• Journal of Sensor Science and Technology
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• v.19 no.1
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• pp.43-51
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• 2010

In this study, wearable ECG measurement system was implemented for health monitoring during daily life. A wearable belt-type ECG electrode worn around the chest by measuring the real-time ECG is produced in order to minimize the inconvenience in wearing. The measured ECG signal is transmitted via an ultra low power consumption wireless data communications unit to personal computer using Zigbee-compatible wireless sensor node. The ECG monitoring program is developed at end user which is personal computer. The measured ECG contains many noises mainly due to motion artifacts. For ECG signal processing, adaptive filtering process is proposed which can reduce motion artifacts efficiently and accurately than digital filter. The experimental results show that a reliable performance with high quality ECG signal can be achieved using this wearable ECG monitoring system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.337-340
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• 2009

Wireless tele-home-care application gives new possibilities for ECG (electrocardiogram) monitoring system with wearable biomedical sensors. Thus, continuously development of high convenient ECG monitoring system for high-risk cardiac patients is essential. This paper describes to monitor a person's ECG using wearable approach. A wearable belt-type ECG electrode with integrated electronics has been developed and has proven long-term robustness and monitoring of all electrical components. The measured ECG signal is transmitted via an ultra low power consumption wireless sensor node. ECG signals carry a lot clinical information for a cardiologist especially the R-peak detection in ECG. R-peak detection generally uses the threshold value which is fixed thus it bring errors due to motion artifacts and signal size changes. Variable threshold method is used to detect the R-peak which is more accurate and efficient. In order to evaluate the performance analysis, R-peak detection using MIT-BIH databases and Long Term Real-Time ECG is performed in this research. This concept able to allow patient to follow up critical patients from their home and early detecting rarely occurrences of cardiac arrhythmia.

• 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.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.11
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• pp.1141-1148
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• 2016

This paper proposed a heart attack predictive monitoring system using QRS pattern of ECG for wearable healthcare. It detects abnormal heart pattern with a ECG (X, Y) coordinate pattern DB on wearable monitoring smart watch. We showed the acute heart failure prevention system and method with a proposed scheme. Especially, It proved the method which can do first aid in gold time through abnormal heart analysis with a digital ECG(X, Y) pattern information when acute heart failure occurs.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.310-314
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• 2023

In this paper, we show that the limitations of Holter monitoring and Wearable Electrocardiogarphy Devices and their arrhythmia detection. Sudden death caused by cardiovascular disease, often referred to as the "silent killer" due to its unpredictable nature, is a major health concern. Electrocardiography (ECG) is a basic diagnostic tool for detecting heart disease, but its limitations make it difficult to detect arrhythmia, a significant indicator of an irregular heart state. To address this limitation, a long-term continuous ECG recording device has been developed, Holter ECG device and wearable device. A significant number of studies have focused on the differences between Holter monitoring and wearable devices. The Holter tests were useful for detecting regularly occurring arrhythmias, whereas wearable patches were better at detecting random and infrequent arrhythmias. Wearable patches were effective in detecting episodes of arrhythmia and myocardial ischemia. Despite the concern, wearable devices had less signal loss than Holter monitoring and patients also preferred wearable devices over Holter monitoring due to convenience. These results could mean that the wearable devices can perfectly replace the Holter test.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.920-923
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• 2003

An wearable electrocardiogram (ECG) monitoring system is a widely used non-invasive diagnostic tool for ambulatory patient who may be at risk from latent life-threatening cardiac abnormalities. In this paper, we have a portable ECG monitoring system with conductive fiber which was characterized by the small-size and the low power consumption. The system consists of conductive fibers, one-chip microcontroller, ECG preprocessing circuit, and monitoring software to be able to record and analyze in PC. ECG preprocessing circuit is made of pre-amplifier with gain of 10, band-pass filter with bandwidth of 0.5-120Hz and 2.5V offset circuit for A/D conversion. ECG signals obtained by sensor are included with corrupted noises such as a baseline wandering, 60 Hz power noise and interference noise by body movement. For cancellation corrupted noises in signals obtained by conductive fiber, we used the wavelet decomposition of wavelet transforms in MATLAB toolbox.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.667-670
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• 2007

Wellness monitoring is a growing area that will benefit from the use of wearable computing systems. The purpose of this study is to implement the wearable ECG monitoring system for ubiquitous healthcare. This paper presents a prototype wearable wellness monitoring system capable of measuring, transmitting and analyzing continuous ECG data. The hardware system allows data to be transmitted wirelessly from chest belt type sensors to a server PC using Zigbee. We conducted experiments using the system for ECG monitoring and medical screening tests and present preliminary data and results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1109-1115
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• 2008

In the ubiquitous health monitoring environments, it is quite important not only to evaluate the physiological health condition but also mental stress condition. In order to achieve this goal, a heart activity monitoring system utilizing a wearable bipolar electrode is devised and the heart rate variability(HRV) is extracted and interpreted in both frequency and time feature domains. Consequently, to evaluate the emotional stress condition of the subjects, a stress-induced experimental protocol was applied to healthy subjects and the time and frequency features of heart activity were analyzed in terms of the ratio of low frequency components v.s., high frequency components and the relevant the moving average distributions compromising the successive RR peaks intervals in the ambulatory ECG measurement system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1102-1108
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• 2008

Wearable physiological signal monitoring systems are regarded as an important sensing unit platforms in ubiquitous/mobile healthcare application. In this paper, we suggested the modified bipolar electrodes implemented on the portable heart activity monitoring system, which minimized the distance of electrodes formed on a attachable pad. The proposed electrode configuration is useful in mobile measurement environments, but has a disadvantage of reduced amplitude of the heart action potential. In order to overcome the shortcoming of the suggested electrode configuration, we implemented the amplifying circuit to increase the signal-gain and decrease the artifacts. For evaluations, we analyzed the specificity of measured cardiography using the proposed electrodes through the comparing of heart activity monitoring system with standard clinical ECG(lead2) by pearson correlation coefficients. The result showed that the average correlation coefficient is $0.903{\pm}0.036,\;0.873{\pm}0.072$ at V3, V4 chest lead position, respectively. Thus, the modified bipolar electrode is quite suitable to monitor the electrical activity of the heart in the situation of the mobile environment, and could be considered having high similarity with standard clinical ECG.

• Journal of Sensor Science and Technology
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• v.20 no.6
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• pp.382-387
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• 2011

Whether a person is feeling sleepy or reasonably awake is important safety information in many areas, such as humans operating in traffic or in heavy industry. The changes of body signals have been mostly researched by looking at electroencephalogram(EEG) signals but more and more other medical signals are being examined. In our study, an electrocardiogram(ECG) signal is measured at a sampling rate of 100 Hz and used to try to distinguish the possible differences in signal between the two states: awake and drowsy. Practical tests are conducted using a wireless sensor node connected to a wearable ECG sensor, and an ECG signal is transmitted wirelessly to a base station connected to a server PC. Through the QRS complex in the ECG analysis it is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease. A program is made with MATLAB for digital signal filtering and graphing as well as recognizing the parts of the QRS complex within the signal. Drowsiness detection is performed by evaluating the R peaks, R-R interval, interval between R and S peaks and the duration of the QRS complex..