• Fashion & Textile Research Journal
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• v.17 no.6
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• pp.1039-1049
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• 2015

The increase in the need for a 24 hour monitoring of biological signals has been accompanied by an increasing interest in wearable systems that can register ECG at any time and place. ECG-monitoring clothing is a wearable system that records heart function continuously, but there have been difficulties in making accurate measurements due to motion artifacts. Although various factors may cause noise in measurements due to motion, the variations in the body surface and clothing during movements that cause eventual the shifting and displacement of the electrodes is particularly noteworthy. Therefore, this study used biomedical body mapping and a motion-capture system to measure and analyze the changes in the body surface and garment during movements. It was deduced that the area where the friction and separation between the garment and skin is the lowest would be the appropriate location to place the ECG electrodes. For this study, 5 male and 5 female in their 20s were selected as subjects, and through their selected body movements, the changes in the garment and skin were analyzed using the motion-capture system. As a result, the area below the chest circumference and the area below the shoulder blades were proposed as the optimal location of electrode for ECG monitoring.

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

• Journal of Sensor Science and Technology
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• v.29 no.1
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• pp.19-26
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• 2020

Electrocardiogram (ECG) classification has become an essential task of modern day wearable devices, and can be used to detect cardiovascular diseases. State-of-the-art Artificial Intelligence (AI)-based ECG classifiers have been designed using various artificial neural networks (ANNs). Despite their high accuracy, ANNs require significant computational resources and power. Herein, three different ANNs have been compared: multilayer perceptron (MLP), convolutional neural network (CNN), and spiking neural network (SNN) only for the ECG classification. The ANN model has been developed in Python and Theano, trained on a central processing unit (CPU) platform, and deployed on a PYNQ-Z2 FPGA board to validate the model using a Jupyter notebook. Meanwhile, the hardware accelerator is designed with Overlay, which is a hardware library on PYNQ. For classification, the MIT-BIH dataset obtained from the Physionet library is used. The resulting ANN system can accurately classify four ECG types: normal, atrial premature contraction, left bundle branch block, and premature ventricular contraction. The performance of the ECG classifier models is evaluated based on accuracy and power. Among the three AI algorithms, the SNN requires the lowest power consumption of 0.226 W on-chip, followed by MLP (1.677 W), and CNN (2.266 W). However, the highest accuracy is achieved by the CNN (95%), followed by MLP (76%) and SNN (90%).

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.171-185
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• 2023

The cardiovascular syndrome is the dominant reason for death and the number of deaths due to this syndrome has greatly increased recently. Regular cardiac monitoring is crucial in controlling heart parameters, particularly for initial examination and precautions. The quantity of cardiac patients is rising each day and it would increase the load of work for doctors/nurses in handling the patients' situation. Hence, it needed a solution that might benefit doctors/nurses in monitoring the improvement of the health condition of patients in real-time and likewise assure decreasing medical treatment expenses. Regular heart monitoring via wireless body area networks (WBANs) including implantable and wearable medical devices is contemplated as a life-changing technique for medical assistance. This article focuses on the latest development in wearable and implantable devices for cardiovascular monitoring. First, we go through the wearable devices for the electrocardiogram (ECG) monitoring. Then, we reviewed the implantable devices for Blood Pressure (BP) monitoring. Subsequently, the evaluation of leading wearable and implantable sensors for heart monitoring mentioned over the previous six years, the current article provides uncertain direction concerning the description of diagnostic effectiveness, thus intending on making discussion in the technical communal to permit aimed at the formation of well-designed techniques. The article is concluded by debating several technical issues in wearable and implantable technology and their possible potential solutions for conquering these challenges.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.220-226
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• 2011

Device of the ECG and pulse signal was made to measure PTT signal using non-invasive method and possible to wearable. PTT alterations were observed according to position change using implemented system.It was needed to ECG and pulse to detect the PTT, used the photoplethymorgraphy appeared to change the blood volume. And also wireless sensor node which was able to Zigbee compatibility was used to transfer the detected ECG and pulse signal to PC. Noise was removed from transit data and algorithm was applied to calculate the PTT. After the evaluation of both the conventional measuring systems and the proposed photoplethymography measuring system, a highly effective and efficient formation and distribution sequences were found within the proposed photoplethymography measuring system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1690-1698
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• 2018

