• Journal of Biomedical Engineering Research
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• v.41 no.5
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• pp.185-194
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• 2020

Arrhythmia is basically diagnosed with the electrocardiogram (ECG) signal, however, ECG is difficult to measure and it requires expert help in analyzing the signal. On the other hand, the radial pulse can be measured with easy and uncomplicated way in daily life, and could be suitable bio-signal for the recent untact paradigm and extensible signal for diagnosis of Korean medicine based on pulse pattern. In this study, we developed an irregular radial pulse detection algorithm based on a learning model and considered its applicability as arrhythmia screening. A total of 1432 pulse waves including irregular pulse data were used in the experiment. Three data sets were prepared with minimal preprocessing to avoid the heuristic feature extraction. As classification algorithms, elastic net logistic regression, random forest, and extreme gradient boosting were applied to each data set and the irregular pulse detection performances were estimated using area under the receiver operating characteristic curve based on a 10-fold cross-validation. The extreme gradient boosting method showed the superior performance than others and found that the classification accuracy reached 99.7%. The results confirmed that the proposed algorithm could be used for arrhythmia screening. To make a fusion technology integrating western and Korean medicine, arrhythmia subtype classification from the perspective of Korean medicine will be needed for future research.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.187-190
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• 2002

Confocal microscopy is very popular technology in bio-medical inspection due to its ability to reject background signals and to measure very thin slide of thick specimens, which is called optical sectioning. But intensity of detected signal in fluorescence type confocal microscopy is so small that only 0.2% of emitted fluorescence light can be detected in the best case. In this paper, we proposed the reflecting optical system to improve the detection intensity and designed the optical system by optimal design method. At the end of the paper, we analyzed the characteristics of the proposed reflecting optical system.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.571-576
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• 2022

Due to the epochal development of the unmanned technology, the importance of LDT(: Location Detection Technology), which accurately estimates the location of a user or object, is dramatically increased. TOA(: Time of Arrival), which calculates a location by measuring the arrival time of signals, and TDOA(: Time Difference of Arrival) which calculates it by measuring the difference between two arrival times, are representative LDT methods. Based on the signals received from three or more base stations, TOA calculates an intersection point by drawing circles and TDOA calculates it by drawing hyperbolas. In order to improve the radio shadow area problem, a huge number of repeaters have been installed in the urban area, but the signals received through these repeaters may cause the serious error for estimating a location. In this paper, we propose an efficient location estimation technique using the signal received through the repeater. The proposed approach estimates the location of MS(: Mobile Station) employing TOA and TDOA methods, based on signals received from one repeater and two BS(: Base Station)s.

• Mass Spectrometry Letters
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• v.6 no.4
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• pp.85-90
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• 2015

This article reviews recent analytical techniques using inductively coupled plasma-mass spectrometry (ICP-MS) immunoassay for clinical and bio analysis. We classified the techniques into two categories, direct and indirect analysis, which depend upon a guideline of whether tagging materials are used or not. Direct analysis is well known, and generally used in conjunction with various other techniques, such as laser ablation, chromatographic separations, etc. Recently, indirect analysis using tagging elements has intensively been discussed because of its importance in future applications to bio and clinical analysis, including environmental and food industries. The method has shown advantages of multiplex detection, excellent sensitivity, and short analysis time owing to signal amplification and magnetic separation. Now, it expands the application field from small biomolecules to large cells.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1735-1736
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• 2008

In this research, a riding robot system named as "RideBot" is developed for health-care and entertainments. The developed riding robot can follow the intention of horseman and can simulate the motion of horse. The riding robot mechanisms are used for many functions of attitude detection, motion sensing, recognition, common interface and motion-generations. This riding robot can react on health conditions, bio-signals and intention informations of user. One of the objectives of this research is that the riding robot could catch user motion and operate spontaneous movements. In this paper, we develope the saddle mechanism which can generate 3 degrees-of-freedom riding motion based on the intention of horseman. Also, we develope reins and spur mechanism for the recognition of the horseman's intention estimation and the bio-signal monitoring system for the health care function of a horseman. In order to evaluate the performance of the riding robot system, we tested several riding motions including slow and normal step motion, left and right turn motion.

