• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.11a
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• pp.59-63
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• 2001

인간의 각성은 감성의 한 차원을 차지하여 인간의 작업수행의 효율성에 미치는 영향을 끼치고 있다. 각성의 정확한 측정 및 분석은 인간의 작업에 생산성 극대화를 제시할 수 있다. 그러나 각성은 자극유형에 따라 모드(mode)가 다르게 나타난다. 본 연구는 이러한 각성의 유형에 따른 생리신호의 반응을 측정하여 각성별 정량화 방법을 제시하고자 한다. 20명의 대학생이 각기 다른 각성 자극인 신체적 각성 및 인지적 각성이 유발되었고, 그에 따른 생리신호 반응을 측정, 분석하였다. 결과적으로 각성의 유형은 중추신경계 및 자율신경계 별로 각각 다른 반응을 보였다.

• Proceedings of the PSK Conference
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• 2002.10a
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• pp.115-130
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• 2002

Signal transduction refers to the processes by which cells perceive the environment and/or internal status. In many physiological responses, cellular signals are activated by the transducers attached to the cell surface plasma membrane in response to chemical modulators. Advances in information technology are required in the pharmaceutical sciences to screen and explore the potential therapeutic agents. (omitted)

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.77-78
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• 2012

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.268-282
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• 2000

Speech is one of the most efficient communication media and it includes several kinds of factors about speaker, context emotion and so on. Human emotion is expressed in the speech, the gesture, the physiological phenomena(the breath, the beating of the pulse, etc). In this paper, the method to have cognizance of emotion from anyone's voice signals is presented and simulated by using neuro-fuzzy model.

• Journal of IKEEE
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• v.10 no.1 s.18
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• pp.55-61
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• 2006

In modern society, development of medical technology has extended the human life span. However, it has also caused some side-effects. Mostly old people who live alone are not available the medical service quickly when they are in emergency situations. Moreover heart related diseases as well are rapidly increasing with aging. This study proposes the emergency medical alarm system. This system measures the physiological signals such as ECG(electrocardiogram), temperature, and motion data, analyzes those data automatically, and sends the urgent message to the Emergency Medical Center and to their family. There are two main parts in the system. In the first part, physiological data acquisition part, the troublesome addition and deletion of body signals on existing proposed systems have been supplemented, which led to the modulized production by means of ECG sensor module, temperature sensor module, acceleration sensor module. The other part is mobile unit, which includes signal processing and transmission functions. And bluetooth allows two parts to communicate with each other. Data that are processed in the mobile unit are stored in the PC database through the WLAN using TCP/IP protocol.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.71-78
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• 2017

There are several algorithms to classify emotion, such as Support-vector-machine (SVM), Bayesian decision rule, etc. However, many researchers have insisted that these methods have minor problems. Therefore, in this paper, we propose a novel method for emotion recognition based on Electroencephalogram (EEG) signal using the Gradient method which was proposed by Han. We also utilize a database for emotion analysis using physiological signals (DEAP) to obtain objective data. And we acquire four channel brainwaves, including Fz (${\alpha}$), Fp2 (${\beta}$), F3 (${\alpha}$), F4 (${\alpha}$) which are selected in previous study. We use 4 features which are power spectral density (PSD) of the above channels. According to performance evaluation (4-fold cross validation), we could get 85% accuracy in valence axis and 87.5% in arousal. It is 5-7% higher than existing method's.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.781-793
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• 2010

Recently, owing to the development of ubiquitous sensor network and mobile communication technologies, many studies on healthcare system are being carried out. In this paper, we have designed and implemented a mobile u-Healthcare system based on sensor network. The u-Healthcare system is composed of three components: wireless sensor network at home, healthcare center located at remote site, and gateway which relays sensing physiological signals to healthcare center. In order to measure patient's physiological signal three sensors are used: three channel ECG sensor, pulse oximeter, and blood pressure sensor. Each sensor is mounted on a mote which can send gathered signal to the base node using Zigbee communication protocol. Once the base node receives physiological signal from each sensor, the client in the base node transfers the signal to the healthcare center. The received physiological signal at the healthcare center is analyzed and processed using various algorithms. The processed results are compared to the standard healthcare database and appropriate treatment including dietetics and exercise cure would be sent to the patient as feedback using SMS message or healthcare center web site. Each patient can check and manage one's health state every day using the healthcare system and gain a recovery under the treatments from minor health problems.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.225-229
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• 1998

