• Journal of Yeungnam Medical Science
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• v.2 no.1
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• pp.77-80
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• 1985

The R-R interval analyzer was developed to measure the autonomic nervous system function using microcomputer. The system based on 8 bit microcomputer including bandpass filter, R-wave detector and clock generator in order to obtain the mean value, standard deviation, total time, CV value, maximum value and minimum value in the specific view point of R-R interval variation. The pattern of R-R interval change after resting, voluntary standing and deep breathing can be analysed in normal subjects and diabetics with autonomic nervous dysfunction. The amplitude of the R-R interval variation showed sensitive pattern for normal subjects at resting, standing and deep breathing. On the contrary, the periodicities of amplitude for abnormal subjects with autonomic nervous dysfunction showed dull pattern. It was suggested that R-R interval analyzer is a good detection method for dysfunction of autonomic nervous system.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.227-237
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• 2014

The purpose of this paper is to implement a multiple bio-signal central monitoring system based on textile fabrics flexible platform which can obtain and monitor bio signals(heart rate, body temperature, electrocardiography, electromyogram) of workers in special working environments and additional situational information (3-axis acceleration, temperature, humidity, illumination, surrounding image). This system can prevent various accidents that may occur in the remote work environment and provide fast and efficient response by detecting workers' situations in real-time. For it, the textile fabrics flexible platform was made as innerwear or outerwear so that it does not interfere with workers' performance while collecting bio-signal and situational information, and obtained information is sent to the central monitoring system through wireless communication. The central monitoring system is based on wireless medical telemetry service of WMTS (Wireless Medical Telemetry Service); can monitor from 2 to 32 people simultaneously; and was designed so that it can be expanded. Also, in this study, to verify performance of the WMTS communication model, packet transmission rates were compared according to the distance.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.76-83
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• 2022

With the recent development of IT technology, research and interest in various biosignal measuring devices is increasing. As an aging society is in full swing, research on the elderly population using IT-related technologies is continuously developing. This study is about the development of life pattern detection and fall detection algorithm, which is one of the medical service areas for the elderly, who are rapidly developing as they enter a super-aged society. This study consisted of a system using a 3-axis accelerometer and an electrocardiogram sensor, collected data, and then analyzed the data. It was confirmed that behavioral patterns could be classified from the actual research results. In order to evaluate the usefulness of the human activity monitoring system implemented in this study, experiments were performed under various conditions, such as changes in posture and walking speed, and signal magnitude range and signal vector magnitude parameters reflecting the acceleration of gravity of the human body and the degree of human activity. was extracted. And the possibility of discrimination according to the condition of the subject was examined by these parameter values.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.335-342
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• 2014

According to the recent trends in the growing elderly population, the chronically ill have increased. Thus the importance of the health care issues for them has emerged. In this paper, we want to implement a chronic disease management system using smart mobile devices. Proposed chronic disease management system is consisted of the biometric sensor, smart mobile devices, the patient management server, patient management DB, and patient symptoms analysis agent. The biometric sensor detects a biological information. Smart mobile devices receive the patient information from the sensor and transmit the information to the patient management server. The patient management server, patient management DB, and patient symptoms agent analysis agent analyze to process data delivered through a wireless communication network. Bio-signals includes modules of ECG, blood pressure, blood sugar and PPG. We are able to determine the current health status by monitoring measured biometric data through chronically ill health management system. We will focus on the individual service to be appropriate for a patient group in a mobile environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1389-1397
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• 2016

This study was to evaluate opportunities for the commercialization of smart insole. smart technology is evolving to Insole. Pressure-sensitive sensor or an acceleration sensor is applied to create a balance of the feet and body, is also evolving for entertainment (sports, entertainment, etc.) and health care. Moreover, smart insole can fix an incorrect walking habit by sending a weight value measured by the sensor on a smartphone and during the movement, smart insole helps to correct body balance by measuring the center of gravity moving condition. However, smart tendency of the insole has yet to create a clear boundary in the entertainment and healthcare markets. This is because the fitness band, smart socks, smart shoes can also replace the benefits of a smart insole. Interestingly, the business opportunities are appearing more frequently in health care solution service of electrocardiogram, body temperature, blood pressure, etc., rather than smart devices.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.197-202
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• 2010

