• Journal of Biomedical Engineering Research
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• v.40 no.1
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• pp.32-37
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• 2019

In this study, we designed a blending algorithm for rate adaptive pacing for cardiac pacemaker. Generally, rate adaptive pacing (RAP) is applied to patients whose heart rate does not rise during exercise for chronotropic incompetence (CI) patient. It is very important to develop an algorithm for RAP that can be properly applied to CI patients. In order to design an RAP algorithm we used dual sensors. Firstly, we designed a bio-signal measurement system based on the dual sensors, which are accelerometer and respiratory system. Secondly, we conducted treadmill test for the simulation experiment while using 3-lead ECG as reference. Finally, we designed a blending algorithm based on activation state of the dual sensors. The proposed blending algorithm was subdivided into three sections based on the accelerometer signal, which are rapidly increased section (W1), hardly changed section (W2), and decreased section (W3). Each weight is set aside for each section. To evaluate this algorithm, ten healthy adult males were participated. The correlation and Root Mean Square Error between the proposed algorithm and the reference were compared, and shown to be r=0.88 and 2.82 bpm, respectively. These results show that the proposed blending algorithm of dual sensors enables proper tracking of the heart rate during exercise. Also, it shows the possibility that the proposed blending algorithm can be applied to improve quality of life of the chronotropic incompetence patient.

• Physical Therapy Rehabilitation Science
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• v.8 no.1
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• pp.32-39
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• 2019

Objective: The aim of this study is to investigate the effects of whole body vibratory stimulation on muscle strength, balance, and fall efficacy among super-aged women. Design: Randomized controlled trial. Methods: Twenty-eight super-aged women over 80 years of age were assigned to either the experimental group (n=14) and control group (n=14). The experimental group received an exercise program that used the whole body vibratory stimulation with a frequency of 30 Hz and amplitude of 3 mm, and the control group received an exercise program without vibratory stimulation. Intervention was provided for 4 weeks, 3 sessions per week, and 30 minutes per session. In order to measure lower extremity muscle strength the 30-second chair stand test (CST) was used. The Berg Balance Scale (BBS) was used to measure dynamic balance. Static balance was measured by tracking the path length, velocity, and area of the center of pressure (CoP). The Falls Efficacy Scale (FES) was used to measure the subjects' fear of falling. Results: Both the experimental and control group demonstrated statistically significant increase in muscle strength, dynamic balance, and fall efficacy (p<0.05). Only the experimental group showed significant improvements in static balance before and after the intervention (p<0.05). The experimental group showed significantly greater improvements in CST, BBS, and CoP (path length, velocity) than control group (p<0.05). Conclusions: Whole body vibratory stimulation exercise is shown to be a safe and appropriate physical therapy intervention method to enhance muscle strength, balance, and fall efficacy of super-aged women.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.1
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• pp.38-48
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• 2020

In order to inspect the existing or newly constructed ship's hull, a professional diver directly inspects the ship's bottom of the water. However, since it is a work done by people, there are many dangers such as human casualties and crashes. To solve this problem, it is necessary to develop underwater drones for ship inspection for visual inspection. The technology applied to underwater drones, the use and manufacturing process of each component, and the method of manufacture such as firmware development were described, and the difference was compared by measuring the drone's own driving ability and driving ability using crawler under water, and the location tracking device test confirmed the error from the actual location. It is estimated that the use of underwater drones produced through this research will prevent human casualties and achieve economic effects and stability.

• Smart Structures and Systems
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• v.31 no.4
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• pp.421-436
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• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.107-113
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• 2023

This paper proposes a method for detecting smoking behavior in images using artificial intelligence technology. Since smoking is not a static phenomenon but an action, the object detection technology was combined with the posture estimation technology that can detect the action. A smoker detection learning model was developed to detect smokers in images, and the characteristics of smoking behaviors were applied to posture estimation technology to detect smoking behaviors in images. YOLOv8 was used for object detection, and OpenPose was used for posture estimation. In addition, when smokers and non-smokers are included in the image, a method of separating only people was applied. The proposed method was implemented using Google Colab NVIDEA Tesla T4 GPU in Python, and it was found that the smoking behavior was perfectly detected in the given video as a result of the test.

