• Transactions of the Korean Society of Mechanical Engineers B
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• v.39 no.5
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• pp.391-395
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• 2015

A 15-Lead ECG has been developed to diagnose posterior wall diseases of the heart that a 12-Lead ECG cannot diagnose. However, 15-Lead ECG data for developing heart-diseases-detecting algorithm are limited, and previous ECG simulators cannot predict the ECG waveform according to the changes in electrode. To solve these problems, the lumped parameter model (LPM), which divides the heart into 15 sections with varying electrical capacitance and electrical resistance. To imitate the electrical conduction in the heart, each node was connected to a current source and delivered the specific current considering the positions and time delay. The purpose of this study is to acquire the waveform that can be used in an ECG by delivering the specific current to LPM.

• Journal of Biomedical Engineering Research
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• v.41 no.1
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• pp.42-47
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• 2020

A personal authentication system based on biosignals has received increasing attention due to its relatively high security as compared to traditional authentication systems based on a key and password. Electrocardiography (ECG) measured from the chest or wrist is one of the widely used biosignals to develop a personal authentication system. In this study, we investigated the feasibility of using similar ECG measured behind the ears to develop a personal authentication system. To this end, similar ECGs were measured from thirty subjects using a pair of three electrodes attached behind each of the ears during resting state during which the standard Lead-I ECG was also simultaneously measured from both wrists as baseline ECG. The three ECG components, Q, R, and S, were extracted for each subject as classification features, and authentication accuracy was estimated using support vector machine (SVM) based on a 5×5-fold cross-validation. The mean authentication accuracies of Lead I-ECG and similar ECG were 90.41 ± 8.26% and 81.15 ± 7.54%, respectively. Considering a chance level of 3.33% (=1/30), the mean authentication performance of similar ECG could demonstrate the feasibility of using similar ECG measured behind the ears on the development of a personal authentication system.

• Journal of Sensor Science and Technology
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• v.15 no.5
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• pp.334-340
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• 2006

A compact biosignal monitoring device was developed. Electrodes for electrocardiogram (ECG) and a LED and silicon detector for photoplethysmogram (PPG) were used. A lead II type was arranged for ECG measurement and reflected light was measured at the finger tip for PPG. A single chip microprocessor (model ADuC812, Analog Device) controlled a measurement protocol and processed measured signals. PPG and ECG had a sampling rate of 300 Hz with 8-bit resolution. The maximum power consumption was 100 mW. The microprocessor computed pulse transit time (PTT) between the R-wave of ECG and the peak of PPG. To increase the resolution of PTT, analog peak detectors obtained the peaks of ECG and PPG whose interval was calculated using an internal clock cycle of 921.6 kHz. The device was designed to be operated by 3-volt battery. Biosignals can be measured for $2{\sim}3$ days continuously without the external interruptions and data is stored to an on-board memory. Our system was successfully tested with human subjects.

• Journal of Biomedical Engineering Research
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• v.41 no.2
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• pp.107-119
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• 2020

The deep neural networks (DNN) that can replicate the behavior of the human expert who recognizes the characteristics of ECG waveform have been developed and studied to analyze ECG. However, although the existing DNNs can not provide the explanations for their decisions, those trials have attempted to determine whether patients have certain diseases or not and those decisions could not be accepted because of the absence of relating theoretical basis. In addition, these DNNs required a lot of training data to obtain sufficient accuracy in spite of the difficulty in the acquisition of relating clinical data. In this study, a small-sized continuous data processing DNN (C-DNN) was suggested to determine the simple characteristics of ECG wave that were not required additional explanations about its decisions and the C-DNN can be easily trained with small training data. Although it can analyze small input data that was selected in narrow region on whole ECG, it can continuously scan all ECG data and find important points such as start and end points of P, QRS and T waves within a short time. The star and end points of ECG waves determined by the C-DNNs were compared with the results performed by human experts to estimate the accuracies of the C-DNNs. The C-DNN has 150 inputs, 51 outputs, two hidden layers and one output layer. To find the start and end points, two C-DNNs were trained through deep learning technology and applied to a parameter acquisition algorithms. 12 lead ECG data measured in four patients and obtained through PhysioNet was processed to make training data by human experts. The accuracy of the C-DNNs were evaluated with extra data that were not used at deep learning by comparing the results between C-DNNs and human experts. The averages of the time differences between the C-DNNs and experts were 0.1 msec and 13.5 msec respectively and those standard deviations were 17.6 msec and 15.7 msec. The final step combining the results of C-DNN through the waveforms of 12 leads was successfully determined all 33 waves without error that the time differences of human experts decision were over 20 msec. The reliable decision of the ECG wave's start and end points benefits the acquisition of accurate ECG parameters such as the wave lengths, amplitudes and intervals of P, QRS and T waves.

