• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2702-2703
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• 2002

본 연구에서는 종래의 심박출량 및 일회 심박동량 측정장치를 휴대용 시스템으로 구현하기 위한 회로 설계방법을 연구하였다. 휴대용 시스템의 설계를 위한 아날로그 부분은 인체 안전을 위한 아이솔레이션 증폭기, 변복조기, 0.1Hz 고역통과 필터 및 잡음제거 회로로 구성되며, 연속 심박출량 모니터링 및 연산을 위한 디지탈 부분은 TMS32030C를 이용한 회로로 구성이 된다. 또한 기존의 방법에서의 문제점을 개선하기 위해 연속 심박출량 연산을 위한 새로운 알고리듬을 제안하였다. 제안된 방법은 앙상블 평균시에 기존의 심전도 R피이크 점을 기준으로 하지 않고, 임피던스 신호의 dZ/dt 최대점을 이용하는 방법을 적용하였다. 제안한 심박출량 신호처리 알고리듬을 이용하여 측정된 임피던스 신호를 분석한 결과 최대 25.5 %까지 개선됨을 확인하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.179-182
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• 2006

현재 감정을 인식할 수 있는 방법으로는 음성, 뇌파, 심박, 표정 등 많은 방법들이 존재한다. 본 논문은 이러한 방법 중 음성 신호를 이용한 방법으로써 특징들은 크게 피치, 에너지, 포만트 3가지 특징 점을 고려하였으며 이렇게 다양한 특징들을 사용하는 이유는 아직 획기적인 특징점이 정립되지 않았기 때문이며 이러한 선택의 문제를 해결하기 위해 본 논문에서는 특징 선택 방법 중 Multi Feature Selection(MFS) 방법을 사용하였으며 학습 알고리즘은 Self Organizing Map 알고리즘을 이용하여 음성 신호의 감정 특징 패턴을 분류하는 방법을 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.65-74
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• 2010

We propose a system that automatically recognizes the tense or relaxed condition of scrolling-shooting game subject that plays. Existing study compares the changed values of source of stimulation to the player by suggesting the source, and thus involves limitation in automatic classification. This study applies SOM of unsupervised learning for automatic classification and recognition of player's condition change. Application of SOM for automatic recognition of tense and relaxed condition is composed of two steps. First, ECG measurement and analysis, is to extract characteristic vector through HRV analysis by measuring ECG after having the player play the game. Secondly, SOM learning and recognition, is to classify and recognize the tense and relaxed conditions of player through SOM learning of the input vectors of heart beat signals that the characteristic extracted. Experiment results are divided into three groups. The first is HRV frequency change and the second the SOM learning results of heart beat signal. The third is the analysis of match rate to identify SOM learning performance. As a result of matching the LF/HF ratio of HRV frequency analysis to the distance of winner neuron of SOM based on 1.5, a match rate of 72% performance in average was shown.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.55-64
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• 2019

Stress is accompanied by changes in the responses of the autonomic nervous system, and the heart rate variability (HRV) index is a quantitative marker that reflects autonomic responses induced by stressors. In this study, we observed changes in the autonomic responses induced by combinations of 30% oxygen administration and color light for stress relaxation. In all, 42 participants produced stress symptoms over the preceding two weeks, as rated on the stress response scale. After stress assessment, they were exposed to three therapeutic conditions, and electrocardiogram (ECG) signals were recorded before, during, and after therapy. The three therapy conditions consisted of only 30% oxygen administration with white light, a combination of 30% oxygen and orange light, and a combination of 30% oxygen and blue light. The HRV indices extracted from ECG signals were heart rate (HR), the standard deviation of the RR interval (SDNN), the mean square root of consecutive RR interval difference values (RMSSD), the low frequency component of HRV (LF), the high frequency component (HF), and the LF/HF ratio. These indicators were used to compare mean values before and after therapy. The results showed that HR and the LF/HF ratio were significantly lower after therapy than before it. In particular, the condition with 30% oxygen and blue light yielded significantly greater RMSSD and HF increases, as well as decreases in LF/HF ratio than in other two conditions. Our results suggest that therapy with 30% oxygen and blue light is the most effective for the relaxation of stress, which implies autonomic balance by parasympathetic activation.

