• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.13-18
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• 2008

In these days, wearable and mobile physiological sensing devices have been studied according to the increasing interest on the healthy and wellbeing life. However, these sensing devices display just the sensing results, such as heart rate, skin temperature, and its daily records. In this work, we propose the novel type of mobile physiological sensing device which deliver the user comfortable grabbing feeling. In addition, we indicate the personalized physiological signal analysis result which be concluded by the different analysis results according to the person to person. In order to verify this sensing device, we collect the data set from 4 different users during a week and measure the physiological signal such as heart rate, hand temperature, and skin conductance. And we observe the result how the analysis results shows the difference between the users. We expect that this work can be applied in the various health care applications in the near future.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1350-1357
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• 2012

Medical system for personal health management recently changes its paradigm from hospital service to self home care based on ubiquitous technology for healthcare anywhere at any time. The present study developed a wireless bio-signal measurement system for patients to self manage pulmonary disease and benign prostate hyperplasia(BPH), both of which are chronic diseases with increasing frequency in modern society. Velocity-type respiratory air flow transducer adapted to develop respiratory module for pulmonary disease management was simplified in structure to measure uni-directional flow since most important diagnostic parameters are evaluated on the expiratory flow signal only. Standard weight measurement technique was introduced to obtain urinary flow signal for BPH management. Three load cell signals were acquired for averaging to minimize noise, followed by accuracy evaluation. Transmission and receiver modules were also developed with user program for wireless communication. Averaged relative errors were 2.05 and 1.02% for respiratory volume and maximal flow rate, respectively, and the relative error was 2.17% for urinary volume, demonstrating that both modules enabled very accurate measurements. Wireless communication distance was verified within 15m, long enough for home care application. The present system allows the user to select a necessary measurement module on a particular health demand and to immediately provide the self-test results, thus better quality health care would be possible.

• Science of Emotion and Sensibility
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• v.23 no.3
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• pp.3-10
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• 2020

This study is aimed at investigating drivers' reactions to yellow signal dilemma situations as a result of the existing signal system, and developing a new signal system. A driver-centered coping model was developed through bio-signal analysis. The driver's physiological response in the existing signal system was observed, and the signal system was developed by applying intersection road driving conditions using a car graphic simulator. Participants were classified into a control group (existing signal system) and an experimental group for a new yellow signal system (new signal system). Based on the results, the emergence of parasympathetic nerves was higher in the experimental group than in the control group, where a statistically significant difference was observed (p < 0.05). The newly developed signal system appeared to cause tension among drivers; however, the sympathetic to parasympathetic nerve ratio was 6: 4, which could be interpreted as an ideal balance. We conclude that drivers can drive more stably if the coping signal system developed in this study is applied to the traffic system.

• Journal of the Korea society of information convergence
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• v.6 no.2
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• pp.45-49
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• 2013

Electrocardiogram(ECG) signal noise as well as conducting other bio-signal measurement were generated. It was intened to enhance the accuracy of cadiac disease diagnosis with removing signal white-noise. Sampling signal was made with generating white-noise. The noise were removed using wavelet transforms and thresholding. Removed noise were compared numerical using SNR(signal to noise ratio). The results compared SNR showed that SURE method was 5.931, 4.9301 in 3, 5dB noise, uninversal was 3.6590, 1.9698 in 7, 9dB noise. De-noising by Thresholding removed noise effectively. ECG signal is expected to improve the accuracy of cadiac desease dianosis.

• Journal of electromagnetic engineering and science
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• v.12 no.4
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• pp.234-239
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• 2012

This paper presents a compact K-band Doppler radar sensor for human vital signal detection that uses a radar configuration with only single coupler. The proposed radar front-end configuration can reduce the chip size and the additional RF power loss. The radar front-end IC is composed of a Lange coupler, VCO, and single balanced mixer. The oscillation frequency of the VCO is from 27.3 to 27.8 GHz. The phase noise of the VCO is -91.2 dBc/Hz at a 1 MHz offset frequency, and the output power is -4.8 dBm. The conversion gain of the mixer is about 11 dB. The chip size is $0.89{\times}1.47mm^2$. The compact Ka-band Doppler radar system was developed in order to demonstrate remote human vital signal detection. The radar system consists of a Ka-band Doppler radar module with a $2{\times}2$ patch array antenna, baseband signal conditioning block, DAQ system, and signal processing program. The front-end module size is $2.5{\times}2.5cm^2$. The proposed radar sensor can properly capture a human heartbeat and respiration rate at the distance of 50 cm.

• Journal of Korean Clinical Health Science
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• v.4 no.4
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• pp.756-761
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• 2016

Purpose. Noise occurs at measuring Electoretinogram(ERG) signals as the other bio-signal measurement. It is compared the denoising performance according to the mother function of wavelet transforms. Methods. The ERG signal that generated power supply noise and white noise was used as a sampling signal. The noise of ERG signal was filtered by using haar, db7, bior mother function. The filtering performance of each mother functions was compared using Fourier transform spectrum and SNR(signal to noise ratio). Results. In the haar functioin, the result of the Fourier transform spectrum was that the power supply noise is removed and the white noise performance is not good. The SNR was 27.0404. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is good. The SNR was 35.1729. In the db7 function, the results of Fourier transform spectrum was that the power supply noise is removed and the white noise performance is the bset. The SNR was 35.4445. Conclusions. The db7, bior function was good results in power supply noise and white noise filtered. The bior function is suitable for filtering noise of the ERG signal.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.2
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• pp.105-110
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• 2008

Human being recognizes emotion fusing information of the other speech signal, expression, gesture and bio-signal. Computer needs technologies that being recognized as human do using combined information. In this paper, we recognized five emotions (normal, happiness, anger, surprise, sadness) through speech signal and facial image, and we propose to method that fusing into emotion for emotion recognition result is applying to multimodal method. Speech signal and facial image does emotion recognition using Principal Component Analysis (PCA) method. And multimodal is fusing into emotion result applying fuzzy membership function. With our experiments, our average emotion recognition rate was 63% by using speech signals, and was 53.4% by using facial images. That is, we know that speech signal offers a better emotion recognition rate than the facial image. We proposed decision fusion method using S-type membership function to heighten the emotion recognition rate. Result of emotion recognition through proposed method, average recognized rate is 70.4%. We could know that decision fusion method offers a better emotion recognition rate than the facial image or speech signal.

• 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

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.104-105
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• 2010

• 대한생식의학회:학술대회논문집
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• 2005.11a
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• pp.100-100
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• 2005