• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.9-15
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• 2019

As the human population increases in the world, the ratio of health doctors is rapidly decreasing. Therefore, it is an urgent need to create new technologies to monitor the physical and mental health of people during their daily life. In particular, negative mental states like depression and anxiety are big problems in modern societies. Usually this happens due to stressful situations during everyday activities including work. This paper presents a machine learning approach to reliably estimating the level of human mental stress using wearable physiological sensors. And also, this paper presents an Android- and Arduino-based stress monitoring and relief system.

• The Journal of Information Technology
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• v.9 no.1
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• pp.9-19
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• 2006

Medications or conitive-behavior methods have been mainly used as a treatment of alcoholism. lately the virtualy technology has been applied to the kink of alcoholic disorders. A virtual environment makes him having avility to over come the drink. In this study, we were implemented by making panorama images and 3D object modules using 3D MAX, VRML, JAVA. And the BAR stimulator that composed with a position sensor, head mount display, and audio system, is suggested. To illustrate the physiological difference between a person who has a alcoholism and without a liquor bottle, heart rate was measured during experiment, and also measured a person's HR after the virtual reality training. The system measures the Physiological signals such as ECG, Temperature, analyzes those data automatically. The system has two parts, one is physiological data acquisition part which gets the body signal, and the other one is mobile nuit which includes signal processing and transmission functions, And Bluetooth allows two parts to communicate with each other. we demonstrated the subjective effectiveness of virtual reality psychotherapy through the clinical experiment.

• Journal of Biomedical Engineering Research
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• v.21 no.5
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• pp.513-517
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• 2000

In this study, we fabricated the advanced telemetry system that transmitting media use radio frequency(RF) for the middle range measurement of the physiological signals and receiving media use optical for electromagnetic interference problem. The telemetry system within a size of 65$\times$125$\times$45mm consists of three parts: a RF transmitter, a optical receiver and a physiological signal processing CMOS one chip. Advantages of proposed telemetry system is wireless middle range(50m) FM transmission, reduce electromagnetic interference to a minimum which enables a comfortable bed-side telemetry system.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10a
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• pp.72-73
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• 2007

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.11a
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• pp.80-81
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• 2011

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.11a
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• pp.72-73
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• 2011

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.65-66
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• 2012

• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.62-69
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• 2020

Most people suffer from stress during day life because modernized society is very complex and changes fast. Because stress can affect to many kind of physiological phenomena it is even considered as a disease. Therefore, it should be detected earlier, then must be released. When a person is being stressed several bio-signals such as heart rate, etc. are changed. So, those can be detected using medical electronics techniques. In this paper, stress assessment system is studied using random forest algorithm based on heart rate, RR interval and Galvanic skin response. The random forest model was trained and tested using the data set obtained from the bio-signals. It is found that the stress assessment procedure developed in this paper is very useful.

• Journal of Biomedical Engineering Research
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• v.16 no.2
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• pp.157-166
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• 1995

The Electroencephalogram (EEG) and evoked potential (EP) t;ave widely been used for study of brain functions. The EEG and EP signals acquired from multi-channel electrodes placed on the head surface are often interfered by other relatively large physiological signals such as electromyogram (EMG) or electroculogram (EOG). Since these artifact-affected EEG signals degrade EEG mapping, the removal of the artifact-affected EEGs is one of the key elements in neuro-functional mapping. Conventionally this task has been carried out by human experts spending lots of examination time. In this paper a neural-network based classification is proposed to replace or to reduce human expert's efforts and time. From experiments, the neural-network based classification performs as good as human experts : variation of decisions between the neural network and human expert appears even smaller than that between human experts.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.544-544
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• 2000

From ancient times. the diagnosis method of the oriental medicine has been Performed by curing diseases by means of rectifying and adjusting the unbalance in the Physiological function of the five viscera and the six bowels of a human body. Diseases have been diagnosed by the condition of blood circulation that cycles a human body through blood vessels by dint of the vitality of the heart, Based on such a systematic pulse diagnosis method, the article presents parameters that will be beneficial to clinical application on the basis of its analysis of the filtering for eliminating noises from pulse signals inputted from sensor group the digital hardware dealing with signals necessary for recognition algorithm. and the structure of diagnosis algorithm and components of pulse waveform.