• 한국공작기계학회논문집
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• 제17권1호
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• pp.132-136
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• 2008

Axis of rotation error on rotary system are significant; such as the spindle radial error motion of a aligner, wire bonder and inspector machine which results in the poor state of manufactured goods. In this paper, the simple stage which consists of one PZT actuator and rotary encoder, is analyzed and measured by high resolution capacitance type displacement sensor. As the result of experiment, the paper discusses several issues that must be considered when designing rotary stage driven by PZT.

• 센서학회지
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• 제17권6호
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• pp.447-453
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• 2008

Respiration rate is one of the important vital signs. Photo-plethysmography (PPG) measurement especially on a finger has been widely used in pulse oximetry and also used in estimating respiration rate. It is well known that PPG contains respiration-induced intensity variation (RIIV) signal. However, the accuracy of finger PPG method has been controversial. We introduced a new technique of enhancing motion artifact by respiration. This was achieved simply by measuring PPG on the thorax. We examined the accuracy of these two PPG methods by comparing with two existing methods based on thoracic volume and nostril temperature changes. PPG sensing on finger tip, which is the most common site of measurement, produced 6.1 % error. On the other hand, our method of PPG sensing on the thorax achieved 0.4 % error which was a significant improvement. Finger PPG is sensitive to motion artifact and it is difficult to recover fully small respiratory signal buried in waveform dominated by absorption due to blood volume changes. Thorax PPG is poor to represent blood volumes changes since it contains substantial motion artifact due to respiration. Ironically, this inferior quality ensures higher accuracy in terms of respiration measurement. Extreme low-cost and small-sized LED/silicon detector and non-constrained reflection measurement provide a great candidate for respiration estimation in ubiquitous or personal health monitoring.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2007년도 학술대회
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• pp.191-195
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• 2007

Recently, landslides frequently happen at a natural slope during period of intensive rainfall. With rapidly increasing population of steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is developed. The system is focused to debris flows which happen frequently during periods of intensive rainfall at steep slopes in Kangwondo. This system is based on the wireless sensor network that is composed of sensor nodes, gateway, and server system. Sensor nodes that are composed of sensing part and communication part are newly developed to detect sensitive ground movement. Sensing part is designed to measure tilt angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15. I) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of laboratory tests is performed at a small-scale earth slope supplying rainfall by artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope failure starts. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs, and can be applied to ubiquitous computing city (U-City) that is characterized by disaster free.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.369-372
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• 2008

Recently, landslides have frequently occurred on natural slopes during periods of intense rainfall. With a rapidly increasing population on or near steep terrain in Korea, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is introduced. The system is focused to debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of sensor nodes, gateway, and server system. Sensor nodes comprising a sensing part and a communication part are developed to detect ground movement. Sensing part is designed to measure inclination angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15.1) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of experimental studies was performed at a small-scale earth slope equipped with an artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope starts to move. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs.

• 대한인간공학회지
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• 제31권4호
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• pp.551-556
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• 2012

Objective: This study presents the effect of visual feedback on one-hand gesture performance in vision-based gesture recognition system when people use gestures to control a screen device remotely. Backgroud: gesture interaction receives growing attention because it uses advanced sensor technology and it allows users natural interaction using their own body motion. In generating motion, visual feedback has been to considered critical factor affect speed and accuracy. Method: three types of visual feedback(arrow, star, and animation) were selected and 20 gestures were listed. 12 participants perform each 20 gestures while given 3 types of visual feedback in turn. Results: People made longer hand trace and take longer time to make a gesture when they were given arrow shape feedback than star-shape feedback. The animation type feedback was most preferred. Conclusion: The type of visual feedback showed statistically significant effect on the length of hand trace, elapsed time, and speed of motion in performing a gesture. Application: This study could be applied to any device that needs visual feedback for device control. A big feedback generate shorter length of motion trace, less time, faster than smaller one when people performs gestures to control a device. So the big size of visual feedback would be recommended for a situation requiring fast actions. On the other hand, the smaller visual feedback would be recommended for a situation requiring elaborated actions.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.551-560
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• 2023

