• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.77-81
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• 2021

In this paper, a low-csst ECG system using a digital filter was implemented. After amplifying the analog ECG signal, it is converted into a digital signal and filtered. The developed ECG module is miniaturized by removing the analog filter element that occupies the existing volume and replacing it with a digital filter using a 3-stage Butterworth filter which is one of IIR filters. It uses a serial monitoring program with C# to check and save the ECG waveform measured on a computer screen. The ECG system using a developed digital filter in this paper uses a low-cost processor instead of an expensive, high-end processor, and its size and price are reduced by converting the analog filter to a digital filter. In addition, since the waveform of the developed ECG system is similar to the actual ECG waveform of MIT-BIU, it is considered that the existing analog filter can be replaced with the developed digital filter.

• ETRI Journal
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• v.29 no.4
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• pp.530-532
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• 2007

This paper presents a simple method to implement a complete on-line portable wireless holter including an electrocardiogram (ECG) monitoring, processing, and communication protocol. The proposed algorithm significantly reduces the hardware resources of threshold estimation for ECG compression, using the standard deviation updated with each new input signal sample. The new method achieves superior performance in terms of hardware complexity, channel occupation and memory requirements, while keeping the ECG quality at a clinically acceptable level.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.347-350
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• 2007

An ECG analysis with activity monitoring for the home care of elderly persons or patients, using wireless sensors technology was design and implemented. The changes in heart rate occur before, during, or following behavior such as posture changes, walking and running. Therefore, it is often very important to record heart rate along with posture and behavior, for continuously monitoring a patient's cardiovascular regulatory system during their daily life activity. The ECG and accelerometer data are continuously recorded with a built-in automatic alarm detection system, for giving early alarm signals even if the patient is unconscious or unaware of cardiac arrhythmias. The hardware allows data to be transmitted wirelessly from on-body sensors to a base station attached to server PC using IEEE802.15.4. If any abnormality un at server then the alarm condition sends to the doctor' PDA (Personal Digital Assistant).

• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.137-144
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• 2011

Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.

• Science of Emotion and Sensibility
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• v.11 no.3
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• pp.419-426
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• 2008

In order to develop "textile electrode - sensing clothing" which is a sort of smart clothing to measure electric activities of heart, we propose possible ways to develop textile electrode and design of sensing clothing, ultimately aiming to develop "ECG sensing clothing for lifestyle monitoring". Conventional sensors for measuring typical electric activities of heart keep certain distance between measuring electrodes to measure signals for electric activities of heart, but these sensors often cause inappropriate factors (e.g. motional artifacts, inconvenience of use, etc) for monitoring natural cardiac activities in our daily life. In addition, most of textile electrodes have made it difficult to collect data due to high impedance and unstable contact between skin and electrodes. To overcome these questions, we minimized distance between electrodes and skin to maximize convenience of use. And in order to complement contact between skin electrodes, we modified textile electrode's form and developed ways to design clothing. As a result, we could find out clinical significance by investigating possible associations of clinical electrocardiogram (ECG) with variation of distance between electrodes, and could also demonstrate clinically significant associations between textile electrode developed herein and clothing.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1303-1310
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• 2010

Recently, researches related with automative mechanism have been widely studied to increase the driver's safety by continuously monitoring the driver's health condition to prevent driver's drowsiness. This paper describes the design of wearable chest belt for ECG and reflectance pulse oximetry for SpO2 sensors based on wireless sensor network to monitor the driver's healthcare status. ECG, SpO2 and heart rate signals can be transmitted via wireless sensor node to base station connected to the server. Intelligent monitoring system is designed at the server to analyze the SpO2 and ECG signals. HRV (Heart Rate Variability) signals can be obtained by processing the ECG and PPG signals. HRV signals are further analyzed based on time and frequency domain to determine the driver's drowsiness status.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.505-508
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• 2008

Electrocardiogram (ECG) and blood pressure (BP) are main vital signs which are the standards in most medical settings in assessing the most basic body functions. Multi parameters are desired in providing more information for health professionals in order to detect or monitor medical problems of patients more precisely. This study urges us to develop a robust wireless healthcare monitoring system which has multiple physiological signs measurements on real time that applicable to various environments which integrates wireless sensor network technology and code division multiple access (CDMA) network with extended feature of locally standalone diagnosis algorithms that implemented in tell phone. ECG signal and BP parameter of the patients are routinely be monitored, processed and analyzed in details at cell phone locally to produce useful medical information to ease patients for tracking and future reference purposes. Any suspected or unknown patterns of signals will be immediately forwarded to hospital server using cell phone for doctors' evaluation. This feature enables the patients always recognize the importance of self-health checking so that the preventive actions can be taken earlier through this analytic information provided by this monitoring system because "Prevention is better than Cure".

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

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.1
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• pp.60-70
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• 2014

Purpose: Bedside electrocardiograph (ECG) monitoring is continuously used for assessing patients' cardiac status in intensive care units. However, it has not been explored whether it is used with proper knowledge and nursing practices; if not, its usage will be limited and the risk for compromised patient safety might be significant. This study, therefore, explored knowledge and nursing practices regarding bedside ECG monitoring in nurses working at intensive care units. Methods: Participants in this survey research were a convenience sample of 156 nurses from 25 intensive care units distributed in five hospitals with more than 1,000 beds each in Seoul, South Korea. Results: Participants showed limited and incorrect knowledge and nursing practices. Only 4 (2.6%) participants correctly answered to all electrode placement sites of RA, LA, LL, and V1. Lead II was the most frequently monitored unit regardless of the main purpose of ECG monitoring, and nursing practices to manage noisy signals did not include skin care at the top priorities. Conclusion: Educators and clinicians alike need to make an effort to ensure that a safe level of knowledge and practices for the monitoring is maintained in order to make sure that patient outcomes are not compromised.