• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1997년도 추계학술대회
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• pp.415-419
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• 1997

The left ventricular relaxation rate is used as a golden standard which describes the left ventricular diastolic unction. So far, to get the rate of relaxation one should calculate the data after full recording, that is, off-line method. Therefore one cannot get the rate of relaxation in real-time while changing loading condition or infusing drug. But real time monitoring of the relaxation rate is necessary while changing loading condition or infusing drug to control the mechanics of heart and to get more information. We propose a new criterion to get the left ventricular relaxation rate and a real time algorithm. By comparison, it was turned out that our criterion outperforms others criterion.

• 한국정보전자통신기술학회논문지
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• 제2권3호
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• pp.9-15
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• 2009

분만시 국내에서 영아 사망률은 약 1%에 이르고, 태아의 질병 발생과 사망은 계속적으로 일어나고 있으므로 저가의 태아 모니터링기술의 개발이 절실하다. 이를 위하여 본 연구에서는 임산부의 복부로부터 태아의 움직임과 심음을 검출할 수 있는 증폭기를 설계하여 고성능 태아 포노그램용 전자청진장치를 개발하고자 한다. 장치로부터 검출된 태아의 청진 신호는 듣거나 녹음할 수 있으며, PC에서 태아의 심음을 분석할 수도 있다. 개발된 증폭기를 이용하여 잡음에 노출된 일반 대학병원 환경에서 30명의 임산부를 대상으로 임상실험을 수행한 결과, 개발된 증폭기는 저잡음, 고이득의 특성을 나타내고, 임산부 중에서 빠른 경우 22주에서도 태아의 심음을 검출할 수 있었고, 심음의 주기검출이 가능하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권9호
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• pp.2512-2545
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• 2024

One of the biggest challenges for the medical professionals is spotting cardiovascular issues in the earliest stages. Around the world, Cardiovascular Diseases (CVD) are a major cause of death for almost 18 million people each year. Heart disease is therefore a serious concern that needs to be treated. The numerous elements that affect health, such as excessive blood pressure, elevated cholesterol, aberrant pulse rate, and many other factors, might make it challenging to detect heart disease. Consequently, early disease detection and the development of effective treatments can benefit greatly from the field of artificial intelligence. The purpose of this work is to develop a new IoT based healthcare monitoring framework for the prediction of CVD using machine learning algorithm. Here, the data preprocessing has been performed to create the normalized dataset for improving classification. Then, an Artificial Gorilla Troop Optimization (AGTO) algorithm is deployed to choose the most pertinent features from the normalized dataset. Moreover, the Multi-Linear Regression Classification (MLRC) model is also implemented for accurately categorizing the medical information as whether healthy or CVD affected. The results of the proposed AGTO-MLRC mechanism is validated and compared using the popular benchmarking datasets.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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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.

• 대한의용생체공학회:의공학회지
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• 제35권5호
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• pp.125-131
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• 2014

The purpose of this study is to verify the utility of reflected photoplethysmography sensor using two green light emitting diodes that influenced by ambient light. Recently it has been studied that green light emitting diode is suitable for light source of reflected photoplethysmography sensor at low temperature and high temperature. Another study showed that, green light is better for monitoring heart rate during motion than led light. However, it has a bad characteristic about ambient light noise. To verify the utility of reflected photoplethysmography sensor using green light emitting diode, this study measures the photoplethysmography signal that is distorted by ambient light and will propose a solution. This study has two parts of research method. One is measurement system that composed sensor and board. The sensor is made up PE-foam and Non-woven fabric for flexible sensor. The photoplethysmography signal is measured by measurement board that composed high-pass filter, low-pass filter and amplifier. Ambient light source is light bulb and white light emitting diode that has three steps brightness. Photoplethysmography signal is measured with lead II electrocardiography signal at the same time and it is measured at the finger and radial artery for 1 minute, 1000 Hz sampling rate. The lead II electrocardiography signal is a standard signal for heart rate and photoplethysmography signal that measured at the finger is a standard signal for waveform. The test is repeated 3 times using three sensor. The data is processed by MATLAB to verify the utility by comparing the correlation coefficient score and heart rate. The photoplethysmography sensor using two green light emitting diodes is shown better utility than using one green light emitting diode and red light emitting diode at the ambient light. The waveform and heart rate that measured by two green light emitting diodes are more identical than others. The amount of electricity used is less than red light emitting diode and error peak detectability factor is the lowest.

