• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.898-902
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• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

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

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.162-171
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• 2020

The incidences of cardiovascular diseases are rapidly increasing worldwide. The electrocardiogram (ECG) is a test to detect and monitor heart issues via electric signals in the heart. Presently, detecting heart disease in real time is not only possible but also easy using the myDAQ data acquisition device and LabVIEW. Hence, this paper proposes a system that can acquire ECG signals in real time, as well as detect heart abnormalities, and through light-emitting diodes (LEDs) it can simultaneously reveal whether a particular waveform is in range or otherwise. The main hardware components used in the system are the myDAQ device, Vernier adapter, and ECG sensor, which are connected to ECG monitoring electrodes for data acquisition from the human body, while further processing is accomplished using the LabVIEW software. In the Results section, the proposed system is compared with some other studies based on the features detected. This system is tested on 10 randomly selected people, and the results are presented in the Simulation Results section.

• Transactions on Electrical and Electronic Materials
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• v.16 no.1
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• pp.16-19
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• 2015

A wearable sensing ECG T-shirt for ubiquitous vital signs sensing is proposed. The sensor system consists of a signal processing board and capacitive sensing electrodes which together enable measurement of an electrocardiogram (ECG) on the human chest with minimal discomfort. The capacitive sensing method was employed to prevent direct ECG measurement on the skin and also to provide maximum convenience to the user. Also, low power integrated circuits (ICs) and passive electrodes were employed in this research to reduce the power consumption of the entire system. Small flexible electrodes were placed into cotton pockets and affixed to the interior of a worn tight NIKE Pro combat T-shirt. Appropriate signal conditioning and processing were implemented to remove motion artifacts. The entire system was portable and consumed low power compared to conventional ECG devices. The ECG signal obtained from a 24 yr. old male was comparable to that of an ECG simulator.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.478-491
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• 2019

This work develops a monitoring system for the population with health concerns. A belt integrated with an on-body circuit and sensors measures a wearer's selected vital signals. The electrocardiogram sensors monitor heart conditions and an accelerometer assesses the level of physical activity. Sensed signals are transmitted to the circuit module through digital yarns and are forwarded to a mobile device via Bluetooth. An interactive application, installed on the mobile device, is used to process the received signals and provide users with real-time feedback about their status. Persuasive functions are designed and implemented in the interactive application to encourage users' physical activity. Two signal processing algorithms are developed to analyze the data regarding heart and activity. A user study is conducted to evaluate the performance and usability of the developed system.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.2
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• pp.45-50
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• 2021

With the recent development of IT technology, research and interest in various bio-signal measuring devices are increasing. But studies related to ECG(electrocardiogram), which is one of the most representative bio-signals, particularly arrhythmic signal detection, are incomplete. Since arrhythmia has various causes and has a poor prognosis after onset, preventive treatment through early diagnosis is best. However, the 24-hour Holter electrocardiogram, a tool for diagnosing arrhythmia, has disadvantages in the limitation of use time, difficulty in analyzing motion artifact due to daily life, and the user's real-time alarm function in danger. In this study, an ECG and pulse monitoring device capable of continuous measurement for a long time, a real-time monitoring app, and software for analysis were developed, and the trend of the measured values was confirmed. In future studies, research on derivation of quantitative results of ECG signal measurement analysis is required, and further research on the development of an arrhythmic signal detection algorithm based on this is required.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.24-30
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• 2019

Modern people argue that mental health care is necessary because of various factors such as unstable income and conflict with others. Recently, equipments capable of measuring electrocardiogram (ECG) in wearable equipment have been widely used. In the case of overseas, it can be seen as a medical assistant [14]. By using such functions, studies are being conducted to distinguish representative emotions (joy, sadness, anger, etc.) with objective values. However, most studies are increasing accuracy by collecting complex bio-signals in a limited environment. Therefore, we examine the factors that have the greatest influence on the change and discrimination of biometric information on each stimulus.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1326-1328
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• 1987

This paper describes the design of digital signal processing system for the automatic diagnosis of ECG. The system comprises analog hardware, digital hardware, and control system by microcomputer. Also, since digital signal processing system can be equipped easily in microcomputer for the compact size(Single board), We expect to develop the Portable ECG Automatic Diagnosis System using this System.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1279-1286
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• 2021

The electrocardiogram (ECG) signal is a good indicator for early diagnosis of heart abnormalities. The ECG signal has a different reference normal signal for each person. And it requires lots of data to diagnosis. In this paper, we propose an adaptive OpenCL-based FPGA-GPU hybrid-layer platform to efficiently accelerate ECG signal diagnosis. As a result of diagnosing 19870 number of ECG signals of MIT-BIH arrhythmia database on the platform, the FPGA accelerator takes 1.15s, that the execution time was reduced by 89.94% and the power consumption was reduced by 84.0% compared to the software execution. The GPU accelerator takes 1.87s, that the execution time was reduced by 83.56% and the power consumption was reduced by 62.3% compared to the software execution. Although the proposed FPGA-GPU hybrid platform has a slower diagnostic speed than the FPGA accelerator, it can operate a flexible algorithm according to the situation by using the GPU.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.110-113
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• 1990

A new approach to impulsive noise rejection and background normalization of digitized electrocardiogram signals is presented using mathematical morphological operators that incoporate the shape information of a signal. A brief introduction to these nonlinear signal processing operators, as well as detailed description of the new algorithm, is presented. Empirical results show that the new algorithm has good performance in impulsive noise rejection and background normalization.