• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1821-1823
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• 2006

This paper presents a development of interface device for electro-oculogram(EOG) signal and it's application to the wireless mouse of wearable PC. The interface device is composed of five bio-electrodes for detecting oculomotor motion, several band-pass filters, instrumentation amplifier and a microprocessor. we have first analyzed impedance characteristics between skin and a bio-electrode. since the impedance highly depends on human face, it's magnitude differs from person. this interface device was applied to develop a wireless mouse for wearable PC, as a Bio Machine Interface(BMI). Where in the prompt on PC monitor is controlled by only EOG signals. this system was implemented in a Head Mount Display(HMD) unit. experimental results show the accuracy of above 90%.

• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.236-243
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• 2004

In this paper, we proposed a brain-computer interface system using EEG signals. It can generate 4 direction command signal from EEG signals captured during imagination of subjects. Bandpass filter used for preprocessing to detect the brain signal, and the power spectrum at a specific frequency domain of the EEG signals for concentration status and non-concentration one is used for feature. In order to generate an adequate signal for controlling the 4 direction movement, we propose a new interface system implemented by using a support vector machine and a time-multiplexing method. Moreover, bio-feed back process and on-line adaptive pattern recognition mechanism are also considered in the proposed system. Computer experimental results show that the proposed method is effective to recognize the non-stational brain wave signal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.238-240
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• 2018

Recently, healthcare services have been developed and studied using various bio-signal analysis tools. Most bio-signal analysis studies utilize Matlab and R Programming. However, in order to apply the algorithm developed by Matlab and R Programming to the system, it is necessary to convert the source code. This paper proposes a smart interface that can skip source code conversion.

• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.319-325
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• 2012

Objective: The aim of this study was to develop the assistive device for accelerator and brake pedals using bio-signals from the prefrontal lobe in the driving simulator and evaluate its performance. Background: There is lack of assistive devices for the driving in peoples with disabilities in Korea. However, if bio-signals and/or brain waves are used at driving a car, the people with serious physical limitations can improve their community mobility. Method: 15 subjects with driver's license participated in this study for experiment of driving performance evaluation in the simulator. Each subject drove the simulator the same course 10 times in three separated groups which use different interface controllers to accelerate and brake: (1) conventional pedal group, (2) joystick group and (3) bio-signal group(horizontal quick glance of the eyes and clench teeth). All experiments were recorded and the driving performances were evaluated by three inspectors. Results: Average score of bio-signal group for the driving in the simulator was increased 3% compared with the pedal group and was increased 9% compared with the joystick group(p<0.01). The subjects using bio-signals was decreased 44% in number of deduction compared with others because the device had the built-in modified cruise control. Conclusion: The assistive device for accelerator and brake pedals using bio-signals showed significantly better performance than using general pedal and a joystick interface(p<0.01). Application: This study can be used to design adaptive vehicle for driving in people with disabilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.65-67
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• 2017

Due to the development of mobile computing and wearable technology, various wearable devices for measuring bio-signals in everyday life have been developed and popularized, and healthcare services utilizing bio-signals are attracting attention. In recent years, healthcare services have been developed and studied using various bio-signal analysis tools. Most bio-signal analysis studies utilize Matlab. However, in order to apply the algorithm developed in Matlab to the system, it is necessary to convert the source. We want to provide a smart interface that can skip source conversion. In this paper, we develop an interface to run the source file itself in the system by omitting the conversion technique for applying the algorithm developed in Matlab to the system.

• Journal of Biomedical Engineering Research
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• v.19 no.3
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• pp.261-268
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• 1998

Electrogastrography(EGG), the cutaneous recording of the myoelectrical activity of the stomach using surface electrodes, is a non-invasive technique to detect gastric motility disorder, We developed a detection and analysis system for the EGG signal, which consists of hardware(bio-amplifier, filter) and softwere(user interface, analysis algorithm, patient database). The EGG signal was amplified and filtered by 3 channel bio-amplifiers, and simultaneously digitized and stored on IBM PC with a sampling frequency of 16 Hz. The stored EGG signal was analyzed using developed algorithm to extract clinically useful information from the signal. The developed system has tested through animal experiments, and is under clinical evaluation.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.935-939
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• 2003

The emotion recognition is one of the most significant interface technologies which make the high level of human-machine communication possible. The central nervous system stimulated by emotional stimuli affects the autonomous nervous system like a heart, blood vessel, endocrine organs, and so on. Therefore bio-signals like HRV, ECG and EEG can reflect one' emotional state. This study investigates the correlation between emotional states and bio-signals to realize the emotion recognition. This study also covers classification of human emotional states, selection of the effective bio-signal and signal processing. The experimental results presented in this paper show possibility of the emotion recognition.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.515-518
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• 2003

The electrical current generated by heart creates not only electric potential but also a magnetic field. In this paper, we have designed the multiplexing data acquisition system for multichannel bio-magnetic signal measurement. The system consists of VXI rack which is organized MUX and AD board, Industrial rack which is mounted single board computer and DSP board. This system enable to realtime monitoring of multichannel data simultaneously. The number of channel could be increased simply added each module and firmware could be upgraded easily using host port interface of DSP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2079-2086
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• 2011

Recently, technology of self diagnosis system which one of health-care has been research very active. With this, In this paper, we have to implement the self-blood sugar measurement system that is interlock with PC, RFID, and Bio-Signal glucose tester and accessible user interface. Therefore the equipments can performs accessible interface composition for communication between devices and PC, analysis and test of communication status of the RFID tag and reader that it easy to obtain the data of self-diagnosis linkage with PC, RFID, and Bio-Signal glucose tester. In other words, as result of communication protocol experiment with self-blood sugar measurement data, it has been showed to display a high-reliability result through year, month, and day, body temperature, and levels and check point of blood glucose.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.19-26
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• 2005

This paper introduces a new design method of realizing the machine control interface by using bio-signals(EEG/EOG). This method can be further expanded to be applied to the computer system responding to EEG or EOG signals and the general bio-feedback system. For this reason, we made the remotely controlled toy system controlled by the EEG spectrums, their combination indexes, and EOG parameters. And the headset that has bio-signal processing modules built-in offers convenience for users, and this make much more advanced system than any other existing BCI and BMI system.