• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.29.2-29
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• 2001

For the design of human-centered systems in which a human and machine such as a robot form a human-in system, human-friendly interaction/interface is essential. Human-friendly interaction is possible when the system is capable of recognizing human biosigns such as5 EMG Signal, hand gesture and facial expressions so the some humanintention and/or emotion can be inferred and is used as a proper feedback signal. In the talk, we report our experiences of applying the Soft computing techniques including Fuzzy, ANN, GA and rho rough set theory for efficiently recognizing various biosigns and for effective inference. More specifically, we first observe characteristics of various forms of biosigns and propose a new way of extracting feature set for such signals. Then we show a standardized procedure of getting an inferred intention or emotion from the signals. Finally, we present examples of application for our model of rehabilitation robot named.

• The Journal of Korean Medicine
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• v.33 no.1
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• pp.68-78
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• 2012

Objectives: The purpose of this study was to analyze the relationship between Yin-deficiency questionnaire score and various biofunctional signals in women. Methods: A retrospective chart review was performed on charts of 195 patients who visited Gangdong Kyung Hee Hospital between April 1st and September 30th, 2011. The subjects were categorized into two groups, a low Yin-deficiency group (n=118) and a high Yin-deficiency group (n=77). The authors analyzed the correlation between Yin-deficiency questionnaire score and biofunctional signals by Pearson's correlation coefficient test and the difference in biofunctional signals between the two groups by independent samples t-test using SPSS for windows. Results: 1. Negative correlations were observed between the temperature difference of back-humerus, standard deviation of all R-R intervals (SDNN), total power (TP), low frequency (LF), high frequency (HF) on heart rate variability parameters, and Yin-deficiency questionnaire score. A positive correlation was observed between the temperature difference of knee-humerus and Yin-deficiency questionnaire score. 2. The temperature difference of back-humerus in the high Yin-deficiency group was significantly higher than that in the low Yin-deficiency group. The temperature difference of knee-humerus, height, waist-hip ratio, SDNN, TP, LF, and HF of the high Yin-deficiency group were significantly lower than those of the low Yin-deficiency group. Conclusions: The results of this study suggest that the comprehensive diagnosis of Yin-deficiency and biofunctional signals is useful.

• Journal of Navigation and Port Research
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• v.38 no.6
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• pp.645-653
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• 2014

A Bridge Navigational Watch Alarm System (hereafter 'BNWAS') is to monitor and detect if an officer of watch(hereafter 'OOW') keeps a sharp lookout on the bridge. The careless lookout of an OOW could lead to marine accidents. For this reason on June 5th, 2009, IMO decided that a ship is equipped with a BNWAS. However, an existing BNWAS gives the OOW a lot of inconvenience and stress in its operation. It requires that the OOW should press reset buttons to confirm their alert watch on the bridge at every three to twelve minute. Many OOWs have complained that at some circumstances they cannot focus on their bridge activities including watch-keeping due to a lots of resetting inputs of BNWAS. Accordingly, IMO has allowed the use of a motion sensor as a resetting device. The motion sensor detects the movements of human body on the bridge and subsequently sends reset signals directly to BNWAS automatically. As a result, OOWs can work uninterrupted. However, some of classification societies and flag authorities have a slightly different stance on the use of motion sensor as a resetting method for BNWAS. The reason is that the motion sensor may trigger false reset signals caused by the motion of objects on the bridge, especially a slight movement such as toss and turn of human body which can extend the period of careless watch. As a basic study to minimize the false reset signals, this paper proposes a simple configuration of BNWAS, which consists of only three motion sensors associated with 'AND' and 'OR' logic gates. Additionally, several considerations are also proposed for the implementation of motion sensors. This study found that the proposed configuration which consists of three motion sensors is better than an existing one by reducing false reset signals caused by a slight movement of human body in one's sleep. The proposed configuration in this paper filters false reset signals and is simple to be implemented on existing vessels. In addition, it can be easily installed just by a basic electrical knowledge.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1637-1642
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• 2015

Next-generation applications using technology IT fused to biological signals from the emotional state to extract a lot of research has been, and the sensitivity of the human sensory functions influences the physiological condition known to be the fact that. In this paper, Propose an Emotional-lighting control algorithm using bio-signals. LED lighting for Emotion light is environmentally friendly and has a high efficiency and long life. In particular, LED lights are different colors represent the possible single light sphere advantages. And, Human sensitivity for determining a more accurate biological signals using EEG was collected using EEG equipment sensitivity was determined to analyze the EEG.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.5
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• pp.589-594
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• 2014

It has been known that the particular brain waves are induced when a human concentrates. In our study, we aimed to analysis the brain waves related to human concentration using visual stimulus to induce the concentration. The visual stimulus tasks were presented to subjects for concentration. We measured EEG signals with several channels and analyzed the signals into several frequency bands. In the measured EEG signals, we analyzed to focus on theta waves, SMR waves and mid-beta waves. Therefore we presented the results to investigate characteristics of the EEG signals related to the human concentration.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.11
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• pp.989-995
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• 2015

In the literature, various stochastic anomaly detection methods, such as limit checking and PCA-based approaches, have been applied to weld defect detection. However, it is still a challenge to identify meaningful defect patterns from very limited sensor signals of laser welding, characterized by intermittent, discontinuous, very short, and non-stationary random signals. In order to effectively analyze the physical characteristics of laser weld signals: plasma intensity, weld pool temperature, and back reflection, we first transform the raw data of laser weld signals into the form of event logs. This is done by multidimensional discretization and event-codification, after which the event logs are decoded to extract weld defect patterns by $Na{\ddot{i}}ve$ Bayes classifier. The performance of the proposed method is examined in comparison with the commercial solution of PRECITEC's LWM$^{TM}$ and the most recent PCA-based detection method. The results show higher performance of the proposed method in terms of sensitivity (1.00) and specificity (0.98).