• Bulletin of the Korean Chemical Society
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• v.35 no.1
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• pp.25-29
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• 2014

This research was aimed to fabricate an optical fiber-based SERS substrate which can detect dopamine neurotransmitters. Chitosan nanoparticles (NPs) were firstly anchored on the surface of optical fiber, and then gold layer was subsequently deposited on the anchored chitosan NPs via electroless plating method. Finally, chitosan-gold nanocomposites combined with optical fiber reacted with dopamine molecules of 100-1500 mg/day which is a standard daily dose for Parkinson's disease patients. The amplified Raman signal at $1348cm^{-1}$ obtained from optical fiber-based SERS substrate was plotted versus dopamine concentrations (1-10 mM), demonstrating an approximate linearity of Y = 303.03X + 2385.8 ($R^2$ = 0.97) with narrow margin errors. The optical fiber-based Raman system can be potentially applicable to in-vitro (or in-vivo) detection of probe molecules.

• BioChip Journal
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• v.16
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• pp.49-57
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• 2020

During living donor liver transplantation, a number of blood vessels and bile ducts are anastomosed while the liver and gallbladder are resected in the donor and recipient. Early detection and treatment of complications after surgery by evaluating the function of blood vessels and the biliary tract is crucial. A biosensing chip that can monitor patient health status from the bile excreted during the recovery process has been developed using a surface-enhanced Raman sensing chip. Surface-enhanced Raman spectroscopy signals of bile obtained from normal bile duct ligation and gallbladder damage mouse models using a cautery device were identified and analyzed. The surface-enhanced Raman chip with a nanometer-level porous structure can selectively separate the nanometer biomarkers and measure the Raman signal. Through the detection of nanometer biomarkers in the bile and comparative analysis of histopathology, the Raman signal in the damaged gallbladder was compared with that caused by liver damage due to bile duct ligation, showing that it becomes a biosensing chip for monitoring recovery.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.16-23
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• 2022

Cardiac disease is the most common cause of death worldwide. Therefore, detection and classification of electrocardiogram (ECG) signals are crucial to extend life expectancy. In this study, we aimed to implement an artificial intelligence signal recognition system in field programmable gate array (FPGA), which can recognize patterns of bio-signals such as ECG in edge devices that require batteries. Despite the increment in classification accuracy, deep learning models require exorbitant computational resources and power, which makes the mapping of deep neural networks slow and implementation on wearable devices challenging. To overcome these limitations, spiking neural networks (SNNs) have been applied. SNNs are biologically inspired, event-driven neural networks that compute and transfer information using discrete spikes, which require fewer operations and less complex hardware resources. Thus, they are more energy-efficient compared to other artificial neural networks algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.331-339
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• 2008

Nowadays with advancement in technology and aging society, the number of disabled citizens is increasing. The disabled citizens always need a caretaker for daily life routines especially for mobility. In future, the need is considered to increase more. To reduce the burden from the disabled, various devices for healthcare are introduced using computer technology. The power wheelchair is an important and convenient mobility device. The demand of power wheelchair is increasing for assistance in mobility. In this paper we proposed a robotic wheelchair for mobility aid to reduce the burden from the disabled. The main issue in an autonomous wheelchair is the automatic detection and avoidance of obstacles and going to the pre-designated place. The proposed algorithm detects the obstacles and avoids them to drive the wheelchair to the desired place safely. By this way, the disabled will not always have to worry about paying deep attention to the surroundings and his path. User has a handheld bio-sensor monitoring system for get user's bio-signal. If user detects unusual signal, alarm send to protector.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.12
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• pp.82-87
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• 2016

The photoplethysmogram (PPG) signal is one of the mainly considered bio signals along with the electrocardiogram (ECG) signal. PPG signals can be used to estimate the speed of flow of blood in vein, saturation of peripheral oxygen and etc. The heartbeat rate is a common feature in order to evaluate those checkup lists. To estimate the correct heartbeat rate, dynamic noises must be removed in the PPG signal. Conventionally, the acceleration signal is used to remove dynamic noises. This method, however, increases the computational complexity. In this paper, we proposes a solution that uses only PPG signals to calculate the heartbeat rate, and which can be used as a basement in real-time healthcare solution.