• Journal of Drive and Control
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• v.17 no.4
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• pp.8-14
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• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.

• Korean Journal of Applied Biomechanics
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• v.26 no.3
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• pp.243-248
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• 2016

Objective: The aim of this study was to determine the kinematical characteristics of somersault with twist in the Lou Yun and Akopian motions and to provide useful information to gymnastic athletes in men's vault. Method: The study subjects were 12 male adult top athletes. After 12 trials (7 Lou Yun and 5 Akopian trials) filmed by using two digital high-speed camcorders set at 90 frames/sec, kinematical data were collected through the direct linear transformation (DLT) method. The mean differences in biomechanical variables were compared during the second flight upward phase. The kinematic characteristics of somersault with twist in the Lou Yun and Akopian motions were identified. Results: In Lou Yun motion, the vertical release velocity through horse breaking was not difficult to obtain, so the athletes had enough time to prepare for the twist. Therefore, the Lou Yun motion has an advantage to make a cat twist in the pike posture. In the Akopian motion, obtaining the horizontal velocity through horse pushing was so easy that the Akopian athletes attained a large angular impulse and angular momentum. Therefore, the Akopian motion has an advantage to making a tilt twist in the body tilting posture. Conclusion: This study suggests that gymnastic athletes should control their body segment movements in order to increase the twisting angular velocity of the whole body, which requires regulation of the longitudinal moment of inertia of the body. Moreover, athletes should prepare for the shoulder and hip twists early in order to make the landing position in advance.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.3
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• pp.199-206
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• 2016

Most Koreans walk having their toes in or out, because of their sedentary lifestyles. In addition, using smartphone while walking makes having a desirable walking posture even more difficult. The goal of this study is to make a simple system which easily analyze and inform any person his or her personal walking habit. To discriminate gait patterns, we developed a gait monitoring system using a 3-axis accelerometer and a foot pressure monitoring system. The developed system, with an accelerometer and a few pressure sensors, can acquire subject's foot pressure and how tilted his or her torso is. We analyzed the relationship between type of gate and sensor data using this information. As the result of analysis, we could find out that statistical parameters like standard deviation and root mean square are good for discriminating among torso postures, and k-nearest neighbor algorithm is good at clustering gait patterns. The developed system is expected to be applicable to medical or athletic fields at a low price.

• Journal of Korean Neurosurgical Society
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• v.55 no.3
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• pp.148-151
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• 2014

Objective : Posture-induced radial neuropathy, known as Saturday night palsy, occurs because of compression of the radial nerve. The clinical symptoms of radial neuropathy are similar to stroke or a herniated cervical disk, which makes it difficult to diagnose and sometimes leads to inappropriate evaluations. The purpose of our study was to establish the clinical characteristics and diagnostic assessment of compressive radial neuropathy. Methods : Retrospectively, we reviewed neurophysiologic studies on 25 patients diagnosed with radial nerve palsy, who experienced wrist drop after maintaining a certain posture for an extended period. The neurologic presentations, clinical prognosis, and electrophysiology of the patients were obtained from medical records. Results : Subjects were 19 males and 6 females. The median age at diagnosis was 46 years. The right arm was affected in 13 patients and the left arm in 12 patients. The condition was induced by sleeping with the arms hanging over the armrest of a chair because of drunkenness, sleeping while bending the arm under the pillow, during drinking, and unknown. The most common clinical presentation was a wrist drop and paresthesia on the dorsum of the 1st to 3rd fingers. Improvement began after a mean of 2.4 weeks. Electrophysiologic evaluation was performed after 2 weeks that revealed delayed nerve conduction velocity in all patients. Conclusion : Wrist drop is an entrapment syndrome that has a good prognosis within several weeks. Awareness of its clinical characteristics and diagnostic assessment methods may help clinicians make diagnosis of radial neuropathy and exclude irrelevant evaluations.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.361-368
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• 2022