• Biomedical Science Letters
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• v.21 no.3
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• pp.135-143
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• 2015

Electrocardiogram measures the electric impulses generated by the heart during its cycle. Recently genome-wide association studies on electrocardiogram traits revealed many relevant genetic loci. Therefore, these findings need to be validated and investigated to determine the underlying mechanisms using mouse models. Invasive radiotelemetry has been widely used to record the electrocardiogram in mice because it has several advantages over non-invasive measurements. However, radiotelemetry is expensive and requires complicated surgery. On the other hand, a non-invasive method using 3 electrodes (one for earth) for lead II is easy to establish and allows for rapid measurement. In this study, eleven mice were measured with this non-invasive method and no statistical difference among them was found in any ECG measurements. In addition, repeat measurement in the same mouse was performed in 9 sets of experiment and the results indicated that non-invasive method was reliable for reproducibility. Further it was shown that measurements for 1, 5, 10, and 15 minutes were not different so that a short recording such as 5 minutes was enough to estimate the ECG values including heart rate. Further this method was validated by measuring the ECG of Balb/c and FVB that were previously shown to differ in ECG values by radiotelemetry. Significant differences were found in heart rate, PR interval and corrected QT interval between these mouse strains. This study partially proved that non-invasive method also could provide the accuracy and reproducibility. Based on these results, the non-invasive ECG recordings of lead II is recommended as a useful method for quick test in mouse model.

• The Korean Journal of Emergency Medical Services
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• v.25 no.1
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• pp.243-249
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• 2021

A decrease in coronary blood flow leads to an imbalance between the supply of oxygen to the myocardium and its demand, and reversible or irreversible damage to the myocardium could occur depending on the severity of the resultant ischemia and the duration of the imbalance. This imbalance results in a cascade of ischemic reactions in the following order: metabolic abnormalities, diastolic dysfunction, systolic dysfunction, and electrocardiogram changes. Variant angina is caused by the closure of the coronary artery due to reversible coronary artery spasm, resulting in myocardial ischemia and subsequent chest pain as a clinical symptom. Variant angina may be observed as ST segment elevation in electrocardiogram measured when present in chest pain. However, 12-lead electrocardiogram performed after the patient's chest pain resolves does not help in the diagnosis. Since the duration of chest pain appears to be <15 minutes, it is important to perform the 12-lead electrocardiogram when clinical symptoms are present. If nitroglycerin is administered without performing 12-lead electrocardiogram by 119 pre-hospital paramedics, the chest pain would be resolved, making it impossible to identify changes in the ST segment. Before administration of nitroglycerin, changes in the ST segment must be recorded by performing 12-lead electrocardiogram.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.10
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• pp.733-740
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• 2004

In this paper, an improved algorithm for the extraction of respiration signal from the electrocardiogram (ECG) is proposed. The whole system consists of two-lead electrocardiogram acquisition (lead Ⅰ and Ⅱ), baseline fluctuation elimination, R-wave detection, adjustment of sudden change in R-wave area using moving average, and optimal lead selection. In order to solve the problem of previous algorithms for the ECG-derived respiration (EDR) signal acquisition, we proposed a method for the optimal lead selection. An optimal EDR signal among the three EDR signals derived from each lead (and arctangent of their ratio) is selected by estimating the instantaneous frequency using the Hilbert transform, and then choosing the signal with minimum variation of the instantaneous frequency. The proposed algorithm was tested on 15 subjects, and we could obtain satisfactory respiration signals that shows high correlation (r>0.9) with the signal acquired from the chest-belt respiration sensor.

• Journal of Veterinary Clinics
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• v.15 no.2
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• pp.432-441
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• 1998

The electrocardiogram (ECG) and electrolytes were measured to obtain diagnostic data after experimental obstruction of duodenum in 8 dogs. Clinical signs of these appeared lower heart rate, temperatures respiration and blood pressure than signs of preoperation. In changes of electrolytes and acid-base balances, all dogs appeared hyponatremiai hypochloremia, metabolic alkalosis, and increased pHi HCO3, scot in blood, but potassium values appeared to increase in 3 cases fl-inc.) and to decrease in 5 cases (K- dec.) Two of three in K-inc. and three of five in K-dec. died at 60 hrs and 72 hrs after obstruction respectly. In changes of ECGI amplitudes of the K-inc cases appeared high in T wave and low in R wave, but amplitudes of the K-dec cases appeared low T waver 57 segment and high in R wave. Conduction times of the K-inc appeared the shorted PR intervals but the K-dec appeared the prolonged PR interval. The changes of these appeared apparently in lead II.

• Clinical and Experimental Pediatrics
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• v.53 no.5
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• pp.644-647
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• 2010

Purpose: To evaluate myocardial conductivity to understand cardiac involvement in patients with mitochondrial disease. Methods: We performed retrospective study on fifty-seven nonspecific mitochondrial encephalopathy patients with no clinical cardiac manifestations. The patients were diagnosed with mitochondrial respiratory chain complex defects through biochemical enzyme assays of muscle tissue. We performed standard 12-lead electrocardiography (ECG) on all patients. Results: ECG abnormalities were observed in 30 patients (52.6%). Prolongation of the QTc interval (>440 ms) was seen in 19 patients (33.3%), widening of the corrected QRS interval in 15 (26.3%), and bundle branch block in four (7.0%). Atrioventricular block, premature atrial contraction and premature ventricular contraction were seen in two patients each (3.5%) and Wolff-Parkinson-White syndrome in one patient (1.8%). Conclusion: Given this finding, we recommend active screening with ECG in patients with mitochondrial disease even in patients without obvious cardiac manifestation.

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