Recent advances in ICT technology have transformed many of our daily lives and attracted a lot of attention to personal health. Heart beat measurement that reflects cardiac activities has been used in various fields such as exercise evaluation and psychological state evaluation for a long time, but its utilization method is limited due to its differentiation from clinical electrocardiogram. Therefore, in this study, we could observe the change of the measured signal according to the change of the distance and the position of the measuring electrodes which are non-standard electrode configuration. Based on the electric dipole model of the heart, correlation with clinical electrocardiogram could be confirmed by synthesizing multiple surface potentials measured with a shorter electrode distance than standard one. From the electromagnetic point of view, the distance between the measuring electrodes corresponds to the distance that the electric potential by the cardiac electric dipole moves, and the electric potential measured at the body surface is proportional to the moving distance of the electric potential. Therefore, it is preferable to make the distance between electrodes as long as possible, and to position the measuring electrode close to the ventricle rather than the atrium. In addition, it was found that standard electrocardiographic waveforms could be synthesized by using arithmetic sum of multiple measuring electrodes due to the relationship of electrical dipole vectors, which is obtained by dividing and positioning a plurality of measuring electrodes on a reference electrode line, such as Lead-I, Lead-II direction. Also, we obtained a significant Pearson correlation coefficient ($r=0.9113{\pm}0.0169$) as a result of synthetic experiments on four subjects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.421-425
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• 2006

An ubiquitous healthcare system for the home care of elderly persons was designed and implemented using wireless sensor network technology. The wireless technology for home-care purpose gives new possibilities for monitoring of vital parameter with wearable biomedical sensors, and will give the patient the freedom to be mobile and still be under continuously monitoring and thereby to better quality of patient care. Emphasis is placed on recent advances in wireless ECG system for cardiac event monitoring with particular attention to arrhythmia detection in patient. This paper presents a diagnostic system for cardiac arrhythmias from ECG data, using wireless sensor technology. The system also provides an application for recording activities, events and potentially important medical symptoms. The hardware allows data to be transmitted wirelessly from on-body sensor to the base station and then to PC/PDA. Data is also transmitted to a back-end server for analysis using wireless internet connection. Experiments were conducted using the system for activity monitoring, exercise monitoring and medical screening tests and present preliminary data and results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1469-1476
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• 2022

Recently, many researches have been conducted to estimate blood pressure using ECG(Electrocardiogram) and PPG(Photoplentysmography) signals. In this paper, we designed and implemented a mobile system to monitor blood pressure in real time by using 1-D convolutional neural networks. The proposed model consists of deep 11 layers which can learn to extract various features of ECG and PPG signals. The simulation results show that the more the number of convolutional kernels the learned neural network has, the more detailed characteristics of ECG and PPG signals resulted in better performance with reduced mean square error compared to linear regression model. With receiving measurement signals from wearable ECG and PPG sensor devices attached to the body, the developed system receives measurement data transmitted through Bluetooth communication from the devices, estimates systolic and diastolic blood pressure values using a learned model and displays its graph in real time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1448-1454
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• 2014

In this study, a new type of electrode device is implemented to measure the capacitance energy and interpret it as the ECG (Electrocardiogram) data. The main idea of this new electrode system is to estimate the capacitance on the skin by assembling a capacitive-coupled circuits and translate into the ECG signal. To measure the coupling energy and estimate the aquired data in terms of heart activity, the capacitive-coupled electrode is garmented with fabrics in the form of a chest band or a vest jacket. To compare the ECG data from the capacitive-coupled electrode with the conventional electrode(Ag-AgCl) system, the corelation coefficient between two signals is computed as 0.9517. Thus, we can conclude the fact that capacitive-coupled electrode system can measure a person's heart activity without any contact to his or her skin and can the interpreted as the ECG data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.990-991
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• 2013

본 연구에서는 모바일 환경에서 장시간 심전도 계측 시 발생하는 무선 및 배터리의 제한적인 자원의 문제점을 해결하기 위하여 낮은 연산량과 높은 압축률을 가지는 템플릿 매칭 기반의 압축 알고리즘을 구현하였다. 템플릿 매칭 기법을 이용한 심전도 데이터 압축은 심전도의 특징점인 R-peak를 검출하여 템플릿을 생성하고 이후 입력되는 심전도 신호와 유사성을 판단하여 해당되는 템플릿의 정보만 저장하고 전송하는 방법이다. 구현된 알고리즘의 성능평가를 위하여 MIT-BIH Normal Sinus Rhythm Database의 10개 레코드에서 각각 10분간 데이터를 추출하여 성능평가를 수행하였으며, 이때, 압축률과 복원율 오차의 평균이 각각 7.94% 와 5.33%의 성능을 나타내었다.