• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2237-2242
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• 2014

As Single households increases for reason of communication development, extending human life, there are many problems occuring all over the world. In order to solve this problem with an invasion of privacy and manintain a healthy life, this paper suggest non-contact type bio-signal measurement system using IR-Radar, displacement sensor and Pan-Tilt system. The proposed system can increse the distance of measured respiration from 1m to over 8m, which is comprised of two IR-Radar for location tracking, one displacement sensor for non-contact type bio-signal measurement and one stepping motor drive system. The proposed system is verified through experiments and were confirmed the possibility.

• Journal of electromagnetic engineering and science
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• v.10 no.4
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• pp.250-255
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• 2010

This paper presents a non-contact measurement method of vital signal by the use of multiple-input multiple-output (MIMO) bio-radar system, configured with two antennas that are separated by a certain distance. The direction of arrival (DOA) estimation algorithm for coherent sources was applied to detect vital signals coming from different spatial angles. The proposed MIMO bio-radar system was composed of two identical transceivers sharing single VCO with a PLL. In order to verify the performance of the system, the DOA estimation experiment was completed with respect to the human target at angles varying between $-50^{\circ}$ and $50^{\circ}$ where the bio-radar system was placed at distances (corresponding to 50 cm and 95 cm) in front of a human target. The proposed MIMO bio-radar system can successfully find the direction of a human target.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2013.10a
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• pp.845-845
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• 2013

• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.2
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• pp.27-34
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• 2013

Most of existing biomedical signal measurement devices measure and evaluate biomedical signal only in a single device. Also, even if the device is multi-functional, those biomedical signals can be measured by selection of the user. In this paper, we implemented wristband-style biomedical signal measurement device for u-healthcare system to solve the problem above. Implemented device uses 4 infrared sensors to measure the pulse, 2 electrodes to measure the skin conductivity, and 3-axis accelerometer to measure momentum. Also, we propose a communication packet frame for transmitting biomedical signal data to PC or mobile device, using Zigbee. Studies show that our device has the error rate of less than twice for pulse measurement, 85.6%, 84.7% reliability for momentum measurement, and the skin conductivity has changed according to the user's physical status.

• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.190-196
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• 2007

The purpose of this study is to develop a measurement system of cutter conditions for combine header diagnosis during rice harvesting. A load cell was installed at the locker-arm to measure load fluctuation and an acceleration senor was used to monitor vibration signal of cutter bar. The data were collected from a paddy field during harvesting. The tests were conducted with a normal cutter, a loosened cutter, a broken cutter, and a worn-out connecter pin at the field. The vibration signals converted by FFT (Fast Fourier Transformation), filtered, and normalized. The load data and peak values of vibration signals in four different frequency ranges were used to determine the cutting operation and the cutter conditions of combine. The multiple comparison tests showed that the load data and peak values of vibration signals were important to monitor the cutting operation and cutter conditions of combine header.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.317-325
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• 2008

The electrocardiogram (ECG) measurement system consists of I/O interface to input the ECG signals from two electrodes, FPGA (Field programmable gate arrays) module to process the signal conditioning, and real time module to control the system. The algorithms based on wavelet transform were developed to remove the noise of the ECG signals and to determine the QRS-waves. Triangular wave tests were conducted to determine the optimal factors of the wavelet filter by analyzing the SNRs (signal to noise ratios) and RMSEs (root mean square errors). The hybrid rule, soft method, and symlets of order 5 were selected as thresholding rule, thresholding method, and mother wavelet, respectively. The developed wavelet filter showed good performance to remove the noise of the triangular waves with 10.98 dB of SNR and 0.140 mV of RMSE. The ECG signals from a total of 6 subjects were measured at different measuring postures such as lying, sitting, and standing. The durations of QRS-waves, the amplitudes of R-waves, the intervals of RR-waves were analyzed by using the finite impulse response (FIR) filter and the developed wavelet filter. The wavelet filter showed good performance to determine the features of QRS-waves, but the FIR filter had some problems to detect the peaks of Q and S waves. The measuring postures affected accuracy and precision of the ECG signals. The noises of the ECG signals were increased due to the movement of the subject during measurement. The results showed that the wavelet filter was a useful tool to remove the noise of the ECG signals and to determine the features of the QRS-waves.

• Journal of the Korea Society of Computer and Information
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• v.16 no.1
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• pp.117-124
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• 2011

This study was realized the home network system for home care by bio-physical sensor system, to convey for the remote physical signal. The composition condition has four functions of displacement point for a Vision, Somatosensory, Vestibular and CNS that the basic measurement used to a Heart Rate, Temperature, Weight. Physical signal are decided 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 physical neuroceptor of sensory organ for the measurement such as a Vision, Somatosensory, Vestibular, CNS, BMI. There are to check a health care condition through a combination of physical organ with a posturography of a exercise. The service 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 the remote control health management system.

• International Journal of Vascular Biomedical Engineering
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• v.3 no.1
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• pp.6-13
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• 2005

Individual clinical significance of each layer of CCA (common carotid artery) has not been well studied. We intended to measure the intima thickness (IT), media thickness (MT), and intima-media thickness (IMT) of CCA separately and tried to analyze the clinical significance. One hundred fifty one consecutive patients (mean age: $57{\pm}15$ years; 77 males, 74 females) underwent CCA scanning using high-resolution ultrasound. The images were off-line analyzed using B-mode ultrasound image processing, devised for individual measurement of IT and MT as well as IMT. The mean coefficients of variation of new method measuring IT, MT, and IMT separately were 0.16% for IMT and 0.21% for both IT and MT. The IT (p < 0.01), MT (p < 0.01) as well as IMT (p < 0.001) of patients with atherosclerotic disease were significantly thicker than that of the patients without atherosclerotic disease. Patients with hypertension showed significantly thicker IT (p < 0.01), MT (p < 0.001), and IMT (p < 0.001) than that of the patients without hypertension. However, only IT was thicker in patients with smoking (p<0.01) than that of the patients without smoking.

• Journal of IKEEE
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• v.12 no.2
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• pp.87-94
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• 2008

Pelvic floor muscle is the main subsystem that maintains urinary continence. It is possible to diagnose the degree of the stress urinary incontinence(SUI) by evaluating the contraction pressure of the pelvic floor muscle. Bio-signal measurement system was developed to measure the contraction pressure. Diagnostic parameters were drawn out by analyzing the measured data. Statistical evaluations were done to classify the all subjects with five groups each has similar characteristics. SUI diagnostic algorithm was implemented to each group separately. The accuracy of the algorithm was about 78.9% and utility was confirmed by clinical trial.

• 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.