In this paper, multi-channel vital signal monitoring system was implemented for home healthcare. The system able to measure vital signal for example ECG, PPG and temperature simultaneously at patients’ home. The vital signal is an essential parameter for healthcare application and can be easily extracted from patients. The implemented system consist of sensor parts for signal extraction, signal amplifier and filter for analog circuit, analog signal to digital conversion for controlling devices and lastly the monitoring program. The system able to transmit vital signals using Bluetooth wireless communications to personal computer or home server. And the tele-monitoring system able to display real-time signals using web monitoring program. In medical application, the vital signal parameter able to stored and saved in the web server for further medical analysis. This system opens up the possibilities of ubiquitous healthcare where further implementation can be easily done.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.19-26
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• 2010

In this paper, we studied about the Embedded System of the biosignal measurement and analysis to sensibility evaluation in daily life for non-intrusive. This system is two kinds of measuring biosiganls(Electrocardiogram:ECG, Photoplethysmography:PPG) and analyzed by real-time wireless transmission to notebook PC using bluetooth for consistent and reliability of physiological way to assess continuously changing sensibility. Comparative studied of an autonomic nerve system activity ratio on characteristics frequency band of two kinds of biosignal analyzed frequency way using the Fast Fourier Transform(FFT) and Power Spectrum Density(PSD). Also the key idea of this system is to minimize computing of analysis algorithm for faster and more accurate to assess the sensibility, and the result of the visualization using graph. In this paper, we evaluated the analysis system to assess sensibility that measuring various situation in daily life using a non-intrusive biosignal measurement system, and the accuracy and reliability in comparison with difference of result by development analysis system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.537-545
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• 2009

Though there were many research and development about telemedicine on land recently, not yet applied to that on the shore. In this paper, when emergency clinic situation were generated in a ship on shore, the telemedicine system was designed and implemented for transfer and clinic service to doctors on the land by measuring basic body signals of patients. Presently, wireless communication and inmarsat telephone are usually used by simple questions and clinic consults to remote doctors when emergency situation were happened in the ship. In this paper, the telemedicine system on the shore were developed for improving this problems by measuring patient's fundamental conditions such as the blood pressure, pulse, the respiratory condition, electrocardiogram, body temperature, patient image and sending these information to remote doctors on land for more accurate prescription. The developed system can supply the high level clinic service to emergency patients on the shore and cope with the emergency situation in ship.

• 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.

• Journal of Biomedical Engineering Research
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• v.22 no.5
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• pp.469-477
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• 2001

In this Paper. we describe a home health care service using electronic health questionnaires and routine checkup of vital signs Including ECG (Electrocardiography) , blood pressure. and SpO$_2$ (Oxygen Saturation) . This system is for patients at home with chronic diseases, discharged Patients, or any normal people for the Prevention of disease The service requires a home health care terminal and a PC with Interned connection installed at Patient home. The distance health care management center is equipped with a vital-sign and questionnaire interpreter as well as database, Web, and notification servers with UMS (Unified Messaging System). Participating Physician can access the servers at the center using a Web browser running on a PC available to them at any time. These components are linked together through various kinds of data and voice communication channels including PSTN (Public Switched Telephone Network) . CATV(Community Antenna TV) . Interned. and mobile communication network. Following the Physician's direction given to a Patient. he or she uses the home health care terminal to collect vital signs and fill out the questionnaire. When the terminal automatically transmits these data to the management center. the data interpreter and servers at the center process the information fo1lowing the Protocol implemented on the system. Physicians can retrieve and review data corresponding to their Patients and send back their diagnostic reports to the center. UMS at the center delivers the physician 's recommendation to the corresponding patient through the notification server. Patients can also reprieve and review their own records as well as diagnostic reports from physicians. The system Provides a new way of collecting diagnostic information and delivering doctor's recommendation to patients at home for their health management. Future works are needed in the development of new technology for measurements and interpretations of various vital signs .