• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.138-141
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• 2006

Blood flow is one of vital signals related to human physiological information. Photoplethysmograph (PPG) has been used to measure indirectly heart rate, blood oxygen saturation ($SpO_2$), and so on. Because PPG signal is weak and sensitive to motion artifacts, it is very important to continuously obtain stable PPG signal during free movement. In this study, we applied the scaled Fourier linear combiner (SFLC) using both the adaptive filter and FLC to remove effectively the motion artifacts as well as background noise in the real time without additional signal correlated with motion from a accelerometer. The proposed method would be useful to reduce the movement and background noise which are not synchronized with heart rate.

• BMB Reports
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• v.51 no.3
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• pp.106-118
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• 2018

How the organ size is adjusted to the proper size during development and how organs know that they reach the original size during regeneration remain long-standing questions. Based on studies using multiple model organisms and approaches for over 20 years, a consensus has been established that the Hippo pathway plays crucial roles in controlling organ size and maintaining tissue homeostasis. Given the significance of these processes, the dysregulation of the Hippo pathway has also implicated various diseases, such as tissue degeneration and cancer. By regulating the downstream transcriptional coactivators YAP and TAZ, the Hippo pathway coordinates cell proliferation and apoptosis in response to a variety of signals including cell contact inhibition, polarity, mechanical sensation and soluble factors. Since the core components and their functions of the Hippo pathway are evolutionarily conserved, this pathway serves as a global regulator of organ size control. Therefore, further investigation of the regulatory mechanisms will provide physiological insights to better understand tissue homeostasis. In this review, the historical developments and current understandings of the regulatory mechanism of Hippo signaling pathway are discussed.

• BMB Reports
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• v.55 no.11
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• pp.519-527
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• 2022

Macrophage activation has long been implicated in a myriad of human pathophysiology, particularly in the context of the dysregulated capacities of an unleashing intracellular or/and extracellular inflammatory response. A growing number of studies have functionally coupled the macrophages' inflammatory capacities with dynamic metabolic reprogramming which occurs during activation, albeit the results have been mostly interpreted through classic metabolism point of view; macrophages take advantage of the rewired metabolism as a source of energy and for biosynthetic precursors. However, a specific subset of metabolic products, namely immune-modulatory metabolites, has recently emerged as significant regulatory signals which control inflammatory responses in macrophages and the relevant extracellular milieu. In this review, we introduce recently highlighted immuno-modulatory metabolites, with the aim of understanding their physiological and pathological relevance in the macrophage inflammatory response.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.107-113
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• 2002

We examined the psychophysiological effects of navigation in a virtual reality (VR). Subjects were exposed to the VR, and required to detect specific objects. Ten electrophysiological signals were recorded before, during, and after navigation in the VR. Six questionnaires on the VR experience were acquired from 45 healthy subjects. There were significant changes between the VR period and the pre-VR control period in several psychophysiological measurements. During the VR period, eye blink, skin conductance level, and alpha frequency of EEG were decreased but gamma wave were increased. Physiological changes associated with cybersickness included increased heart rate, eye blink, skin conductance response, and gamma wave and decreased photoplethysmogram and skin temperature. These results suggest an attentional change during VR navigation and activation of the autonomic nervous system for cybersickness. These findings would enhance our understanding for the psychophysiological changes during VR navigation and cybersickness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1606-1616
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• 2011

The blood pressure measuring equipment, which is being supplied and used most widely by being recognized convenience and accuracy now generally, is oscillometric blood pressure monitor. However, a change in blood pressure is basically influenced by diverse elements such as each individual's physiological status and physical condition. Thus, the measurement of blood pressure, which used single element called oscillation in blood pressure of being conveyed to cuff, is not considered on physiological elements such as cardiovascular system status and blood vessel stiffness index, and on external elements, thereby being quite in error. Accordingly, this study detected diverse bio-signals and body informations in each individual as the measurement subject such as ECG, PPG, and Korotkoff Sound in order to enhance convenience and accuracy of measuring blood pressure in the complex measurement equipment, thereby having extracted regression method for compensation in error of oscillometric blood pressure measurement on the wrist, and having improved accuracy of measuring blood pressure. To verify a method of improving accuracy, the blood pressure value in each of SBP, DBP, MAP was acquired through 4-stage experimental procedure targeting totally 51 subjects. Prior to experiment, the subjects were divided into two groups such as the experimental group for extracting regression method and the control group for verifying regression method. Its error was analyzed by comparing the reference blood pressure value, which was obtained through the auscultatory method, and the oscillometric blood pressure value on the wrist. To reduce the detected error, the blood pressure compensation regression method was calculated through multiple linear regression analysis on elements of blood pressure, individual body information, PTT, HR, K-Sound PSD change. Verification was carried out on improving significance and accuracy by applying the regression method to the data of control group. In the experimental results, as a result of confirming error on the reference blood pressure value in SBP, DBP, and MAP, which were acquired through applying regression method, the results of $-0.47{\pm}7.45$ mmHg, $-0.23{\pm}7.13$ mmHg, $0.06{\pm}6.39$ mmHg could be obtained. This is not only the numerical value of satisfying the sphygmomanometer reference of AAMI, but also shows the lower result than the numerical value in SBP : $-2.5{\pm}12.2$ mmHg, DBP : $-7.5{\pm}8.4$ mmHg, which is the mean error in the experimental results of Brram's research for verifying accuracy of Omron RX-M, which shows relatively high accuracy among wrist sphygmomanometers. Thus, the blood pressure compensation could be confirmed to be made within significant level.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.95-105
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• 2009

