• 기본간호학회지
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• 제13권2호
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• pp.275-284
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• 2006

Purpose: The purpose of this study was to analyze tile trends in physiological variables in CAT research in nursing in Korea. Method: Of studies published in Korea between January, 2000 and December, 2005, 227 studies were analyzed according to the criteria of type, theme, and patterns in physiological variables related to CAT. Results: There were 72 articles on CAT research in which physiological variables were examined. The most frequently researched type of CAT was massage and in particular, foot massage. The most frequently used physiological variables in CAT research were blood pressure, pulse, and body temperature. Patients with high blood pressure were the most frequent subjects for CAT research. As to the effect of physiological variable by CAT type, foot massage showed a decline in blood pressure in all six research studies involving patients with high blood pressure. Conclusion: There is a need to describe accurately the mechanism by which CAT affects physiological variables. There is also a need for repetitive analysis to verify the effect, and meta-analysis for the effect on physiological variables according to type of CAT.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.13-18
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• 2008

최근 건강 관리에 대한 관심이 증가하면서 착용형 생체 신호 센서, 재택형 무구속계측 센서에 관한 연구가 활발하게 진행되고 있다. 그러나, 측정 기술의 발전과 달리 측정결과를 제공하는 단계에서는 심장 박동수, 체온 등의 값을 단일된 임계치 기반으로 판단하며, 분석된 결과가 사용자에게 어떤 의미를 주는지에 대한 해석은 제공하지 않고 있다. 따라서 본 논문에서는 사용하기 편한 돌 형태의 휴대형 생체신호 측정센서를 기반으로 사용자 별로 적합한 생체신호 해석 방법을 제안한다. 개인화된 생체 신호 해석을 위해 1 주일간 사용자의 시간대별 데이터를 획득하고 사용자 별 특성에 따라 모델링을 한 후, 모델에 기반하여 사용자에게 맞는 생체 신호 범위를 정하고 이를 판단하는 근거로 활용한다, 센서는 기존의 착용형 생체 신호 센서 및 이를 이용한 응용에 폭넓게 사용될 수 있다.

• ETRI Journal
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• 제37권6호
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• pp.1231-1241
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• 2015

In this study, we investigate the relationship between emotions and the physiological responses, with emotion recognition, using the proposed fuzzy information granulation-based neural network (FIGNN) for boredom, pain, and surprise emotions. For an analysis of the physiological responses, three emotions are induced through emotional stimuli, and the physiological signals are obtained from the evoked emotions. To recognize the emotions, we design an FIGNN recognizer and deal with the feature selection through an analysis of the physiological signals. The proposed method is accomplished in premise, consequence, and aggregation design phases. The premise phase takes information granulation using fuzzy c-means clustering, the consequence phase adopts a polynomial function, and the aggregation phase resorts to a general fuzzy inference. Experiments show that a suitable methodology and a substantial reduction of the feature space can be accomplished, and that the proposed FIGNN has a high recognition accuracy for the three emotions using physiological signals.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.173-177
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• 2009

일상생활에서 활용 가능한 다양한 종류의 생체 신호 획득 및 분석 방법이 연구되고 있다. 기존의 생체 신호 분석 방법은 표준화된 임계치를 사용하여 해석한 결과를 제공하며 신호 측정 당시의 상황이 고려되지 않아 잡음 혹은 외부 환경의 영향을 받기 쉬운 단점이 있다. 본 논문에서는 생체 신호뿐만 아니라 기타 정황정보를 기반으로 하여 개인화된 신호를 분석하기 위한 모델(Personalized Decision Making method, PDM)을 제안한다. 개인화된 신호 해석 모델은 사용자의 맥락 정보, 사용자의 맥락 정보, 사용자의 나이, 성별, 현재의 몸 및 정신 상태, 음식 및 카페인의 섭취 여부, 측정 시간 및 측정 요일 등을 기반으로 각 맥락 간의 연관 관계를 나타내고, 이상적인 사용자의 생체 신호 예측치를 베이즈 정리를 기반으로 획득한다. 개인화된 해석 모델(ACM)을 통해 표준 임계치를 적용한 해석에 비해 인식의 정확도를 높일 수 있으며, 다양한 측정시의 조건을 알면 현재 사용자의 건강상태를 개인화된 분석과 유사한 정확도로 예측이 가능하다. 제안한 방법은 현재 관측된 관측치의 분포를 모르더라도, 현재 사용자의 상태를 맥락정보를 기반으로 하여 예측할 수 있으므로, 일반적인 데이터 모델을 기반으로 개개인에 맞는 얼굴 표정을 인식하는 연구 등에 활용이 가능하다.

• International Journal of Contents
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• 제10권2호
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• pp.47-58
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• 2014

Physiological signals provide important clues in the diagnosis and prediction of disease. Analyzing these signals is important in health and medicine. In particular, data preprocessing for physiological signal analysis is a vital issue because missing values, noise, and outliers may degrade the analysis performance. In this paper, we propose PhysioCover, a system that can recover missing values of physiological signals that were monitored in real time. PhysioCover integrates a gradual method and EM-based Principle Component Analysis (PCA). This approach can (1) more readily recover long- and short-term missing data than existing methods, such as traditional EM-based PCA, linear interpolation, 5-average and Missing Value Singular Value Decomposition (MSVD), (2) more effectively detect hidden variables than PCA and Independent component analysis (ICA), and (3) offer fast computation time through real-time processing. Experimental results with the physiological data of an intensive care unit show that the proposed method assigns more accurate missing values than previous methods.