• Fisheries and Aquatic Sciences
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• v.26 no.5
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• pp.355-365
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• 2023

The Pacific abalone, Haliotis discus hannai, is a highly valued and industrially important aquaculture species with growing demands of the expanding abalone aquaculture industry. To explore the feasibility of using the brown alga, Sargassum horneri, as a potential substitute for abalone feed, it is important to identify the feed preference and attractant effect of S. horneri on Pacific abalone. Our experiments indicated that the feeding-associated movement of abalone could be detected using a video tracking system under indirect illumination with dim red light. To further analyze the attraction potentials of various test materials, preference analysis was performed using Avicel-coated glass plates with ground powders of various seaweeds (e.g., S. horneri, Saccharina japonica, and Undaria pinnatifida) and commercial abalone feed, together with coffee waste. Heat map analysis indicated greater attraction by the kelp S. japonica than by S. horneri and commercial feed, which showed similar preference levels. Feeding preference based on the area of Avicel eaten by abalone showed a significant preference for U. pinnatifida over S. horneri (feeding area: 68.6 ± 20.1% vs. 37.5 ± 22.4%, p < 0.05). Additionally, the feeding area was significantly greater for plates with S. japonica than for plates with S. horneri (44.0 ± 16.6% vs. 22.6 ± 15.4%, p < 0.05). There was no significant difference in feeding area between commercial feed and S. horneri (31.7 ± 11.6% vs. 31.6 ± 20.2%, p > 0.05). The methanol extracts attracted abalone in the following order: U. pinnatifida > S. horneri > S. japonica > commercial feed > coffee waste. To determine the attractive effects of the components of methanol extracts, mixtures of methanol extracts of commercial feed with increasing amounts of S. horneri were examined. The results showed a significant increase in feeding preference upon addition of S. horneri up to 50% and 75%, suggesting its potential for use as an appetite-enhancing feed additive. This study identified conditions that can be successfully used to monitor the movement of Pacific abalone; the results of preference analysis confirmed that abalone exhibited similar attraction and feeding preference for S. horneri, compared with commercial feed.

• Computers and Concrete
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• v.31 no.5
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• pp.457-468
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• 2023

Buildings, bridges, and dams are examples of civil infrastructure that play an important role in public life. These structures are prone to structural variations over time as a result of external forces that might disrupt the operation of the structures, cause structural integrity issues, and raise safety concerns for the occupants. Therefore, monitoring the state of a structure, also known as structural health monitoring (SHM), is essential. Owing to the emergence of the fourth industrial revolution, next-generation sensors, such as wireless sensors, UAVs, and video cameras, have recently been utilized to improve the quality and efficiency of building forensics. This study presents a method that uses a target-based system to estimate the dynamic displacement and its corresponding dynamic properties of structures using UAV-based video. A laboratory experiment was performed to verify the tracking technique using a shaking table to excite an SDOF specimen and comparing the results between a laser distance sensor, accelerometer, and fixed camera. Then a field test was conducted to validate the proposed framework. One target marker is placed on the specimen, and another marker is attached to the ground, which serves as a stationary reference to account for the undesired UAV movement. The results from the UAV and stationary camera displayed a root mean square (RMS) error of 2.02% for the displacement, and after post-processing the displacement data using an OMA method, the identified natural frequency and damping ratio showed significant accuracy and similarities. The findings illustrate the capabilities and reliabilities of the methodology using UAV to evaluate the dynamic properties of structures.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.210-217
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• 2022

Passive source depth estimation has been studied for decades since the source depth can be used for target classification, target tracking, etc. The purpose of this paper is to solve the problem of ambiguity in the previous paper [S.-il. Cho et al. (in Korean), J. Acoust. Soc. Kr. 38, 120-127 (2019)] that source depth is estimated in two points. The patterns of phase shift of Channel Impulse Response(CIR) reflected in ocean surface and bottom is used for removing ambiguity of the source depth estimation, and after removing ambiguity, source depth is estimated at one point through the intersection of CIR. In order to extract CIR in case of unknown source signal and continuous signal or noise, Ray-based blind deconvolution is used. The proposed algorithm is demonstrated through numerical simulation in ocean waveguide.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.329-332
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.280-283
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• 2022

This study aims to identify problems with existing e-learning content and non-face-to-face class methods, improve students' concentration, improve class achievement and educational effectiveness, and propose an artificial intelligence class system design using a web server. By using the function of face and eye tracking using OpenCV to identify attendance and concentration, and by inducing feedback through voice or message to questions asked by the instructor in the middle of class, learners relieve boredom caused by online classes and test by runner If the score is not reached, we propose an artificial intelligence education program system design that can bridge the academic gap and improve academic achievement by providing educational materials and videos for the wrong problem.