• 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.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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• pp.824-836
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• 2020

This study investigated the effects of textile attachments on electroencephalogram using 20 persons (10 males and 10 females). Four types of attachment cushions were manufactured by changing the shell fabric (cotton and microfiber) and interlining (synthetic loose fiber and buckwheat). This was done using BIOS-S8 (BioBrain Inc., Korea), an 8-channel polygraph for multi-body signal measurement, to measure EEG. Data were analyzed using the SPSS 24.0 statistical program. EEG values were significantly activated according to gender, particularly when the subjects' eyes were open. For the male cases, 'RT', 'RAHB' values were highly activated and for the female cases, 'RA', 'RB', 'RG', 'RFA', 'RST', 'RLB', 'RMB', 'RST', 'RMT' values were highly activated. Examining the differences in EEG according to type of attachment indicated no significant difference in both sexes. However, in cases of females with their eyes closed, the 'RSA' index was quite different in the left occipital lobe (O1), and when their eyes were open, the 'RFA' in the right frontal lobe (F4) showed a significant difference. However, there was no obvious correlation between the activation of EEG and the subjective preference of textile attachments.

• 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

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.729-738
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• 2019

Recently, we aim to improve the quality of virtual reality contents based on quantitative analysis results of emotions through combination of emotional recognition field and virtual reality field. Emotions are analyzed based on the participant's vital signs. Much research has been done in terms of signal analysis, but the methodology for quantifying emotions has not been fully discussed. In this paper, we propose a normalization function design and expression method to quantify the emotion between various bio - signals. Use the Brute force algorithm to find the optimal parameters of the normalization function and improve the confidence score of the parameters found using the true and false scores defined in this paper. As a result, it is possible to automate the parameter determination of the bio-signal normalization function depending on the experience, and the emotion can be analyzed quantitatively based on this.

• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.13-22
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• 2017

Emotion has a direct influence such as decision-making, perception, etc. and plays an important role in human life. For the convenient and accurate recognition of high-arousal negative emotion, the purpose of this paper is to design an algorithm for analysis using the bio-signal. In this study, after two emotional induction using the 'normal' / 'fear' emotion types of videos, we measured the Galvanic Skin Response (GSR) signal which is the simple of bio-signals. Then, by decomposing Tonic component and Phasic component in the measured GSR and decomposing Skin Conductance Very Slow Response (SCVSR) and Skin Conductance Slow Response (SCSR) in the Phasic component associated with emotional stimulation, extracting the major features of the components for an accurate analysis, we used a discrete wavelet transform with excellent time-frequency localization characteristics, not the method used previously. The extracted features are maximum value of Phasic component, amplitude of Phasic component, zero crossing rate of SCVSR and zero crossing rate of SCSR for distinguishing high-arousal negative emotion. As results, the case of high-arousal negative emotion exhibited higher value than the case of low-arousal normal emotion in all 4 of the features, and the more significant difference between the two emotion was found statistically than the previous analysis method. Accordingly, the results of this study indicate that the GSR may be a useful indicator for a high-arousal negative emotion measurement and contribute to the development of the emotional real-time rating system using the GSR.

• International Journal of Industrial Entomology and Biomaterials
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• v.2 no.1
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• pp.1-6
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• 2001

This paper reports a few characteristics of seven insect mitochondrial genomes sequenced completely (Bombyx mori, Drosophila melanogaster, D. yakuba, Apis mellifera, Anopheles gambiae, A. quadrimaculatus, and Locusta migratoria). Comparative analysis of complete mt genome sequences from several species revealed a number of interesting features (base composition, gene content, A+T-rich region, and gene arrangement, etc) of insect mitochondrial genome. The properties revealed by our work shed new light on the organization and evolution of the insect mitochondrial genome and more importantly open up the way to clearly aimed experimental studies for understanding critical roles of the regulatory mechanisms (transcription and translation) in mitochondrial gene expression.

