pattern classification, the required number of nodes in hidden and input layers was reduced compared to using raw data as an input, also reducing the necessary time for study. Accurate pattern classification was possible by an appropriate feature selection.

• Journal of Biomedical Engineering Research
• /
• v.12 no.3
• /
• pp.191-202
• /
• 1991

This paper describes ECG data compression algorithm using neural network. As a learning method, we use back error propagation algorithm. ECG data compression is performed using learning ability of neural network. CSE database, which is sampled 12bit digitized at 500samp1e/sec, is selected as a input signal. In order to reduce unit number of input layer, we modify sampling ratio 250samples/sec in QRS complex, 125samples/sec in P & T wave respectively. hs a input pattern of neural network, from 35 points backward to 45 points forward sample Points of R peak are used.

• Proceedings of the KOSOMBE Conference
• /
• v.1996 no.05
• /
• pp.31-35
• /
• 1996

This paper presents a real time algorithm for monitoring of the arrythmia of ECG signal. A real time monitoring, following by detecting a QRS complex, is the most important. Using 2-dimensional time-delay coordinates which are reconstructed by the phase portrait plotting special trajectory, we detect QRS complexes. In this study, arrythmias are detected by matching the past standard template with tile present pattern when changing abruptly In order to matching with each other, we propose modified chain coding algorithm which applies vetor table consisting of eight orthonormal code(=binary code) to the phase portraits. This algorithm using logical function increases the weight if exceeding to the threshold determinded by correlation value and the distance from a straight line(y=x). Evaluating the performance of the proposed algorithm, we use standard MIT/BIH database. The results are fellowing, 1) Improve the speed of matching template than that of cross-correlation ever has been used. 2) Because the proposed algorithm is robust to varing fiducial point, it is possible to monitor the ECG signal with irregular RR interval. 3) In spite of baseline wandering owing to the low frequency noise, monitoring performance is not reduced.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.20 no.1
• /
• pp.54-65
• /
• 1996

The purposes of this study were 1) to present the optimum slacks pattern for young men, 2) to develope a methodology to draft basic slacks pattern using AutoCAD The total crotch legth and the shape of the crutch line were determined by anthropometric data analysis. The total crotch length was calculated with the waist girth, the hip girth and the crotch length measurements. The anthropometric data utilized for this procedure was National Anthropometric Survey of Korea, 1992. And multidimensional anthropometric measurements were carried out for 6 male college students between the age of 18 to 24. The subjects were measured with the Martin's anthropometer and the sliding gauge. Mean, standard deviation and t-test were performed for statistical analysis of the data. The automatic drafting method was programmed by AutoLISP in AutoCAD. The automatic drafting was based on the Muller's slacks pattern drafting method, the measurements of slacks construction components and the curve of crotch line. The crotch line was drafted using of the arc function in AutoCAD. The total crotch length was calcuated using the multiple regression equation. The experimental pattern developed to accomodate individual body wleasurements expected to produce customized apparel production in QRS(Quick Response System) production system.

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

• Korean Journal of Clinical Laboratory Science
• /
• v.44 no.3
• /
• pp.136-141
• /
• 2012

The hearts of highly trained athletes show morphologic and electrocardiographic (ECG) changes that suggest the presence of cardiovascular disease, including sinus bradycardia, a striking increase in precordial R-wave or S-wave voltages, ST segment depression, and T-wave inversions. Despite a number of previous observational surveys, the determinants of abnormal ECG patterns in trained athletes remain largely unresolved. In this study, we compared the electrocardiographic characteristics of athletes to determine any sensitive indicators. Comparison between ECG patterns and cardiac physiology was performed in 21 junior athletes and 25 untrained subjects with no signs of cardiac disease. Sinus bradycardia was detected in a subset of athletes but not statistically significant between the athletes ($69.9{\pm}11.1bpm$) and the control ($72.7{\pm}9.9bpm$) group. The mean values of the PR and QTc intervals in the athletes' group were $149.2{\pm}15.4ms$ and $402.3{\pm}28.8ms$, respectively. Also, there were no significantly differences between control group and the athletes' group. In addition, the athletes demonstrated a spectrum of alterations in the 12-lead ECG pattern, including marked increase in precordial R-wave or S-wave voltages ($$SV_1+RV_5{\geq_-}35mm$$, 23.8%), QRS duration ($${\geq_-}90ms$$, 90.5%), suggestive of left ventricular hypertrophy. However, left axis deviation, ST segment depression, and T-wave changes in V5, V6 were not observed in either the athletes or control group. Our findings suggest that sinus bradycardia, precordial R-wave or S-wave voltages, and QRS duration seem to be more sensitively detected in athletes than in control group. Further researches on the electrocardiographic patterns of athletes should be carried out to improve the sensitivity and specificity of diagnostic criteria.

