• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.261-268
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• 2014

This paper presents a electrocardiogram(ECG), electromyogram(EMG), and Photoplethysmography(PPG) signal wireless monitoring system based on Bluetooth Low Energy (BLE). ECG and EMG sensor interface analog front-end circuits are designed by using off-the-shelf parts. Texas Instruments(TI)'s CC2540DK is used for BLE-based communication. Two CC2540DK modules are used as Peripheral and Central nodes. In peripheral device, vital signals are acquired by the analog front-ends and fed to ADC for analog-to-digital conversion. The peripheral transmitts the data through the air to the central device. The central device receive the data and sends them to PC using UART. GUI is designed using Labview for displaying the acquired vital signals. The developed system can be used for future ubiquitous wireless healthcare system based on bluetooth 4.0.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.671-677
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• 2012

A black-box program was implemented in order to monitor abnormal symptoms of human body irregularly occurring during sleep. The system consists of sensor probing body signals, auxiliary devices such as the alarm, lamp, network camera, and signal monitoring computer. Various types of sensors, PPG, ECG, EEG, temperature, respiration sensor, G-sensor, and microphone were used to more exactly identify the causes of abnormal symptoms. If a symptom occurs, the system records the patient's condition to provide information being utilized in the treatment. The sensors are attached on some locations of body being proper to check a specific type of abnormal reaction. Based on the normal range and type of measurement data, criteria of signal levels were set to distinguish abnormal reaction. An abnormal signal being probed, the program starts to operate the lamp, alarm, and network camera at the same time and stores the signal and video data.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.551-552
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• 2021

본 논문에서는 촬영한 피부 영상(얼굴, 손 등)을 이용한 생체신호(맥박, 호흡, 혈압, 체온 등) 측정 S/W 기술을 제안한다. 기존의 생체신호 측정 기술은 다양한 센서(PPG, 압력 센서, 혈압계, 체온계 등)가 탑재된 측정 장치를 이용하여 상태를 측정하고 이를 진단하는 연구들이 진행되어 왔다. 각 각의 생체신호를 측정하기 위해서는 별도로 구비된 측정 장치들을 이용하여 개별적으로 생체신호를 측정하고 확인하여야 한다. 제안된 기술은 스마트 디바이스에 생체신호 측정 S/W의 설치만으로 카메라로 촬영한 피부 영상의 피부 관심 영역에서 계산된 색상 데이터를 이용하여 다양한 생체신호를 언제 어디서나 실시간으로 측정할 수 있으며, 생체신호 측정 성능 평가 결과 맥박수 2.63%, 호흡수 5.98%, 이완기 혈압 2.48%, 수축기 혈압 5.23% 및 체온 0.25%의 오차율이 계산되었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.109-114
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• 2010

In this paper, the implementation of a human signal sensing module that has capabilities to check and restore the weak signals from the human body is presented. A module presented in this paper consists of processing and sensing elements related to human pulse and body temperature and a controller implemented with SoC design method. PPG data is detected by a noise filtering process toward the amplified signal which is from the operating frequency between 0.1Hz - 10Hz. A digital temperature sensor is used to check the body temperature. A sensor outputs the corresponding value of the electric voltage according to the body temperature. Moreover, this paper discusses the implementation of an enhanced microprocessor which is synthesized with VHDL as a part of the SoC development and used to control the entire module. The SoC processor is implemented on a Xilinx Spartan 3 XC3S1000 device and has the achieved operating frequency of 10MHz. The implemented SoC processor core is successfully tested with macro memories in FPGA and the experimental results are hereby shown.

• Proceedings of the Korean Society of Computer Information Conference
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• 2011.06a
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• pp.273-276
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• 2011

우리는 감성 공학에 기반하여 일상 생활 속에서 비침습적이면서 사용하기 간편한 광전용적맥파신호를 계측하고 분석하는 이어폰형 생체 신호 측정 시스템에 관하여 연구하였다. 생체 신호 측정 시스템에서는 광전용적맥파(photoplethysmograph, PPG)와 3축 가속도로 생체 신호와 운동 신호를 활용하였다. 수신된 생체 신호인 광전용적맥파 신호는 Peak 검출 및 전처리 알고리즘을 통하여 심박동변동성(heart rate Variablity,HRV)에 대한 시계열 정보로 변환하고 고속 퓨리에 변환(Fast Fourier Transfirm, FFT)과 전력 스펙트럼 밀도 분석(Power Spectrum Density, PSD)방법으로 교감과 부교감 신경 활성도 변화를 관측하였고, 운동 센서로 움직임을 관측하였다. 수신부 시스템은 안드로이드 기반의 자바 어플리케이션으로 스마트 폰에서 구현하였고, 송신부인 이어폰 생체정보 측정모듈로 맥파를 측정하여 상황에 따라 변화하는 자율 신경계의 활성도비율을 확인하였다.

• Proceedings of the Korean Magnestics Society Conference
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• 2011.06a
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• pp.196-198
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• 2011

• Proceedings of the Korean Magnestics Society Conference
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• 2011.06a
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• pp.194-195
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• 2011

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.992-999
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• 2009

The pulse transit time(PTT), which is determined by measuring the electrocardiogram(ECG) and pulse wave, gives comprehensive information about the cardiovascular system. However, a little movement of body and/or inaccurate pressure applied to skin during the measurement of pulse wave leads to acquire incorrect results. To overcome such problem, we developed an integrated sensor system which makes it possible to measure ECG, pressure pulse wave(PPW) and photoplethysmograph(PPG) at the same time. Futhermore, we implemented a new metal electrode which enables to continuously measure ECG. We verified that both integrated sensor system and new electrode provide useful effect.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.857-861
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• 2016

In this study, we proposed a new method that can be measure ECG (Electrocardiography) and PPG (Photoplethysmography) in realtime on the site of the wrist for check the state of health in daily life. For convenience measurement of ECG the lead I method was used on the wrist, and omit the reference junction ECG I was measured in the right hand and the left hand of the potential difference. Then the measured electrocardiogram was amplified by the differential amplifier and the signals were passed HPF, LPF, and BPF filters. For removing the PPG's noise from the Motion artifact and temperature, we apply the reflective photoelectric volume pulse wave measurement method using green LED as a light source. The circuits was designed to be able to check the waveform using higher active amplification method at weak signals. For the validation of our device, the measured signals were compared with E2-KIT on same time. The results shows that the error does not exceed the maximum one, most of the data is confirmed to be issued Peak inspection of the same number.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1252-1256
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• 2016

Internet of Things(IoT)-devices are now expanding inter-connecting networking technologies to invent healthcare monitoring system especially for assessing physiological conditions of the chronically-ill patients those with cardiovascular diseases. Hence, IoT system is expected to be utilized for home healthcare by dedicating the original usage of IoT devices to collect the biomedical data such as electrocardiogram(ECG) and photoplethysmography(PPG) signal. The aim of this work is to implement health monitoring system by integrating IoT devices with Raspberry-pi components to measure and analyze ECG and the multi-channel PPG signals. The acquired data and fiducial features from our system can be transmitted to mobile devices via wireless networking technology to support the concept of tele-monitoring services based on IoT devices.