• 대한인간공학회지
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• 제31권2호
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• 한국운동역학회지
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• 제20권3호
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• pp.303-310
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• 2010

The purpose of this study was (a)to compare electromyographic (EMG) activities and physiological variables on the development of fatigue induced by ergometer test, (b)to determine investigate the differences in the stage of fatigue between the electromyographic characteristics and physiological variables. Nine male university students who have no musculoskeletal disorder were recruited as the subjects. The electromyographic characteristics(peak IEMG, average IEMG, median frequency, mean edge frequency) and physiological variables(HR, RPE, blood lactate) were determined for each stage(15, 30, 45, 60 minutes, all out). For each dependent variable, one-way analysis of variance(ANOVA) with repeated measures and correlation analysis were performed to test if significant difference existed(p<.05). The results showed that peak IEMG, average IEMG from low extremity and physiological variables were significantly increased during the all-out stage. EMG parameters in VL, VM show significantly correlation with physiological variables during whole stages. This indicated that IEMG values may be proper parameters to determine muscle fatigue rather than physiological variables.

• Journal of Chest Surgery
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• 제10권2호
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• pp.274-280
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• 1977

As a major cause for postoperative hypoxia, the importance of increased physiological shunting is increasingly emphasized. This study is a review and analysis of postoperative physiological shunting following open heart surgery with the aid of extracorporeal circulation. Sixteen patients were selected from among 21 patients who underwent elective open heart surgery at the Department of Thoracic and Cardiovascular Surgery, Kyungpook National University, School of Medicine, from December, 1975 to September, 1977. The results were as follows: 1. The degree of postoperative physiological shunt was progressively increased from 18.8% mean value one hour after surgery to 22.7% mean value, reaching a peak on the second postoperative days. 2. For up to one week, large physiological shunt[15%] was persisted in one patient. 3. Comparing long[more than 90 minutes] with short[less than 90 minutes] perfusion time group using pump oxygenator, it was found that the physiological shunt increased about 3% in the long as compared with the short perfusion time group. 4. The mean blood pressure was 70-80 mmHg without a remarkable causal relationship between physiological shunt and mean blood pressure. 5. On elevated $PaO_2$[>200 torr], the physiological shunt was decreased less than 20% of cardiac output, but on diminished $PaO_2$[102 torr] after two days, it was 22.7% of cardiac output. From above results, a contrary causal relationship between $PaO_2$ and physiological shunt was obtained. Co Reviewing chest X-rays postperfusion, it was demonstrated that no remarkable causal relationship between roentgen-ray evidence and physiological shunt could be obtained.

• 감성과학
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• 제4권1호
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• pp.23-31
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• 2001

Psychological and physiological effects from simulator sickness could be an important bias factor for sensibility evaluation. The present experiment investigated the effects of simulator sickness on sensibility evaluation in the controlled condition of driving a car for 60 minutes on a constant speed (60km/h) in graphic simulator. The simulator sickness was measured and analysed for every five minutes using their subjective evaluation and physiological signals. Results of the subjective evaluation showed that there was significant difference between rest and driving condition at 10 minutes from the start of driving, and the level of difference was increased linearly with time. The analysis on central and autonomic nervous systems showed the significant difference between rest and driving conditions after 5 minutes from the start of the driving on the parameters $\alpha$/total and $\beta$/total, and increased level of sympathetic nervous system. But there was no significant difference between different time conditions. The results indicates that physiological changes from simulator sickness can be a bias factor in objective evaluation of human sensibility which also, uses physiological signals. That is, the changes on the parameter $\alpha$/total and $\beta$/total, and on activation level of sympathetic nervous system from simulator sickness can be a bias factor for evaluation of the level of pleasantness and tension. Therefore the effort on improving the analysis by minimizing or eliminating the bias factors should be done for better and accurate sensibility evaluation in simulator environments.

• 감성과학
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• 제7권3호
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• pp.27-35
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• 2004

본 연구는 피부전도도(skin conductance response), 말초혈관 반응(peripheral plethysmograph), 피부온도 (skin temperature)와 심박수(heart rate)와 같은 다양한 생리신호를 측정하여 운전자의 심리반응을 통하여 적정 운전상태를 분석하고자 하였다. 운전자의 심리반응을 측정 및 분석하기 위하여 하드웨어와 알고리듬을 개발하였으며, 운전상황은 자동차 시뮬레이터를 이용하여 다양한 가상 운전상황을 설정하고 생리신호를 측정하였다. 측정 결과 운전자 생리신호가 운전환경의 변화에 따른 심리적 긴장 또는 이완 수준을 잘 반영하고 있고, 감정적 변화에는 다소 둔감한 것으로 나타났다. 이를 심리적 순위척도를 이용하여 정량화하여 심리적 적정 운전범위를 제안하였다. 본 연구의 결과는 추후 운전자의 안전운전이나 건강상태를 모니터링 하기 위한 시스템 개발의 자료로 활용할 수 있을 것이다.