• Journal of Advanced Navigation Technology
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• v.13 no.6
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• pp.926-932
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• 2009

The whole-body massager among healthcare devices is under being popularized in a large scale as times goes by. It is critical to measure, analyze and judge the stress relaxsation trend from HRV signal using PPG in case of massager operation with such relaxsation device for removing stress of human being. There may be artifact in HRV measured signal because the measured object is under shaking with that massager in this case. We present the methodology to remove such artifact from those measured HRV signal, and then measure and analyze the desired HRV successfully in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.819-821
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• 2014

This study is proposed the design method of tag to measure biomedical signal for interfacing with smart phone. The measurable physiological signals are ECG and PPG. On the smart phone by using the measured signals, we have designed the tag that can extract parameters such as heart rate, heart rate distribution, mean blood pressure, arterial stiffness, autonomic nervous balance. By using the estimated medical informations from this tag, One's health status will be able to manage one.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.898-902
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• 2018

A novel heart beat interval estimation algorithm is presented based on parabola approximation method. This paper presented a two-step processing scheme; a first stage is finding R-peak in the Electrocardiogram (ECG) by Shannon energy envelope estimator and a secondary stage is computing the interpolated peak location by parabola approximation. Experimental results show that the proposed algorithm performs better than with the previous method using low sampled ECG signals.

• Journal of Broadcast Engineering
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• v.18 no.4
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• pp.543-549
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• 2013

Motion artifacts of central and autonomic nervous system signals degrades the performance of the bio-signal based human factor analysis. Firstly, we propose a defining method of motion artifact section by analyzing successive image frames. Motion artifact section is defined when the amount of motion is greater than the pre-defined threshold. In here, the amount of motion is estimated by first derivation of image frames at temporal domain. Secondly, we propose another defining method of motion artifact section through designing 2D Gaussian probability density function model by analyzing feature vectors of one cycle of signal such as length and amplitude. The defined motion artifact sections are interpolated on the basis of 1D Gaussian function. At result of applying the method into photoplethysmography signal, we confirmed that the calculated heartbeat rate from the restored photoplethysmography came up to the one from electrocardiography. Also, we found that the video based method generated relatively more false acceptance of motion artifact section and the probability density function based method generated relatively more false rejection of motion artifact section.

• Science of Emotion and Sensibility
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• v.7 no.3
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• pp.27-35
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• 2004

This study has investigated a psychological status of optimal and pleasant driving condition by measuring various physiological signals using SCR(skin conductance response), PPG(peripheral plethysmograph), SKT(skin temperature) and HR(heart rate). The physiological response was measured during various simulated driving conditions. We developed a hardware and algorithm to measure and analyze the physiological response. The physiological signals has reflected the level of driver's tension or relaxation as well as the heart rate. The emotional responses of drivers were also measured and analyzed in this experiment. The result of the study can be used to design a system to enhance the driver's emotional satisfaction as well as to monitor the driver's safety and health condition.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.90-94
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• 2002

이전연구에서 가상현실에 몰입하는 동안 넓은 시야 (Field of view: 150$^{\circ}$)와 빠른 운행속도 (70 km/sec)가 사이버멀미를 심화시킨다는 결과를 얻었다: 피험자의 90%가 좁은 시야 (50$^{\circ}$)와 느린 운행속도 (30 km/sec)에서 사이버멀미 증상이 적었다. 본 실험에서는 피험자가 생리적인 동요를 경험할 때마다 바이오피드백 방법을 사용해서 사이버멀미 감소 가상환경 (cybersickness alleviating virtual environment, CAVE)을 제시한 후, 그 효과를 관찰하였다. 피부전도도, 말초체온, 말초혈류량, 심박률, 눈 깜박임, 뇌전위의 변수들을 입력으로 하는 인공신경망으로 구성된 실시간 멀미 탐지 시스템과 CAVE-제시 피드백 시스템을 구축하였다. 이 시스템은 생리적 측정치들이 사이버멀미의 출현을 신호할 때마다 피드백 출력으로 좁은 화면과 감소된 운행속도를 일시적으로 제공했다. 36명의 피험자를 대상으로 SSQ (simulator sickness questionnaires)와 자기보고를 이용하여 사이버멀미의 빈도와 심각도를 조사하였다. 모든 피험자는 한달 간격으로 CAVE 조건과 non-CAVE 조건에서 두 번 가상현실을 경험하였다. 사이버멀미의 빈도와 심각도는 non-CAVE 조건보다 CAVE 조건에서 유의미하게 감소하였다. 즉, 전기생리학적 특징들에 기반한 인공신경망에 의해 제공된 좁은 시야와 느린 운행의 가상환경은 사이버멀미 증상들을 의미있게 감소시켰다. 이러한 결과들은 생체신호 피드백 시스템을 이용하여 인간 친화적 가상환경을 구축할 수 있는 가능성을 보인 것이다.