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.796-801
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• 1994

Measuring noise, sound quality or acoustical comfort presents a difficult task for the acoustic engineer. Sound and noise are ultimately jugded by human beings acting as analysers. Regulations for determining noise levels are based on A-weighted SPL measurement performed with only one microphone. This method of measurement is usually specified when determining whether the ear can be physically damaged. Such a simple measurement procedure is not able to determine annoyance of sound events or sound quality in general. For some years investigations with binaural measurement analysis technique have shown new possibilities for the objective determination of sound quality. By using Artificial Head technology /1/, /2/ in conjunction with psychoacoustic evaluation algorithms - and taking into account binaural signal processing of human hearing, considerable progress regarding the analysis of sounds has been made. Because sound events often arise in a complex way, direct conclusions about components subjectively judged to be annoying with regard to their causes and transmission paths, can be drawn in a limited way only. A new procedure, complementing binaural measurement technology combined with mulit-channel measuements of acceleration sensor signals has been developed. This involves correlating signals influencing sound quality, analyzed by means of human hearing, with signals form different acceleration sensors fixed at different positions of the sound source. Now it is possible to recognize the source and the transmission way of those signals which have an influence on the annoyance of sound.

• Progress in Medical Physics
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• v.30 no.4
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• pp.139-149
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• 2019

Purpose: With neurodegeneration, the signal intensity of the cerebrospinal fluid (CSF) in the brain increases. The objective of this study was to evaluate chemical exchange saturation transfer (CEST) signals with and without the contribution of CSF signals in elderly human brains using two different 3T magnetic resonance imaging (MRI) sequences Methods: Full CEST signals were acquired in ten subjects (Group I) with a three-dimensional (3D)-segmented gradient-echo echo-planar imaging (EPI) sequence and in ten other subjects (Group II) with a 3D gradient and spin-echo (GRASE) sequence using two different 3T MRI systems. The segmented tissue compartments of gray and white matter were used to mask the CSF signals in the full CEST images. Two sets of magnetization transfer ratio asymmetry (MTR_asym) maps were obtained for each offset frequency in each subject with and without masking the CSF signals (masked and unmasked conditions, respectively) and later compared using paired t-tests. Results: The region-of-interest (ROI)-based analyses showed that the MTR_asym values for both the 3D-segmented gradient-echo EPI and 3D GRASE sequences were altered under the masked condition compared with the unmasked condition at several ROIs and offset frequencies. Conclusions: Depending on the imaging sequence, the MTR_asym values can be overestimated for some areas of the elderly human brain when CSF signals are unmasked. Therefore, it is necessary to develop a method to minimize this overestimation in the case of elderly patients.

• International Journal of Advanced Culture Technology
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• v.6 no.1
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• pp.42-49
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• 2018

In this study, we tried to reveal the state of stillness of Cho Ji-Hoon's poem "Silent Night 1" as a healing modifier. The language of poem is synaptically linked to the calmness emotion of the human body, seeking a principle that leads to a state of healing. Therefore, this study was carried out for the purpose of applying the principle to literary therapy program. The silent signal embedded in the poem is encoded into the signals of the sound as it is synapsed to the human body. Encoding of auditory nerves by poem lines is like a Morse code that word and word leave in the human body. The action potential of the auditory nerve is further activated by the potential difference between the word and the word represented by the neural network, such as a Morse code, which is accessed to the human body by such a path. There is worked as amplified potential difference between the words perceived by a sound which is synapsed to the human body and by a silence which is synapsed to the human body. The phenomenon of the words approaching the human body and setting the absence of sound and amplifying the sound is because the words amplifies the Morse codes in the human neural network. At this time, the signals overlap each other. Thereby this poem is increasing the amplitude of the sound. This overlapping of auditory signals appears and amplifies the catharsis. If this Cho Ji-Hoon Poem's principle is applied to literary therapy program in the future, more effective treatment will be done.

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.705-713
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• 2011

Objective: The aim of this study is to compare results of emotion recognition by several algorithms which classify three different emotional states(happiness, neutral, and surprise) using physiological features. Background: Recent emotion recognition studies have tried to detect human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 217 students participated in this experiment. While three kinds of emotional stimuli were presented to participants, ANS responses(EDA, SKT, ECG, RESP, and PPG) as physiological signals were measured in twice first one for 60 seconds as the baseline and 60 to 90 seconds during emotional states. The obtained signals from the session of the baseline and of the emotional states were equally analyzed for 30 seconds. Participants rated their own feelings to emotional stimuli on emotional assessment scale after presentation of emotional stimuli. The emotion classification was analyzed by Linear Discriminant Analysis(LDA, SPSS 15.0), Support Vector Machine (SVM), and Multilayer perceptron(MLP) using difference value which subtracts baseline from emotional state. Results: The emotional stimuli had 96% validity and 5.8 point efficiency on average. There were significant differences of ANS responses among three emotions by statistical analysis. The result of LDA showed that an accuracy of classification in three different emotions was 83.4%. And an accuracy of three emotions classification by SVM was 75.5% and 55.6% by MLP. Conclusion: This study confirmed that the three emotions can be better classified by LDA using various physiological features than SVM and MLP. Further study may need to get this result to get more stability and reliability, as comparing with the accuracy of emotions classification by using other algorithms. Application: This could help get better chances to recognize various human emotions by using physiological signals as well as be applied on human-computer interaction system for recognizing human emotions.