• Journal of the Korean Society of Clothing and Textiles
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• v.45 no.2
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• pp.305-316
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• 2021

In this study, the effect of wearing functional compression pants is verified using a lower-limb wearable robot through a bio-signal analysis and subjective fit evaluation. First, the compression area to be applied to the functional compression pants is derived using the quad method for nine men in their 20s. Subsequently, functional compression pants are prepared, and changes in Electroencephalogram (EEG) and Electrocardiogram (ECG) signals when wearing the functional compression and normal regular pants inside a wearable robot are measured. The EEG and ECG signals are measured with eyes closed and open. Results indicate that the Relative alpha (RA) and Relative gamma wave (RG) of the EEG signal differ significantly, resulting in increased stability and reduced anxiety and stress when wearing the functional compression pants. Furthermore, the ECG analysis results indicate statistically significant differences in the Low frequency (LF)/High frequency (HF) index, which reflect the overall balance of the autonomic nervous system and can be interpreted as feeling comfortable and balanced when wearing the functional compression pants. Moreover, subjective sense is discovered to be effective in assessing wear fit, ease of movement, skin friction, and wear comfort when wearing the functional compression pants.

• Journal of Biomedical Engineering Research
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• v.23 no.5
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• pp.397-403
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• 2002

Urine glucose monitoring system is a self-monitoring system that display the glucose level by non-invasive measurement method. In this paper, We developed a noninvasive urine glucose monitoring system that improved defects of urine glucose measurement with a colorimeter method and invasive blood glucose measurement method. This system consist of bio-chemical sensor for urine glucose measurements, signal detecting part, digital and signal analysis part, display part and power supplying part. The developed bio-chemical sensor for the measurement of urine glucose has good reproducibility, convenience of handing and can be mass-produced with cheap price. To evaluate the performance of the developed system, We performed the evaluation of confidence about the detection of glucose level by a comparison between a standard instrument in measuring glucose level and the developed system using standard glucose solutions mixed with urine. Standard error was 2.85282 from the evaluation of confidence based on regression analysis. Also, In analysis of S.D(standard deviation) and C.V(coefficient of validation) that are important parameters to evaluate system using bio-chemical sensor, S.D was 10% which falls under clinically valid value, 15%, and C.V was under 5%. Consequently from the above results, compared to blood glucose measurement, the system performance is satisfactory.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1370-1378
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• 2018

There is a problem to measure neutral bio-signals during sleep because of inconvenience of attaching lots of sensors. In this study, we measured single electrocardiogram(ECG) signal and analyzed the correlation with sleep. After R-peak detection from ECG signal, we extracted 9 features from time and frequency domain of heart rate variability(HRV). Mean of HRV, RR intervals differing more than 50ms(NN50), and divided by the total number of all RR intervals(pNN50) have significant differences in each sleep stage. Specially, the mean HRV has an average of 87.8% accuracy in classifying sleep and awake status. In the future, the measurement ECG signal minimizes inconvenience of attaching sensors during sleep. Also, it can be substituted for the standard sleep measurement method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.891-898
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• 2012

The study for the passenger's comfortableness of vehicles and the arousal of car drivers has been done widely. On the other hand, there are few studies for the locomotive engineers. Human error means that the mistakes made by human, recently it receives attention in the field of safety engineering and human engineering. Comparing the operating condition of train with car, because of the simplification of the visual stimulus, the arousal level on the train goes down easily. The arousal level down makes judgement down, the accident risk from human error is getting bigger. In this study, we measured bio-signals(ECG, EDA, PPG, respiration and EEG) from 6 locomotive engineers to evaluate their arousal state while they operated the train. Also we recorded the 3 axes acceleration signal showing the vibration state of train. Also, the existence of tunnels were simultaneously measured. At the station section where the train speed goes down, the size of vector's sum decreases because of reduced vibration. Beta component in EEG tends to increase at the entering point of each station and tunnel. It is due to the arousal reaction and tension growth. The mean SCR(skin conductance response) was more increased in neutral section. As the button control movement (body movement) increases in the neutral section, it is appeared that SCR increase. RR interval tends to gradually increase during train operation for 1 hour 40 minutes. However, It tends to sharply decrease at the stop station because strong concentration needed to stop train on the exact point. The engineer's arousal reaction can be checked through analysing the bio-signal change during train operation. Therefore, if this analysing result is adopted to the sleepiness prevention caution system, it will be useful for the safety train operation.