• Proceedings of the ESK Conference
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• 1996.04a
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• pp.259-263
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• 1996

Psychological action is physiological response of outernal stimulus. Physiological response is accompanied b physiological signals which are EEG, EMG, GSR, ECG, BP, and tec. Physiological signals are recently studied for determination of human phychological state. Psychological activity causes electric potential of brain. Physiological signal is considered as measurement of human psychological state. Aditory sensibility which is one of the sense of human may determine differences between positive and negative feeling. EEG and GSR variation with auditory quality of stimulus can be define human negative and positive mental state. This study is to characterize parameters which can determine negative and positive psycholigical state of human.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.3
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• pp.258-266
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• 2013

This paper presents the correlation between psychological and physiological acoustics for the automotive acceleration sound. The research purpose of this paper is to evaluate the sound quality of acceleration sound of a passenger car based EEG signal. The previous method for the objective evaluation of sound quality is to use sound metrics based on psychological acoustics. This method uses not only psychological acoustics but also physiological acoustics. For this work, the sounds of 7 premium passenger cars are recorded and evaluated subjectively by 33 people. The correlation between the subjective rating and sound metrics is calculated based on physiological acoustics. Finally the correlation between the subjective rating and the EEG signal measured on the brain is also calculated. Throughout these results the new evaluation system for the sound quality on the automotive acceleration sound of a passenger car has been developed based on bio-signal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.1076-1094
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• 2022

Technology for emotion recognition is an essential part of human personality analysis. To define human personality characteristics, the existing method used the survey method. However, there are many cases where communication cannot make without considering emotions. Hence, emotional recognition technology is an essential element for communication but has also been adopted in many other fields. A person's emotions are revealed in various ways, typically including facial, speech, and biometric responses. Therefore, various methods can recognize emotions, e.g., images, voice signals, and physiological signals. Physiological signals are measured with biological sensors and analyzed to identify emotions. This study employed two sensor types. First, the existing method, the binary arousal-valence method, was subdivided into four levels to classify emotions in more detail. Then, based on the current techniques classified as High/Low, the model was further subdivided into multi-levels. Finally, signal characteristics were extracted using a 1-D Convolution Neural Network (CNN) and classified sixteen feelings. Although CNN was used to learn images in 2D, sensor data in 1D was used as the input in this paper. Finally, the proposed emotional recognition system was evaluated by measuring actual sensors.

• 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.

• Journal of Korea Technology Innovation Society
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• v.6 no.4
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• pp.411-428
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• 2003

We have examined and analyzed the status of policy, R＆D investments, patents and market share of physiological signal measurement technologies for major countries including Korea, the United States, European Union and Japan. Korea is generally inferior to the others in terms of priority of industrial policy, R＆D investment, number of patents, technological level and world market share. However, Korea could recover competitiveness, with intensive government supports for this technology.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.5
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• pp.25-28
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• 1978

This paper deals with the development research on the application of the principle of polyphase envelope detectioal),2) to extract the envelope from the complex physiological signal waveforms, which otherwise would be very difficult to observe and determine. In order to verify the developed system, the experimental results are included.

• Science of Emotion and Sensibility
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• v.5 no.1
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• pp.17-24
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• 2002

This research was the first step to develop Expert System for Evaluation of Human Sensibility, where human sensibility can be inferred from objective physiological signals. The study aim was to develop an algorithm in which human arousal level can be judged using measured physiological signals. Fuzzy theory was applied for mathematical handling of the ambiguity related to evaluation of human sensibility, and the degree of belonging to a certain sensibility dimension was quantified by membership function through which the sensibility evaluation was able to be done. Determining membership function was achieved using results from a physiological signal database of arousal/relaxation that was generated from imagination. To induce one final result (arousal level) based on measuring the results of more than 2 physiological signals and the membership function of each physiological signal, Dempster-Shafer's Rule of Combination in Evidence was applied, through which the final arousal level was inferred.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.606-611
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• 2007

최근 u-healthcare 서비스 분야에서 단일 시점의 일반화된 치료가 아닌 장시간 개개인의 특성이 반영된 진료와 의료 서비스에 대한 관심이 증가하고 있다. 그러나 기존의 생체 신호 해석은 임상적인 실험을 통해 얻은 표준화된 임계치를 이용해 분석하는 일관된 판단 방법이 주를 이루었다. 본 논문에서는 미래형 홈 환경에서 사용자에 따라 다른 신호 해석을 지원하는 사용자 적응적 생체 신호 해석 방법을 제안한다. 생체 신호 해석은 사용자의 컨텍스트와 환경 컨텍스트를 통합하는 모듈과, 지식표현 기법을 적용한 개인화된 추론 모듈로 구성된다. 제안된 방법은 사용자 정황 정보를 고려하여 사용자 적응적인 생체 신호 해석을 지원하며, 환경 컨텍스트를 고려하여 환경의 변화에 영향을 최소화하는 생체 신호 해석을 지원한다. 또한 사상의학 이론을 생체신호 해석에 동적으로 적용할 수 있는 틀을 제공한다. 이는 추후 미래형 홈 환경에서 다양한 종류의 센서와 함께 개인화된 맞춤형 재택 건강관리 서비스에 활용할 수 있다.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.55-59
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• 2010

Driver distraction is a major cause of traffic accidents in Korea. Various measures are being introduced to detect and warn driver distraction. The objective of this research is to investigate changes in driver's physiological signals due to distraction during driving. Driving simulator experiments have been carried out to investigate discrepancy in EEG signals among normal driving, DMB watching during driving, and cellular phone use during driving. Based on the discrepancy, combination of EEG signals have been identfied as candidate variables for detecting driver distraction. Statistical analysis has been carried out to verify their statistical significance.

• Journal of Sensor Science and Technology
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• v.9 no.6
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• pp.448-454
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• 2000

This paper describes the implementation of a multi-subject, multi-channel optical telemetry system for the short range measurement of electrocardiograms (EKGs) a system which receives command signals and transmits physiological signals to the external system using LED (Light Emitting Diode) and PD (Photodiode). This system decreases the dependency of power supply voltage to the CMOS IC chips and a new enforced synchronization technique using infrared bi-directional communication has also been proposed. The telemetry IC with the size of $5.1{\times}5.1mm^2$ has the following functions: receiving of command signal, initialization of internal state of all functional blocks, decoding of subject selection signal, time division multiplexing of 4-channel modulated physiological signals, transmission of modulated signals to external system, and auto power down control.