Korea Advanced Institute of Science and Technology · Engineering
Professor Yong-Hwa Park's research lab specializes in microelectromechanical systems (MEMS) and micro-opto-electromechanical systems (MOEMS), with a strong focus on energy loss mechanisms in resonant devices, particularly anchor loss in MEMS resonators. The lab develops advanced computational multiphysics models to predict Q-factor and design sensitivity, integrating beam dynamics, substrate wave propagation, and electrostatic actuation. In parallel, the lab explores biomedical applications, including AI-driven cough detection using sound cameras and robot-assisted gait training for stroke rehabilitation. The research also extends into bio-inspired bioprocessing, such as mycelial penicillin fermentation using carrier-supported growth. These diverse yet interconnected areas reflect a core mission of designing high-performance, miniaturized, and intelligent microsystems for healthcare and sensing applications.
Figures are computed from collected data and may differ slightly.
A computational model is developed for the prediction of wave propagation in the substrate of a MEMS resonator to study energy loss mechanisms from the vibrating beams to the substrate, viz., anchor loss. The model employs a modified classical Fourier transform method under periodic excitations at the anchor area. The present substrate model, when applied to a typical commercially fabricated substrate, estimates that the anchor loss of an ends-anchored resonator with its center frequency of 50 M
A carrier-supported mycelial growth of Penicillium chrysogenum was applied to penicillin fermentation system using celite as a support material. Hyphal growth through the pore matrices of the material showed strong anchorages and provided highly stable biofilm growth. With bioparticles developed in such a manner, both cell growth and penicillin production were observed to increase significantly compared to the conventional dispersed filamentous cultures. Maximum values of specific penicillin pro
Coughing is a typical symptom of COVID-19. To detect and localize coughing sounds remotely, a convolutional neural network (CNN) based deep learning model was developed in this work and integrated with a sound camera for the visualization of the cough sounds. The cough detection model is a binary classifier of which the input is a two second acoustic feature and the output is one of two inferences (<i>Cough</i> or <i>Others</i>). Data augmentation was performed on the collected audio files to al
A computational multiphysics model of the coupled beam-substrate-electrostatic actuation dynamics of MEMS resonators has been developed for the model-based prediction of Q-factor and design sensitivity studies of the clamped vibrating beam. The substrate and resonator beam are modeled independently and then integrated by enforcing their interface compatibility condition and the force equilibrium to arrive at the multiphysics model. The present model has been validated with several reported singl
A 20-MHz switching high-speed light-modulating device for three-dimensional (3-D) image capturing and its system prototype are presented. For 3-D image capturing, the system utilizes a time-of-flight (TOF) principle by means of a 20-MHz high-speed micromachined electro-absorptive modulator, the so-called optical shutter. The high-speed modulation is obtained by utilizing the electro-absorption mechanism of the multilayer structure, which has an optical resonance cavity and light-absorption epila
This study presents a design and evaluation of a mock circulatory platform, which can reproduce blood pressure and its waveforms to provide palpation experience based on the human cardiovascular physiology. To reproduce the human cardiovascular behavior, especially the blood pressure, the proposed platform includes three major modules: heart, artery and reservoir modules. The heart module reproduces source pressure exerted on the whole system with a controlled time-profile. The artery module con
Robot-assisted gait training (RAGT) is at the cutting edge of stroke rehabilitation, offering a groundbreaking method to improve motor recovery and enhance the quality of life for stroke survivors. This review investigates the effectiveness and application of various RAGT systems, including both end-effector and exoskeleton robots, in facilitating gait enhancements. The selection process for this comprehensive analysis involved a meticulous review of the literature from databases such as PubMed,
20 Mega-Hertz-switching high speed image shutter device for 3D image capturing and its application to system prototype are presented. For 3D image capturing, the system utilizes Time-of-Flight (TOF) principle by means of 20MHz high-speed micro-optical image modulator, so called 'optical shutter'. The high speed image modulation is obtained using the electro-optic operation of the multi-layer stacked structure having diffractive mirrors and optical resonance cavity which maximizes the magnitude o
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