Traffic accidents on highways are likely to happen when there is an imbalance in the complex relationships among key elements such as road geometries, driver related factors, and mechanical performances. The Demand-Effort Model (DEM), which evaluates highway safety, can be explained by the imbalance, which occurs when the level of demand of the driver's attention to the road environment exceeds that of the response from the driver. This study suggests a new model that improves the reliability of the current DEM through the reinterpretation on the physiological signals with the help of the Neural Network Model (NNM). The data were collected from 149 subjects, who drove a test vehicle on the Yongdong, Honam, and Seohaean Expressways in Korea. Three important results could be drawn from the recursive tests as follows; (1) Only 5 out of 10 parameters on the physiological signals which are currently used were proven to be meaningful through the Normality Test, Cluster Analysis, and Mann-Whitney Analysis. (2) The revised DEM, which internally uses the NNM, showed more reliable results than existing DEM. Group 1, which is based on the new DEM showed 80.0% of accuracy in measuring the level of driver's efforts, however, that of Group 2 based on the current DEM was 74.3%. (3) Field tests on the Honam Expressway showed lower 'type II error' with the new DEM (40.5%) than the old DEM (58.8%). The DEM is designed as a quick and easy way to determine highway safety prior to the minute road safety audit (RSA) by a professional audit team. Then a new DEM, which is based on the NNM, needs to be considered since it showed higher reliability and lower error.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.207-216
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• 2013

The aim of this study is to design a classifier for sleep stage analysis and select important feature set which shows sleep stage well based on physiological signals during sleep. Sleep has a significant effect on the quality of human life. When people undergo lack of sleep or sleep-related disease, they are likely to reduced concentration and cognitive impairment affects, etc. Therefore, there are a lot of research to analyze sleep stage. In this study, after acquisition physiological signals during sleep, we do pre-processing such as filtering for extracting features. The features are used input for the new combination algorithm using genetic algorithm(GA) and neural networks(NN). The algorithm selects features which have high weights to classify sleep stage. As the result of this study, accuracy of the algorithm is up to 90.26% with electroencephalography(EEG) signal and electrocardiography(ECG) signal, and selecting features are alpha and delta frequency band power of EEG signal and standard deviation of all normal RR intervals(SDNN) of ECG signal. We checked the selected features are well shown that they have important information to classify sleep stage as doing repeating the algorithm. This research could use for not only diagnose disease related to sleep but also make a guideline of sleep stage analysis.

• Korean Journal of Cognitive Science
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• v.16 no.3
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• pp.189-197
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• 2005

In this study, changes in performance of 2-back task, blood oxygen saturation and heart rate due to $40\%$ concentration oxygen supply were observed. Five male $(25.8\pm1.3)$ and five female $(23.0\pm1.0)$ college students were nked to perform 2-bark task during two types of oxygen (concentration $21\%,\;40\%$) administration. The experimental sequence consisted of Rest1(1 min.), 0-back Task (1 min.), 2-bark Task (2 min.), and Rest2 (4 min.) and the physiological signals such as blood oxygen saturation and heart rate were measured throughout the stages. The experimental result showed that the performance increased significantly at $40\%'s$ concentration of oxygen rather than $21\%'s$, which shows oxygen supply has positive influence on cognitive performance. When $40\%$ concentration oxygen is supplied, the oxygen saturation in the blood increased and heart rate was decreased significantly comparing to $21\%$. It is Suggested that $40\%$ oxygen can stimulate brain activation bY increasing actual blood oxygen concentration in the process of cognitive performance, and hyperoxia makes heart rate decrease.

• Science of Emotion and Sensibility
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• v.11 no.1
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• pp.105-112
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• 2008

This study investigated the effect of 40% oxygen administration on the addition task performance in three levels of difficulties and physiological signals. Ten male and female college students were selected as the subjects for this study. The experiment consisted of two runs: one was a addition task, with normal air (21% oxygen) administered and the other was with hyperoxic air (40% oxygen) administered. The experimental sequence in each run consisted of Rest1 (3 min), Task1 (1 min, one digit addition task), Task2 (1 min, two digit addition task), Task3 (1 min, three digit addition task), and Rest2 (4 min). Blood oxygen saturation and heart rate were measured throughout the five phases. The accuracy rates of the addition task were enhanced with 40% oxygen administration compared to 21% oxygen. Difference in the accuracy rates grew higher with the rise of difficulty. When 40% concentration oxygen is supplied, blood oxygen saturation increased and heart rate was decreased comparing to 21%. This study showed that the supply of high concentration oxygen increases blood oxygen saturation, which in turns accelerates brain activation resulting from cognitive process and enhances arithmetic abilities. Particularly when difficulty is high, demand for oxygen increases and, as a result, the effect of high concentration oxygen becomes more significant.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.101-116
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• 2011

Current researches on emotion detection classify emotions by using the information from facial, vocal, and bodily expressions, or physiological responses. This study was to review three representative emotion recognition methods, which were based on psychological theory of emotion. Firstly, literature review on the emotion recognition methods based on facial expressions was done. These studies were supported by Darwin's theory. Secondly, review on the emotion recognition methods based on changes in physiology was conducted. These researches were relied on James' theory. Lastly, a review on the emotion recognition was conducted on the basis of multimodality(i.e., combination of signals from face, dialogue, posture, or peripheral nervous system). These studies were supported by both Darwin's and James' theories. In each part, research findings was examined as well as theoretical backgrounds which each method was relied on. This review proposed a need for an integrated model of emotion recognition methods to evolve the way of emotion recognition. The integrated model suggests that emotion recognition methods are needed to include other physiological signals such as brain responses or face temperature. Also, the integrated model proposed that emotion recognition methods are needed to be based on multidimensional model and take consideration of cognitive appraisal factors during emotional experience.