Recently, there has been significant research into the recognition of human activities using three-dimensional sequential skeleton data captured by the Kinect depth sensor. Many of these studies employ deep learning models. This study introduces a novel feature selection method for this data and analyzes it using machine learning models. Due to the high-dimensional nature of the original Kinect data, effective feature extraction methods are required to address the classification challenge. In this research, we propose using the first four moments as predictors to represent the distribution of joint sequences and evaluate their effectiveness using two datasets: The exergame dataset, consisting of three activities, and the MSR daily activity dataset, composed of ten activities. The results show that the accuracy of our approach outperforms existing methods on average across different classifiers.

• The Journal of Korean Physical Therapy
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• 제31권6호
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• pp.333-338
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• 2019

Purpose: Although previous studies on the screw-home movement (SHM) for autopsy specimen and walking of living persons conducted, the possibility of acquiring SHM based on inertial measurement units received little attention. This study aimed to investigate the possibility of measuring SHM for the non-weighted bearing using a micro-electro-mechanical system-based wearable motion capture system (MEMSS). Methods: MEMSS and camera-based motion analysis systems were used to obtain kinematic data of the knee joint. The knee joint moved from the flexion position to a fully extended position and then back to the start point. The coefficient of multiple correlation and the difference in the range of motion were used to assess the waveform similarity in the movement measured by two measurement systems. Results: The waveform similarity in the sagittal plane was excellent and the in the transverse plane was good. Significant differences were found in the sagittal plane between the two systems (p<0.05). However, there was no significant difference in the transverse plane between the two systems (p>0.05). Conclusion: The SHM during the passive motion without muscle contraction in the non-weighted bearing appeared in the entire range. We thought that the MEMSS could be easily applied to the acquisition of biomechanical data on the knee related to physical therapy.

• Journal of Acupuncture Research
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• 제31권4호
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• pp.11-19
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• 2014

Objectives : Acupuncture manipulation, a kind of sophisticated hand movements, has been considered a fundamental skill for acupuncture practice. In this study, we aimed to develop acupuncture manipulation education system(AMES) using visual feedback of acupuncture manipulation. We also investigated whether or not acupuncture practice-$na{\ddot{i}}ve$ students could enhance their acupuncture manipulation skills after AMES training. Methods : Using AMES and motion sensor, we visualized a time-series motion template(intended motion) and participant's own motion(actual motion) manipulating an acupuncture needle. Ten students were trained with complex lifting/thrusting techniques for 8 training trials. We compared the motion pattern error of the students between the first and the last trials. Results : In our pilot experiment, half of the participants showed significantly improved manipulation skills in complex lifting/thrusting techniques after training with AMES which is developed in this study, while the other half of the participants did not show significant improvements. Conclusions : The AMES could be useful in acupuncture-manipulation training for students. Our findings suggest that novice can improve sophisticated hand movement for acupuncture manipulation with sensorimotor learning using visual feedback.

• 제어로봇시스템학회논문지
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• 제13권11호
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• pp.1092-1098
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• 2007

A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

• Journal of information and communication convergence engineering
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• 제15권4호
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• pp.244-249
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• 2017

Wearable sensor-based gait analysis has been widely conducted to analyze various aspects of human ambulation abilities under the free-living condition. However, there have been few research efforts on using wearable sensors to analyze human walking on an unstable surface such as on a ship during a sea voyage. Since the motion of a ship on the unstable sea surface imposes significant differences in walking strategies, investigation is suggested to find better performing wearable sensor-based gait analysis algorithms on this unstable environment. This study aimed to compare two representative gait event algorithms including time domain and frequency domain analyses for detecting heel strike on an unstable platform. As results, although two methods did not miss any heel strike, the frequency domain analysis method perform better when comparing heel strike timing. The finding suggests that the frequency analysis is recommended to efficiently detect gait event in the unstable walking environment.