• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.145-152
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• 2010

Most wearable system for mobile healthcare applications consists of three parts. The first part is the sensing elements based on bio-signal, the second is the circuit module for control, data acquisition and wireless communication and control and the third is garment with a built-in electrodes and circuits. The existing healthcare garment systems have to find a solution to signal-wire and uncomfortable and inappropriate electrode to long-term attachment. Even if the wireless communication is used for healthcare garment system, the interface between sensors and circuits have to use wires. To solve these problems, this paper use electrode using PEDOT coated PVDF nanoweb for ECG signal and PVDF film sensor for respiratory signal. And, we constructed garment network using digital yarn of 10um, and transmitted ECG and respiratory signal to mobile phone through the integrated circuit with bluetooth called station To evaluate feasibility of the proposed mobile healthcare garment system, we experimented with transmission and measurement of ECG and respiratory signal using nanoweb electrode and digital yarn. We got a successful result without noise and attenuation.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.2
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• pp.56-62
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• 2015

In this study, we implemented an unconstraint ECG monitoring system on a chair. Nowadays, modern people spend most of their time sitting on the chair. Therefore, it is necessary to have an unconstraint ECG monitoring system that can be used for a long time. The implemented system can perform measurement even with clothes on and it has great advantage on motion artifacts. A pair of unconstraint electrodes are placed on the back of the chair. Amplifier and filters are designed to remove motion artifacts, The baseline noise and power line noise are filtered and very low level of bio-signal is amplified to give a final measurement. Control unit and wireless transmission unit are implemented. Analog signal is converted into digital signal and transmits biological signal to the PC and the smart phone. Therefore continuous ECG monitoring in daily life is made possible. A comparison experiment between Ag / AgCl electrode and unconstraint electrode is conducted to evaluate the performance of the implemented system. As a result, we confirm our unconstraint system can be used for daily life ECG monitoring.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.2
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• pp.191-199
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• 2008

In this paper, we present a performance analysis and design and implementation results of a 2.4 GHz bio-radar system that can detect human heartbeat and respiration signals. In order to design a 2.4 GHz bio-radar system qualitatively, we investigate the electromagnetic properties of human tissues and calculate the target SNR of demodulation output with respect to distance. The target SNR is defined by the 90 % success ratio for detecting heartbeat signal. With this target SNR value, the performance and link budget of the bio-radar system is simulated using MATLAB. Using this link budget results, the direct conversion receiver is designed and Implemented in 4 layer printed circuit board(PCB). With output power of 0 dBm and 5 Hz bandwidth, 80 % success ratio of 50 cm is measured. Measurement results show a good agreement with simulation results.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.381-391
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• 2017

Biometric technology is a technology for authenticating a user using the physical or behavioral features of the inherent characteristics of the individual. With the necessity and efficiency of the technology in the fields of finance, security, access control, medical welfare, inspection, and entertainment, the service range has been expanding. Biometrics using biometric information such as fingerprints and faces have been exposed to counterfeit and disguised threats and become a social problem. Recent studies using a bio-signal from the inside of the body other than the bio-information of the external body are being developed. This paper analyzes the recent research and technology of biometric systems using bio-signals, ECG, heart sounds, EEG, and EMG to present the skills needed for the development direction. In the future, utilizing the deep learning to build and analyze database to manage bio-signal based big data for the complex condition of individuals, biometrics technologies suitable for real time environment are expected to be researched.

• Journal of the Ergonomics Society of Korea
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• v.27 no.4
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• pp.95-101
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• 2008

This research is to develop PPG filtering method for respiration measurement in U-Health Care system. Respiration rate was determined by filtering PPG and analyzing its spectrum. Optimal filter of PPG has been selected to get respiration by testing 120 sets of experiment data using 700 filtering cases. As a result, 2nd order Bessel-filter that used band-pass cutoff frequency at 0.175~0.4Hz with second order was good at developing respiration signal. Respiration signal in time domain could be continuously analyzed by converting frequency domain using spectrum analysis. 24 seconds has been found to be optimal time duration of collecting PPG data for determining respiration. Therefore, this study was successful of getting not only heart activity but also respiration by only PPG. Minimal invasive measurement obtaining multi-bio information by one sensor can be expected to apply to U-Health Care and human computer interaction.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.31-37
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• 2010

This study was developed the home network system for the home stay care by bio-sensor system to translate the physical signal algorithm. The composition algorithm has five functions for a input function, frequency variable, displacement point input function, axial Variable, axial Sway Displacement to search a max and min point with adjustment of 0.01 unit in the reference level. There were checked physical condition of body balance to compounded a measurement such as a heart rate, temperature, weight. The algorithm of home network system can be used to support health care management system through health assistants in health care center and central health care system. It was expected to monitor a physical parameter for health management system.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.103-109
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• 2017

In order to apply the patient monitoring system to the hospital field, it is necessary to be able to measure and analysis data the major bio-signals that are basically covered by the existing patient monitoring system. We have implemented a wearable device and the patient monitoring system for measuring ECG and oxygen saturation. The implemented system transmits the measured bio-signal to the server on the nursing station via Bluetooth. It is represented by graph waveforms and numerical values that can be checked by the medical staff in the patient monitoring system. The validity of this system is verified by comparing the data collected through the designed system with the data obtained from the conventional equipment.

• Progress in Medical Physics
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• v.5 no.2
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• pp.35-43
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• 1994

Electromagnetic wave may induce effect and damage on the bio-body, either by electric fields of magnetic fields. We measure electrophysiological changs in rabbit's brain exposed to 2.45GHz micro wave(power density 40mW/cm$^2$) which distance 30cm from the source. In order to process the bio-electrical signal (EEG), used pre-amplifier module with self-made and Digtal analyzer computer system. Spectal analysis of the EEG showed variable power in the frequency range(1～30Hz) through each exposure time(10min, 20min, 30min) before and after. In effectively measured by the bio-electrical signal processing and can found threshold of minmal permissible exposure and lethal exposure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.859-864
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• 2022

Drowsy driving, one of the biggest causes of traffic accidents every year, is accompanied by various factors. As a general method to check whether or not there is drowsiness, a method of identifying a driver's expression and driving pattern, and a method of analyzing bio-signals are being studied. This paper proposes a driver fatigue detection system using deep learning technology and bio-signal measurement technology. As the first step in the proposed method, deep learning is used to detect the driver's eye shape, yawning presence, and body movement to detect drowsiness. In the second stage, it was designed to increase the accuracy of the system by identifying the driver's fatigue state using the pulse wave signal and body temperature. As a result of the experiment, it was possible to reliably determine the driver's drowsiness and fatigue in real-time images.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.109-114
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• 2013

The biological active points (BAP) are known as low resistance spots or good electro-permeable points. In this paper, a new method for BAP detection using the bio-impedance measurement system based on the adaptive frequency tracking filter (AFTF) and the transition event detector is presented. Also, the microcontroller process continuous time demodulation of the modulated signal by multi frequency components using the AFTF. The transition event detector based on the phase space method is applied about each frequency using the BAP equivalent model which is proposed.