• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1280-1287
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• 2019

For developing a wireless implantable device to monitoring the artery variation in real-time. The concept of a special vessel variation measurement capacitive sensor is presented in this paper. The sensor consists of two part; main sensor to measuring the arterial variation, and reference sensor is used to improve the accuracy of the capacitance value variation. Before sensor manufacture, a model of the sensor attached on the artery was designed in 3D to conduct in the FEA simulation to validate the validity and feasibility of the idea. The artery model was designed as layered structures and made of collagenous soft tissues with intima inside, followed by the media and the adventitia. Also, a grease layer was designed in the inner of the arterial wall to imitate the clogged arteries. The simulation was divided into two parts; sensor performance test by changing the diameter of the grease layer, and arterial wall tension test by changing the blood pressure. As the simulation results, the capacitance value measured by the proposed sensor is decreased follow the diameter of the grease increased. Also, large elastic deformation of the arterial wall since changing the blood pressure has been observed.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.221-228
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• 2024

As the importance of cardiovascular health is highlighted, research on its correlation with blood pressure, the most important indicator, is being actively conducted. Therefore, extensive clinical data is essential, but the measurement of the central arterial blood pressure waveform must be performed invasively within the artery, so the quantity and quality are limited. This study suggested a mock circulatory robot and artificial aorta to reproduce the blood pressure waveform generated by the overlap of forward and reflected waves. The artificial aorta was fabricated with biomimetic silicone to mimic the physiological structure and vascular stiffness of the human. A pressurizing chamber was implemented to prevent distortion of the blood pressure waveform due to the strain-softening of biomimetic silicone. The reproduced central arterial blood pressure waveforms have similar magnitude, shape, and propagation characteristics to humans. In addition, changes in blood pressure waveform due to aging were also reproduced by replacing an artificial aorta with various stiffness. It can be expanded to construct a biosignal database and health sensor testing platform, a core technology for cardiovascular health-related research.

• Korean Journal of Materials Research
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• v.32 no.11
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• pp.508-514
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• 2022

Piezoelectric composite films which are enabled by inorganic piezoelectric nanomaterials-embedded polymer, have attracted enormous attention as a sustainable power source for low powered electronics, because of their ease of fabrication and flexible nature. However, the absorption of applied stress by the soft polymeric matrices is a major issue that must be solved to expand the fields of piezoelectric composite applications. Herein, a flexible and porous piezoelectric composite (piezoelectric sponge) comprised of BaTiO₃ nanoparticles and polydimethylsiloxane was developed using template method to enhance the energy conversion efficiency by minimizing the stress that vanishes into the polymer matrix. In the porous structure, effective stress transfer can occur between the piezoelectric active materials in compression mode due to direct contact between the ceramic particles embedded in the pore-polymer interface. The piezoelectric sponge with 30 wt% of BaTiO₃ particles generated an open-circuit voltage of ~12 V and a short-circuit current of ~150 nA. A finite element method-based simulation was conducted to theoretically back up that the piezoelectric output performance was effectively improved by introducing the sponge structure. Furthermore, to demonstrate the feasibility of pressure detecting applications using the BaTiO₃ particles-embedded piezoelectric sponge, the composite was arranged in a 3 × 3 array and integrated into a single pressure sensor. The fabricated sensor array successfully detected the shape of the applied pressure. This work can provide a cost-effective, biocompatible, and structural strategy for realizing piezoelectric composite-based energy harvesters and self-powered sensors with improved energy conversion efficiency.

• Journal of Magnetics
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• v.17 no.4
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• pp.302-307
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• 2012

We have designed, fabricated and tested an integrated microfluidic chip with a Planar Hall Effect (PHE) sensor. The sensor was constructed by sequentially sputtering Ta/NiFe/Cu/NiFe/IrMn/Ta onto glass. The microfluidic channel was fabricated with poly(dimethylsiloxane) (PDMS) using soft lithography. Magnetic nanoparticles suspended in hexadecane were used as ferrofluid, of which the saturation magnetisation was 3.4 emu/cc. Droplets of ferrofluid were generated in a T-junction of a microfluidic channel after hydrophilic modification of the PDMS. The size and interval of the droplets were regulated by pressure on the ferrofluid channel inlet. The PHE sensor detected the flowing droplets of ferrofluid, as expected from simulation results. The shape of the signal was dependent on both the distance of the magnetic droplet from the sensor and the droplet length. The sensor was able to detect a magnetic moment of $2{\times}10^{-10}$ emu at a distance of 10 ${\mu}m$. This study provides an enhanced understanding of the magnetic parameters of ferrofluid in a microfluidic channel using a PHE sensor and will be used for a sample inlet module inside of integrated magnetic lab-on-a-chip systems for the analysis of biomolecules.

