• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.125-138
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• 2023

The development of AI systems for radiation therapy is important to improve the accuracy, effectiveness, and safety of cancer treatment. The current system has the disadvantage of monitoring patients using CCTV, which can cause errors and mistakes in the treatment process, which can lead to misalignment of radiation. Developed the PMRP system, an AI automation system that uses depth cameras to measure patient's fine movements, segment patient's body into parts, align Z values of depth cameras with Z values, and transmit measured feedback to positioning devices in real time, monitoring errors and treatments. The need for such a system began because the CCTV visual monitoring system could not detect fine movements, Z-direction movements, and body part movements, hindering improvement of radiation therapy performance and increasing the risk of side effects in normal tissues. This study could provide the development of a field of radiotherapy that lags in many parts of the world, along with the economic and social importance of developing an independent platform for radiotherapy devices. This study verified its effectiveness and efficiency with data through phantom experiments, and future studies aim to help improve treatment performance by improving the posture correction mechanism and correcting left and right up and down movements in real time.

• Smart Structures and Systems
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• v.19 no.6
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• pp.679-694
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• 2017

The complexity, enlargement and irregularity of structures and multi-directional dynamic loads acting on the structures can lead to unexpected structural behavior, such as torsion. Continuous torsion of the structure causes unexpected changes in the structure's stress distribution, reduces the performance of the structural members, and shortens the structure's lifespan. Therefore, a method of monitoring the torsional behavior is required to ensure structural safety. Structural torsion typically occurs accompanied by displacement, but no model has yet been developed to measure this type of structural response. This research proposes a model for measuring dynamic torsional response of structure accompanied by displacement and for identifying the torsional modal parameter using vision-based displacement measurement equipment, a motion capture system (MCS). In the present model, dynamic torsional responses including pure rotation and translation displacements are measured and used to calculate the torsional angle and displacements. To apply the proposed model, vibration tests for a shear-type structure were performed. The torsional responses were obtained from measured dynamic displacements. The torsional angle and displacements obtained by the proposed model using MCS were compared with the torsional response measured using laser displacement sensors (LDSs), which have been widely used for displacement measurement. In addition, torsional modal parameters were obtained using the dynamic torsional angle and displacements obtained from the tests.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.1-5
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• 2007

In this paper, we propose an unmanned patient monitoring system design and performance of a motion capture and sound detection. Unmanned patient monitoring system can be used in the greek koma and meaning deep sleep patient to need 24 hour surveillance. To monitoring, we used laptop, CCTV camera (or PC camera), A/D converter, microphone and detection program. The detection program based on the frame difference method and sound level meter. It had several functions such as data collecting and storing. All of this system was tested in several the simulations of emergency situations. It can be expected that an unmanned patient monitoring system can be used in emergency situation and patient care.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.1-6
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• 2014

In this paper, we propose an intelligent streetlight system that has a complex sensor module of temperature, humidity, luminance and motion detection and controlled by the fuzzy logic based central monitoring system in order to get flexible and precise manipulation of the streetlight system in USN environment. The proposed streetlight system provides low power consumption and high efficiency by using sensed data from the complex sensor module, which were collected, processed, and analyzed by the fuzzy logic based central monitoring system. The performance of the proposed streetlight system is to be evaluated by a simulation study in terms of power savings and safety at the fields constructed as a test-bed under several suggested scenarios. Finally, we know that the proposed intelligent streetlight system can maximize the energy savings efficiently with the fuzzy logic based central monitoring system and selective remote dimming control by connecting it to the wireless ubiquitous sensor network (USN) using a Zigbee module.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.2
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• pp.104-111
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• 2008

The ECG is biomedical electrical signal occurring on the surface of the body due to the contraction and relaxation of the heart. This signal represents an extremely important measure for health monitoring, as it provides vital information about a patient's cardiac condition and general health. ECG signals are contaminated with high frequency noise such as power line interference, muscle artifact and low frequency nose such as motion artifact. But it is difficult to filter nose from ECG signal, and errors resulting from filtering can distort a ECG signal. The present study implemented a small-size and low-power ECG measurement system that can remove motion artifact for convenient health monitoring during daily life. The implemented ECG monitoring system consists of ECG amplifier, a low power microprocessor, bluetooth module and monitoring program. Amplifier was designed and implemented using low power instrumentation amplifier, and microprocessor was interfaced to the ECG amplifier to collect the data, process, store and feed to a transmitter. And bluetooth module used to wirelessly transmit and receive the vital sign data from the microprocessor to an PC at the receiving site. In order to evaluate the performance of the implemented system, we assessed motion artifact rejection performance in each situation with artificially set condition using adaptive filter.

• Structural Monitoring and Maintenance
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• v.9 no.4
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• pp.359-371
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• 2022

Bridges are critical to the civil engineering infrastructure network as they facilitate movement of people, the transportation of goods and services. Given the aging of bridge infrastructure, federal officials mandate visual inspections biennially to identify necessary repair actions which are time, cost, and labor-intensive. Additionally, the expansion joints of bridges are rarely monitored due to cost. However, expansion joints are critical as they absorb movement from thermal effects, loadings strains, impact, abutment settlement, and vehicle motion movement. Thus, the need to monitor bridge expansion joints efficiently, at a low cost, and wirelessly is desired. This paper addresses bridge joint monitoring needs to develop a cost-effective, real-time wireless system that can be validated in a full-scale bridge structure. To this end, a wireless expansion joint monitoring was developed using commercial-off-the-shelf (COTS) sensors. An in-service bridge was selected as a testbed to validate the performance of the developed system compared with traditional displacement sensor, LVDT, temperature and humidity sensors. The short-term monitoring campaign with the wireless sensor system with the internet protocol version 6 over the time slotted channel hopping mode of IEEE 802.15.4e (6TiSCH) network showed reliable results, providing high potential of the developed system for effective joint monitoring at a low cost.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.401-410
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• 2007

In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.17-21
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• 1989

6-DOE simulator system is designed to real-time processing for motion control, data acquisition, image generation and image processing etc.. In this paper, we introduce hardware and software design technologies for distributed processing, event-trapping, system monitoring and time scheduling procedure in 6-DOF simulator system design.

• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.353-358
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• 1995

The impedance pneumography which is widely used in monitoring respiration is simple to use and noninvasive, but it is sensitive to motion artifacts and insensitive to detect obstructive apnea. A 3-channel respiratory inductive plethysmography (RIP) developed in this study detects inductance change of the inductance band induced by cross-sectional area change of thorax or abdomen as one breathes. It was confirmed that RIP was less sensitive to various motion artifacts but more sensitive to detection of obstructive apnea than impedance pneumography.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.519-526
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• 1990

In this paper we propose the resolved motion controller using a neural network for a robot manipulator. Neural identifier designed by a neural network is trained by using a feedback force as an error signal. The identifier approximates the output of a unknown nonlinear system by monitoring both the input and the output of this system. If the neural network is sufficiently trained well, it does not require either strict modelling of the manipulator or precise parameter estimation. The effectiveness of the proposed controller is demonstrated by computer simulation using a two-link planar robot.