• 센서학회지
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• 제15권6호
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• pp.417-424
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• 2006

An ubiquitous healthcare monitoring system for elderly person at home was designed for continuous healthy monitoring of elderly person or patients. Human vital signals, such as ECG and body temperature, were monitored by terminal PC or PDA via ECG and temperature sensor nodes on the patient's body. From the ECG data, the heart rate, tachycardia, bradycardia and arrhythmia were diagnosed on the terminal PC or PDA to assist doctor's or nurse's aid or patient itself to monitor the patient's condition and give medical examination. Artificial judgement support system was designed in server computer and the system support a doctor or nurser for management or treatment of the patient. This system can be applied to vital signal monitoring system for solitude elderly person at self house or home health care service part. And this ubiquitous healthcare system can reduce the medical expenses in coming aging or aged society.

• Journal of electromagnetic engineering and science
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• 제3권1호
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• pp.45-49
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• 2003

Wireless life signal detecting system is implemented with using the mechanism of Doppler Effect. This system can measure the respiration and heart rates with the periodic movement of skin and muscle near the heart. The system is consisted of antenna, RF transmitter, receiver, and display part. We did use two operating frequencies at 1.9 ㎓ and 10 ㎓. Firstly, the link budget about detecting system is analyzed and the signal detected from the system is compared with electrocardiogram(ECG) of monitor which is using for patient monitoring in hospital. Secondly, the detection of vital sign is also performed according to the different distances, and including behind the wall.

• 대한의용생체공학회:의공학회지
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• 제28권1호
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• pp.36-45
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• 2007

Today Human Personal Trainers are becoming very famous in this health conscious world. They teach user to achieve fitness goals in managed way. Due to their high fee and tight schedule they are unavailable to mass number of people. Another solution to this problem is to develop digital personal trainer portable instrument that may replace human personal trainers. We developed a portable digital exercise trainer device - BIOFIT that manages, monitors and records the user's physical status and workout during exercise session. It guides the user to exercise efficiently for specific fitness goal. It keeps the full exercise program i.e. exercises start date and time, duration, mode, control parameter, intensity in its memory which helps the user in managing his exercise. Exercise program can be downloaded from the internet. During exercise it continuously monitors the user's physiological parameters: heart rate, number of steps walked, and energy consumed. If these parameters do not range within prescribed target zone, the BIOFIT will alarm the user as a feedback to control exercise. The BIOFIT displays these parameters on graphic LCD. During exercise it continuously records the heart rate and number of steps walked every 10 seconds along with exercise date and time. This stored information can be used as treatment for the user by an exercise expert. Real-time ECG monitoring can be viewed wirelessly (RF Communication) on a remote PC.

• Safety and Health at Work
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• 제13권2호
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• pp.148-154
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• 2022

Background: Bus driving is a mentally demanding activity that requires prolonged attention to ensure safety. The aim of the study was to assess mental fatigue caused by driving a public bus and to find a profile of workers at higher risk. Methods: We evaluated changes of critical flicker fusion (CFF) (index of central arousal) and heart rate variability (HRV) (index of autonomic balance) in a 6-hour driving shift on a real route, in 31 professional bus drivers, and we tested the influence of personal factors such as sleep quality, BMI, and age. Paired t-test was used to test differences of CFF and HRV between both initial and final phase of driving, while multiple linear regression tested the influence of personal variables on the indexes of mental fatigue. Results: Results showed that CFF significantly decreased after 6 hours of bus driving (41.91 Hz, sd 3.31 vs. 41.15 Hz, sd 3.15; p = 0.041), and heart rate significantly decreased in the final phase of driving, with respect to the initial phase (85 vs. 78 bpm, p = 0.027). Increasing age (beta = -0.729, p = 0.022), risk of obstructive sleep apnea syndrome (beta = -0.530, p = 0.04), and diurnal sleepiness (beta = -0.406, p = 0.017) showed a significant effect on influencing mental fatigue. Conclusion: Elderly drivers at higher risk of sleep disorders are more prone to mental fatigue, when exposed to driving activity. Monitoring indexes of central arousal and autonomic balance, coupled with the use of structured questionnaires can represent a useful strategy to detect profile of workers at higher risk of mental fatigue in such duty.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.41-43
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• 2005

PDA-based monitoring is used to acquire continuously the patient's vital signs, including electrocardiography, activity, heart rate and $SpO_2$. In this paper, A biomedical signal acquisition device was designed using 3-axial MEMS accelerometer and 1-ch ECG amplifier, to have the function of monitoring activity and electrocardiography. The proposed system is composed of transmitter and receiver. Through the Zigbee communication, subject's biosignals can be transmitted in real-time to receiver, and transmitted data confirmed using PDA. The packet size used in this device was set not to exceed a maximum payload size of 116 byte. One packet consists of two segments. The transmission speed was 21 packet per second, 420 ECG samples per second, and 42 acceleration samples per second. The proposed method can be used to develop Activities of Daily Living(ADL} monitoring devices for the elderly or movement impaired people and enables patients to be monitored without any constraints. Also, this method will reduce medical costs in the aged society.