The purpose of the current study was comparative analysis of autonomic and electrocortical responses to passive and active touch of the tektites with different subjective emotional preference. Perspective goal of the project is development of a template for classification of tactile stimuli according to subjective comfort and associated physiological manifestations. The study was carried out on 36 female college students. Physiological signals were acquired by Grass and B10PAC 100 systems with AcqKnowledge III software. Frontal, parietal and occipital EEG (relative power spectrum /percents/ of EEG bands - delta, theta, slow and fast alpha, low and fast beta), and autonomic variables, namely heart rate (HR), respiratory sinus arrhythmia (RSA), pulse transit time (PTT), respiration rate (RSP) and skin conductance parameters (SCL, amplitude, rise time and number of SCRs) were analyzed for rest baseline and stimulation conditions. Analysis of the overall pattern of reaction indicated that autonomic response to tactile stimulation was manifested in a form of moderate HR acceleration, RSP increase, RSA decrease (lowered vagal tone), decreased n and increased electrodermal activity (increased SCL, several SCRs) that reflects general sympathetic activation. Parietal EEG effects (on contra-lateral side to stimulated hand) were featured by short-term alpha-blocking, slightly reduced theta and significantly increased delta and enhanced fast beta activity with few variations across stimuli. The main finding of the study was that most and least preferred textures exhibited significant differences in autonomic (HR, RSP, PTT, SCR, and at less extent in RSA and SCL) and electrocortical responses (delta, slow and fast alpha, fast beta relative power). These differences were recorded both in passive and active stimulation modes, thus demonstrating reproducibility of distinction between most and least emotionally preferred tactile stimuli, suggesting influence of psychological factors, such as emotional property of stimulus, on physiological outcome. Nevertheless, development of sufficiently sensitive .and reliable template for classification of emotional responses to tactile stimulation based on physiological response pattern may require more extensive empirical database.

• Science of Emotion and Sensibility
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• v.4 no.2
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• pp.79-88
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• 2001

The objectives of this study were to investigate the relationship of sound parameters with subjective sensation and physiological responses, and to figure out the interrelationship between the subjective sensation and physiological responses. Sound parameters calculated were LPT, ΔL, Δf, loudness[Z], and sharpness[Z]. Subjective sensation was evaluated in 7 aspects(soft-hard, loud-quiet, pleasant-unpleasant, sharp-dull, clear-obscure, rough-smooth, high-low) by thirty participants. We acquired physiological responses when each fabric sound was presented to 10 participants. Physiological signals obtained in this study were electroencephalogram(EEG), pulse volume(PV), skin conductance level(SCL), and LF/HF of heart rate variability. The larger the values of loudness[Z] and LPT, the louder and the rougher the subjective sensation of the perceived fabric sound. Also, the larger the values of loudness[Z] and LPT, the harder, the duller, and the less pleasant. As LPT increased, PV decreased. Loudness[Z] increased in proportion to SCL and so did sharpness[Z] to LF/HF. As the sound perceived to be quieter and clearer, the relative power of slow alpha rose. As the sound perceived to be more pleasant and smoother, PV rose.

• Journal of Biosystems Engineering
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• v.36 no.3
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• pp.223-230
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• 2011

Physiological signals such as body temperature, heart rate, blood pressure and heart rate variability and biomechanical workload for stress analysis were investigated during the cherry tomato harvesting work in a greenhouse. The skin temperatures raised $0.05^{\circ}C$/min, $0.03^{\circ}C$/ min, and $0.08^{\circ}C$/min in standing, stooping and squatting postures, respectively. Breath rate significantly increased from 18 to 28 breaths/min during the cherry tomato harvesting work. As the heart rate during the work ranged from about 72 to 110 beats/min (bpm), the cherry tomato harvesting work appeared to be a light intensity task of less than 110 bpm. The worker's average energy consumption rate in three positions during 43 min working time was 65.74 kcal (91 kcal/h in 70 kg). This was a light intensity of work, compared to 75 kcal/h in 70 kg of basic metabolic energy consumption rate of a worker with 70 kg weight; The maximum shear force on the disk (L5/ S1) due to static workload in the cherry tomato harvesting work was 446 N in the stooping posture, 321 N in the squatting posture and 287 N in the standing posture. Acute stress index expressed with the heart rate variability, increased parasympathetic activation up to about 70 while workers were doing most agricultural work in this study. This study provided a system to measure quantitatively workers' physiological change, kinematics and kinetic factors without any restrictions of space in the greenhouse works.