• Biomolecules & Therapeutics
• /
• v.1 no.1
• /
• pp.9-19
• /
• 1993

DA-125, a new anthracycline antibiotic, showed antitumor activity against animal tumors and human tumors. Therefore we studied the cardiotoxic potential of DA-125 in hamsters and rats as a part of safety research, and compared it with that of doxorubicin(DXR). In acute cardiotoxicity test model used hamsters DA-125 was administered intravenously at a dose of 6, 9, 12 mg/kg, and DXR at 3 mg/kg was given. The electrocardiogram(ECG) of hamsters was recorded for 30 minutes after administration. The DA-125 caused slight ECG alterations at a dose of 6 mg/kg. At a dose of 12 mg/kg DA-125 induced moderate to remarkable changes in ECG like decrease of heart rate, widening of PR interval and 07 interval, and A-V block in 3 out of 5 animals. The severity of ECG alteration at 12 mg/kg of DA-125 was similar to that at 3mg/kg of DXR and these changes caused by DA-125 and DXR recovered within 10 minutes after injection. In chronic cardiotoxicity test model used rats, DA-125 was administered intravenously once a week for three weeks at a dose of 6, 9mg/kg and DXR was given at a dose of 6mg/kg. Electrocardiogram was recorded every week from the start of administration to 2 weeks after the last administration and the animals were sacrificed for histological heart examination at 1 week or 2 weeks after the last administration. DA-125 did not cause any abnormal changes in ECG and in histological heart examination due to administration, but DXR caused widening of ST segment, QRS complex, and QT interval from 1 week after administration and these changes were continued to necropsy. These alterations in ECG were accompanied by cardiac histological lesions such as vacuolation in myocardiac cells, interstitial edema and necrosis of myocytes. These results suggest that DA-125 is less cardiotoxic than DXR.

• Fashion & Textile Research Journal
• /
• v.14 no.6
• /
• pp.1010-1017
• /
• 2012

This study examined the clothing wearing comfort of elderly women by electroencephalogram (EEG) and electrocardiogram (ECG) analyses. This study utilized 7 elderly individuals aged 65 or more. Two kinds of clothing ensemble (control and prototype) were used as experimental clothing. The control consisted of a general clothing ensemble and the prototype consisted of clothing that added an extra gap. Subjects wore the control or prototype from 9:00 to 21:30 and EEG and ECG signals were measured in the last 30 minutes. The EEG analysis showed that relative band power of a and ${\alpha}$/high ${\beta}$ were higher when they wore the prototype rather than the control. The ECG analysis showed that absolute band power of HF was higher; however, absolute band power of LF and LF/HF was lower when they wore the prototype rather than the control. Subjects felt less stressful and more comfortable when they wore the prototype. The results demonstrate the necessity to develop clothing in consideration of the body changes in elderly women. It is significant that the assessment of wearing comfort was aided by the use of EEG and ECG analysis in the field of clothing and textiles.

• Journal of Internet Computing and Services
• /
• v.20 no.6
• /
• pp.137-142
• /
• 2019

This paper Various services exist to detect and monitor abnormal event. However, most services focus on fires and gas leaks. so It is impossible to prevent and respond to emergency situations for the elderly and severely disabled people living alone. In this study, AI model is designed and compared to detect abnormal event of heart rate signal which is considered to be the most important among various bio signals. Specifically, electrocardiogram (ECG) data is collected using Physionet's MIT-BIH Arrhythmia Database, an open medical data. The collected data is transformed in different ways. We then compare the trained AI model with the modified and ECG data.

• International Journal of Contents
• /
• v.18 no.2
• /
• pp.68-80
• /
• 2022

The health of the human heart is commonly measured using ECG (Electrocardiography) signals. To identify any anomaly in the human heart, the time-sequence of ECG signals is examined manually by a cardiologist or cardiac electrophysiologist. Lightweight anomaly detection on ECG signals in an embedded system is expected to be popular in the near future, because of the increasing number of heart disease symptoms. Some previous research uses deep learning networks such as LSTM and BiLSTM to detect anomaly signals without any handcrafted feature. Unfortunately, lightweight LSTMs show low precision and heavy LSTMs require heavy computing powers and volumes of labeled dataset for symptom classification. This paper proposes an ECG anomaly detection system based on two level BiLSTM for acceptable precision with lightweight networks, which is lightweight and usable at home. Also, this paper presents a new threshold technique which considers statistics of the current ECG pattern. This paper's proposed model with BiLSTM detects ECG signal anomaly in 0.467 ~ 1.0 F₁ score, compared to 0.426 ~ 0.978 F₁ score of the similar model with LSTM except one highly noisy dataset.

