• 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.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.2
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• pp.29-36
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• 2005

In oder to generate various shock signals in a field study, a passenger car was driven at several speeds over road profiles that included a number of half sine shaped bumps of various heights. A triaxial SAE pad sensor was mounted on the front passenger seat to measure the acceleration signals which might produce subjective discomfort. The measured accelerations were correlated with the subjective assessments of 14 subjects. The magnitude of subjective discomfort was found to be proportional to the VDV and also the peak to peak of the frequency weighted acceleration signal.

• Journal of the Korean Society for Railway
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• v.10 no.4
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• pp.398-404
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• 2007

The objective of this study is to verify the hypothesis that cognitive process of railway drivers would be influenced by train speed. The hypothesis is tested by investigating railway drivers' cognitive processes at different speeds of a locomotion. The experiment shows that human performance of railway drivers decreases as the train speed becomes faster. In addition, simple signals outperformed complex signals at every train speed. Therefore, it is suggested to redesign complex signals simpler for improving drivers' human performance. It is also recommended that the Korean railway safety law should be revised to mention requirement of the signal design, especially for the fastest train including KTX. The implications of the experiments are discussed in detail.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.5-52
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• 2002

In this paper, we develop analysis models for classification of temporal data from human subjects. The study focuses on the analysis of electroencephalogram (EEG) signals obtained during various emotional states. We demonstrate a generally applicable method of removing EOG and EMG artifacts from EEGs based on independent component analysis (ICA). All EEG channel maps were interpolated from 10 EEG subbands. ICA methods are based on the assumptions that the signals recorded on the scalp are mixtures of signals from independent cerebral and artifactual sources, that potentials arising from different parts of the brain, scalp and body are summed linearly at the electrodes and that prop...

• The Journal of the Acoustical Society of Korea
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• v.4 no.1
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• pp.9-15
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• 1985

In this paper, we describe a new algorithm for deciding whether a given segment of a speech signal is classified as voiced speech, unvoiced speech, or silence, based on parameters made on the signal. The measured parameters for the voiced-unvoiced classfication are the areas of each Zero crossing interval, which is given by multiplication of the magnitude by the inverse zero corssing rate of speech signals. The employed parameter for the unvoiced-silence classification, also, are each of positive area summation during four milisecond interval for the high frequency emphasized speech signals.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1163-1168
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• 2005

This paper proposes a soft-remote-control (soft-remocon) system based on EMG signals for the Intelligent Sweet Home. The proposed system is applied to Intelligent Sweet Home which was developed to help the independence living of the elderly and physically handicapped individuals. The goal of proposed system is to control home-installed electronic devices such as TV, air-conditioner, curtain and lamp in Intelligent Sweet Home using EMG signals. Features such as VAR and DAMV having good separability performance are selected for pattern classification. FMMNN is adopted as a pattern classifier. Classification results are allowed to a developed remote control module and then corresponding infrared pulses can operate home-installed electronic devices. We concluded that EMG as an input interface for home-installed electronic devices in Intelligent Sweet Home.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.364-371
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• 2013

Emotion Recognition is one of the important part to develop in human-human and human computer interaction. In this paper, we have focused on the performance of multi-class SVM (Support Vector Machine) with Gaussian RFB (Radial Basis function) kernel, which has been used to solve the problem of emotion recognition from physiological signals and to improve the accuracy of emotion recognition. The experimental paradigm for data acquisition, visual-stimuli of IAPS (International Affective Picture System) are used to induce emotional states, such as fear, disgust, joy, and neutral for each subject. The raw signals of acquisited data are splitted in the trial from each session to pre-process the data. The mean value and standard deviation are employed to extract the data for feature extraction and preparing in the next step of classification. The experimental results are proving that the proposed approach of multi-class SVM with Gaussian RBF kernel with OVO (One-Versus-One) method provided the successful performance, accuracies of classification, which has been performed over these four emotions.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.11 no.2
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• pp.84-95
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• 2007

Background and Purpose: We have studied the trends of EEG signals in the voluntary breathing condition by applying the fractal analysis. According to chaos theory, irregularity of EEG signals can result from low dimensional deterministic chaos. A principal parameter to quantify the degree of Chaotic nonlinear dynamics is correlation dimension. The aim of this study was to analyze correlation between the correlation dimension of EEG and HRV(heart rate variability). We have studied the trends of EEG signals in the voluntary breathing condition by applying the fractal analysis. Methods: EEG raw data were measured by moving windows during 15 minutes. Then, the correlation dimension(D2) was calculated by each 40-seconds-segment in 15 minutes data, totally 36 segments. 8 channels EEG study on the Fp, F, T, P was carried out in 30 subjects. Results and Conclusion: Correlation analysis of HRV was calculated with deterministic non-linear data and stochastic non-linear data. 1. Ch1(Fp1), Ch4(F3), Ch4(F4) is positive correlated with In LF. 2. Ch1(Fp1), Ch3(F3) is positive correlated with In TF.

• Journal of Industrial Technology
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• v.43 no.1
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• pp.25-31
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• 2023

Stretchable and flexible electronics that comply with dynamic movements and micromotion of the human tissues can enable real-time monitoring of physiologic signals onto the human skin and in the brain, respectively. Especially, gallium based liquid metal stretchable electronics can offer human-interactive biosensors to monitor various physiologic parameters. However, the liquid-like nature, surface oxidation and contamination by organic materials, and low biostability of the liquid metals have still limited the long-term use as bioelectronics. Here we introduced electrochemical deposition without oxidation pathways to overcome these practical challenges in liquid metal bioelectronics. CNT/PDDA composite with reduction way and PEDOT:BF₄ with oxidation way under organic solvent are suggested as rationally designed material engineering approaches. We confirmed that the structures with the soft, flexible, and stretchable liquid metal platform can successfully detect dopamine with a high sensitivity and selectivity, record neural signals including action potentials without scar formation, and monitor physiologic signals such as EMG and ECG.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1485-1488
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• 2003

This paper proposes a wireless EMG-based human-computer interface (HCI) for persons with disabilities. For the HCI, four interaction commands are defined by combining three elevation motions of shoulders such as left, right and both elevations. The motions are recognized by comparing EMG signals on the Levator scapulae muscles with double thresholds. A real-time EMG processing hardware is implemented for acquiring EMG signals and recognizing the motions. To achieve real-time processing, filters such as high- and low-pass filter and band-pass and -rejection filter, and a full rectifier and a mean absolute value circuit are embedded on a board with a high speed microprocessor. The recognized results are transferred to a wireless client system such as a mobile robot via a Bluetooth module. From experimental results using the implemented real-time EMG processing hardware, the proposed wireless EMG-based HCI is feasible for the disabled.