• Journal of Sensor Science and Technology
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• v.7 no.1
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• pp.9-16
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• 1998

This paper describes how the directivity pattern of the scattered sound pressure is distributed when a plane acoustic wave is incident on a rigid or soft spherical shell underwater. A coupled Finite Element-Boundary Element method is developed as a numerical technique. The result of the coupled FE-BE method is agreed with theoretical solution for algorithmic confirmation.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.10-17
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• 2008

The purpose of this thesis is to reduce of error for source location through acoustic emission(AE) signal, generated elastic wave from crack growth to leak for facility diagnosis. Especially, in order to overcome noise from original signal, this paper proposed enhancement of source location by using noise reduction based on wavelet transform. To evaluate actual performance in experiments, Pencil Lead Break is used crack signal source on the aluminum plate and drain valve of air compressor is used as substitute pressure vessel to generate leak signal. In signal processing, wavelet shrinkage and soft threshold are used to discriminate signal source and then source location techniques have been effectively used with group velocity using material property and time difference between sensor using cross correlation. Source location for crack and leak test have some difference, but the result show that improved 30% with a average length within 10.46mm in crack test and improved 2% compare with average filter in leak test when we applied wavelet transform.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.357-360
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• 1997

Abstract: In teleoperation field robotic system such as hydraulically actuated robotic excavator, the maneuverability and convenience is the most important part in the operation of robotic excavator. Particularly the force information is important in dealing with digging and leveling operation in the teleoperated excavator. Excavators are also subject to a wide variation of soil-tool interaction forces. This paper presents a new force reflecting joystick in a velocity-force type bilateral teleoperation system. The master system is electrical joystick and the slave system IS hydraulically actuated cylinder with linear position sensor. Particularly Pneumatic motor is used newly in the master joystick for force reflection and the information of the pressure of salve cylinder is measured and utilized as the force feedback signal. Also force-reflection gain greatly affects the excavation performance of a hydraulically actuated robotic system and it is very difficult to determine it appropriately since slave excavator contacts with various environments such as from soft soil to rock. To overcome this, this paper proposes a force-reflection gain selecting algorithm based on artificial neural network and fuzzy logic.

• Smart Structures and Systems
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• v.5 no.2
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• pp.153-171
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• 2009

In this paper, the analytical fault detection and diagnosis (FDD) is presented using model-based and signal-based methodology with wavelet analysis on signals obtained from sensors and sensor networks. In the model-based FDD, we present the modeling of contact interface found in soft materials, including the biomedical contacts. Fingerprint analysis and signal-based FDD are also presented with an experimental framework consisting of a mechanical pneumatic system typically found in manufacturing automation. This diagnosis system focuses on the signal-based approach which employs multi-resolution wavelet decomposition of various sensor signals such as pressure, flow rate, etc., to determine leak configuration. Pattern recognition technique and analytical vectorized maps are developed to diagnose an unknown leakage based on the established FDD information using the affine mapping. Experimental studies and analysis are presented to illustrate the FDD methodology. Both model-based and wavelet-based FDD applied in contact interface and manufacturing automation have implication towards better quality of life by applying theory and practice to understand how effective diagnosis can be made using intelligent FDD. As an illustration, a model-based contact surface technology an benefit the diabetes with the detection of abnormal contact patterns that may result in ulceration if not detected and treated in time, thus, improving the quality of life of the patients. Ultimately, effective diagnosis using FDD with wavelet analysis, whether it is employed in biomedical applications or manufacturing automation, can have impacts on improving our quality of life.