• Journal of Internet Computing and Services
• /
• v.23 no.1
• /
• pp.31-38
• /
• 2022

An electrocardiogram(ECG) is a recoding of electrical signals of the heart's cyclic activity and an important body information for diagnosing myocardial rhythm. Large amount of information are generated continuously and a significant period of cumulative signal is required for the purpose of diagnosing a specific disease. Therefore, research on compression including clinically acceptable lossy technique has been developed to reduce the amount of information significantly. Recently, wearable smart heart monitoring devices that can transmit electrocardiogram(ECG) are being developed. The use of electrocardiogram, an important personal information for healthcare service, is rapidly increasing. However, devices generally have limited capability and power consumption for user convenience, and it is often difficult to apply the existing compression method directly. It is essential to develop techniques that can process and transmit a large volume of signals in limited resources. A method for compressing and transmitting the ECG signals efficiently by using the cumulative average (template) of the unit waveform is proposed in the paper. The ECG is coded lovelessly using template matching. It is analyzed that the proposed method is superior to the existing compression methods at high compression ratio, and its complexity is not relatively high. And it is also possible to apply compression methods to template matching values.

• Journal of Biomedical Engineering Research
• /
• v.43 no.6
• /
• pp.424-433
• /
• 2022

As the proportion of non-contact telemedicine increases and the number of electrocardiogram (ECG) data measured using portable ECG monitors increases, the demand for automatic algorithms that can precisely analyze vast amounts of ECG is increasing. Since the P, QRS, and T waves of the ECG have different shapes depending on the location of electrodes or individual characteristics and often have similar frequency components or amplitudes, it is difficult to distinguish P, QRS and T waves and measure each parameter. In order to measure the widths, intervals and areas of P, QRS, and T waves, a new algorithm that recognizes the start and end points of each wave and automatically measures the time differences and amplitudes between each point is required. In this study, the start and end points of the P, QRS, and T waves were measured using six Deep Neural Networks (DNN) that recognize the start and end points of each wave. Then, by synthesizing the results of all DNNs, 12 parameters for ECG characteristics for each heartbeat were obtained. In the ECG waveform of 10 subjects provided by Physionet, 12 parameters were measured for each of 660 heartbeats, and the 12 parameters measured for each heartbeat well represented the characteristics of the ECG, so it was possible to distinguish them from other subjects' parameters. When the ECG data of 10 subjects were combined into one file and analyzed with the suggested algorithm, 10 types of ECG waveform were observed, and two types of ECG waveform were simultaneously observed in 5 subjects, however, it was not observed that one person had more than two types.

• The Journal of the Korea Contents Association
• /
• v.9 no.12
• /
• pp.496-503
• /
• 2009

In the life environment changed with not only the material abundance but also the quality, it is the most crucial factor for the strategy of sensibility engineering to investigate vital signal according to the sensibility. In this perspective, it is necessary to design and merchandise the products in cope with each sensibility and needs as well as its functional aspects. In this paper, we proposed the correlation between the visual sensibility and the vital signal using the wearable based electrocardiogram sensing clothes. We measured the electrocardiogram (ECG) signal by wearing the electrocardiogram sensing clothes. The heart rate variability (HRV) is calculated form the acquired ECG signal by wearing the electrocardiogram sensing clothes. And the power spectrum analysis using the Fast Fourier Transform (FFT) is evaluated the correlation between the visual sensibility and the vital signal. we plan to conduct empirical applications to verify the adequacy and the validity of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.6
• /
• pp.1151-1156
• /
• 2007

In this paper, we develop a new conversion method for implementing binary ECG(Electrocardiogram) conversion scheme to improve our previous research works that supported the conversion of binary ECG files into HL7 aECG for enhancing interoperability of ECG data. HL7 aECG is a XML-based standard for interoperability of ECG waveform. To improve the performance of ECG data conversion, we utilize a compilation-based ECG conversion method on binary ECG files. Our new method supports both flexibility of BED-based ECG conversion mechanism and the performance of direct conversion mechanism.

• Journal of The Korean Society of Clinical Toxicology
• /
• v.17 no.1
• /
• pp.28-31
• /
• 2019

Glyphosate herbicides, which are widely used worldwide, are known to have low toxicity. However, excessive intake may cause serious life-threatening complications; therefore, caution is needed when using them. A 51-year-old man visited the hospital after ingesting glyphosate herbicide. At the time of admission, his vital signs were 80/60 mmHg-115/min-20/min-$37.3^{\circ}C$. Electrocardiogram (ECG) showed QRS widening and corrected QT (QTc) prolongation, and blood tests showed metabolic acidosis. Treatment with gastric lavage, activated charcoal, sodium bicarbonate and intravenous lipid emulsion therapy was performed. After 2 hours, his blood pressure increased to 130/90 mg, and no QRS widening was observed on ECG.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.13 no.1
• /
• pp.31-38
• /
• 2013

Patients with heart disease need long-term monitoring of the electrocardiogram (ECG) signal using a portable electrocardiograph. This trend requires the miniaturization of data storage and faster transmission to medical doctors for diagnosis. The ECG signal needs to be utilized for efficient storage, processing and transmission, and its data must contain the important components for diagnosis, such as the P wave, QRS-complex, and T wave. In this study, we select the vertex which has a larger curvature value than the threshold value for compression. Then, we reconstruct the compressed signal using by radial basis function interpolation. This technique guarantees a lower percentage of root mean square difference with respect to the extracted sample points and preserves all the important features of the ECG signal. Its effectiveness has been demonstrated in the experiment using the Massachusetts Institute of Technology and Boston's Beth Israel Hospital arrhythmia database.