• Journal of Veterinary Clinics
• /
• v.19 no.2
• /
• pp.132-138
• /
• 2002

Non-human primates are widely used for experimental animal and raised as companion animal in Korea. To establish the electrocadiogram (ECG) of non-human primates that are domestically raised, the author measured bipolar limb leads and augmented unipolar limb leads, after tiletamine/zolazepam (TZ) injection as sedative agents. The amplitudes of P,Q, R,S and T wave and duration time of P wave, QRS complex, PR and QT interval in each lead of ECG were evaluated in 7 non-human primates at 15 minutes after TZ injection, respectively. The amplitude of P wave in I, II,III, aVR, aVL and aVF leads revealed 0.06$\pm$ 0.05,0.14$\pm$ 0.05, 0.1 $\pm$ 0.05,-0.11 $\pm$ 0.06,-0.04$\pm$ 0.04 and 0.12$\pm$ 0.05 mV respectively. The amplitude of Q wave revealed -0.16$\pm$ 0.15, -0.23$\pm$ 0.18, -0.17$\pm$ 0.13, 0.16$\pm$0.13, 0.04$\pm$ 0.09 and -0.2$\pm$0.13 mV, respectively. The amplitude of R wave revealed 0.56$\pm$0.56, 1.24$\pm$ 0.67, 0.92$\pm$0.33, -0.37$\pm$ 1.14, -0.22$\pm$ 0.47 and 1.12 $\pm$ 0.47 mV, respectively. The amplitude of S wave revealed -0.02$\pm$ 0.08, -0.04$\pm$0.06, -0.06$\pm$0.04, 0.02$\pm$0.04, 0.04$\pm$0.09 and -0.04 $\pm$ 0.06 mV, respectively. The amplitude of T wave revealed -0.01 $\pm$ 0.15,-0.02$\pm$ 0.13, 0.01 $\pm$ 0.08, 0.02$\pm$ 0.12, 0.01 $\pm$ 0.11 and -0.03$\pm$ 0.09 mV, respectively. The duration time of P wave revealed 0.05 $\pm$ 0.01, 0.04$\pm$ 0.01, 0.05$\pm$ 0.02, 0.05 $\pm$ 0.02, 0.04$\pm$ 0.01 and 0.04$\pm$ 0.01 sec, respectively. The duration time of QRS complex revealed 0.05 $\pm$ 0.02,0.05$\pm$ 0.01, 0.05 $\pm$ 0.01, 0.04$\pm$ 0.01, 0.05$\pm$ 0.01 and 0.05 $\pm$ 0.01 sec, respectively. The duration time of PR interval revealed 0.08$\pm$ 0.01, 0.07$\pm$0.01,0.08$\pm$ 0.03, 0.08$\pm$0.01, 0.08$\pm$ 0.01 and 0.08$\pm$0.01 sec, respectively. The duration time of QT interval revealed 0.23$\pm$ 0.06, 0.22$\pm$ 0.05, 0.23 $\pm$ 0.06, 0.23$\pm$ 0.06, 0.24$\pm$ 0.05 and 0.22$\pm$ 0.02 sec, respectively. No significant changes were observed in e amplitude of P and T waves. The amplitude of QRS complex in ketamine group was higher than that of TZ group. However, no significant changes were observed in both intra-group and inter-group. There were no significant changes in the duration time of P wave, QRS complex and PR interval obtained from both groups. Also, the duration time of QT interval in TZ group was significantly longer at 30 min.(P< 0.05) an that of 10 minutes after injection. However, significant difference was not found between two groups. The mean cardiac electric axis in ketamine group tended to decrease until 30 min. after injection and then gradually increase. However, mean cardiac electric axis of TZ group was increased until 30 min. after injection and then decreased. But significant differences were not observed between groups. These results suggest that the ECG pattern after TZ injection to non-human primates reared in korea was established. It was also considered that the injection of ketamine and TZ didn't significantly affect on ECG pattern of the non-human primates.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.176-180
• /
• 2004

The ST-segment that the beginning part of T wave is the important diagnostic parameter to finding myocardial ischemia. Abnormal ST appears in two types. One is the level change, and the other is the pattern change. In this paper, we describe the monitoring of abnormal ST using PC based system. Hardware of this system consists of transmitter, receiver and PC. The function of transmitter is measuring ECG in three channels which are selected manually and transmitting the data to receiver by digital radio way. Connection with receiver and PC is by RS232C, and the data received on the PC is analyzed automatically by ECG analysis algorithm and saved to file. In the algorithm part for detecting abnormal ST, ST-segments are approximated by a polynomial. This method can detect all of the deviation and pattern change of ST-segment regardless the change in the heart rate or sampling rate. To gain algorithm reliability, the method rejects distorted polynomial approximation by calculation the difference between the approximated ST-segment and original ST-segment. In pre-signal processing, the wavelet transformation separates high frequency bands including QRS complex from the original ECG. Consequently, the process improves the performance of detecting each feature points.

• Proceedings of the KOSOMBE Conference
• /
• v.1996 no.05
• /
• pp.293-297
• /
• 1996

For the representative beat calculation and efficient rhythm analysis new method, that is, QRS typification were proposed. A problem that were resulted from pattern classification based on binary logic could be solved out by the fuzzy clustering and classification nodes could be reduced by using the proposed new feature vector. The accurate representative beat could be obtained by excluding the ST-T segment that happened outlier through ST-T segment typification procedure.