The purpose of this study was to develop a hand rehabilitation training system for hemiplegic patients. We also tried to find out five hand postures (WF: Wrist Flexion, WE: Wrist Extension, BG: Ball Grip, HG: Hook Grip, RE: Rest) in real-time using multi-channel EMG-based deep learning. We performed a pre-processing method that converts to Spider Chart image data for the classification of hand movement from five test subjects (total 1,500 data sets) using Convolution Neural Networks (CNN) deep learning with an 8-channel armband. As a result of this study, the recognition accuracy was 92% for WF, 94% for WE, 76% for BG, 82% for HG, and 88% for RE. Also, ten physical therapists participated for the usability evaluation. The questionnaire consisted of 7 items of acceptance, interest, and satisfaction, and the mean and standard deviation were calculated by dividing each into a 5-point scale. As a result, high scores were obtained in immersion and interest in game (4.6±0.43), convenience of the device (4.9±0.30), and satisfaction after treatment (4.1±0.48). On the other hand, Conformity of intention for treatment (3.90±0.49) was relatively low. This is thought to be because the game play may be difficult depending on the degree of spasticity of the hemiplegic patient, and compensation may occur in patient with weakened target muscles. Therefore, it is necessary to develop a rehabilitation program suitable for the degree of disability of the patient.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.300-302
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• 2022

The purpose of this study is to compare the speed, confidence, and ease of endotracheal intubation in a transfer posture by using the SALT(Supraglottic Airway Laryngopharyngeal Tube), and a direct laryngoscope to improve the ability to implement professional airway management. The subject of the study was an experimental study by a randomized crossover design, targeting 28 first-class emergency medical technicians working in J-do fire station, and the SPSS 20.0 version was used for data analysis. The endotracheal intubation by using SALT showed a significant difference in speed compared to endotracheal intubation by using a direct laryngoscope(p<.001), and also showed a significant difference in confidence and ease(p<.001). If it is transfer to endotracheal intubation by direct laryngoscope, or in the case of transfer patients, if SALT is used, safe and rapid intubation will be possible.

• Journal of the Korea Computer Graphics Society
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• v.30 no.2
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• pp.21-29
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• 2024

Although there is an increasing demand for capturing various natural motions, collecting climbing motion data is difficult due to technical complexities, related to obscured markers. Additionally, scanning climbing structures and preparing diverse routes further complicate the collection of necessary data. To tackle this challenge, this paper proposes a climbing motion synthesis using reinforcement learning. The method comprises two learning stages. Firstly, the hanging policy is trained to grasp holds in a natural posture. Once the policy is obtained, it is used to extract the positions of the holds, postures, and gripping states, thus forming a dataset of favorable initial poses. Subsequently, the climbing policy is trained to execute actual climbing maneuvers using this initial state dataset. The climbing policy allows the character to move to the target location using limbs more evenly in a natural posture. Experiments have shown that the proposed method can effectively explore the space of good postures for climbing and use limbs more evenly. Experimental results demonstrate the effectiveness of the proposed method in exploring optimal climbing postures and promoting balanced limb utilization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.285-291
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• 2020

In manufacturing, humans are being replaced with robots, but expert skills remain difficult to convert to data, making them difficult to apply to industrial robots. One method is by visual motion recognition, but physical features may be judged differently depending on the image data. This study aimed to improve the accuracy of vision methods for estimating the posture of humans. Three OpenPose vision models were applied: MPII, COCO, and COCO+foot. To identify the effects of face-covering accessories and image preprocessing on the Convolutional Neural Network (CNN) structure, the presence/non-presence of accessories, image size, and filtering were set as the parameters affecting the identification of a human's posture. For each parameter, image data were applied to the three models, and the errors between the actual and predicted values, as well as the percentage correct keypoints (PCK), were calculated. The COCO+foot model showed the lowest sensitivity to all three parameters. A <50% (from 3024×4032 to 1512×2016 pixels) reduction in image size was considered acceptable. Emboss filtering, in combination with MPII, provided the best results (reduced error of <60 pixels).

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.181-190
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• 2021

Sports activities conducted by multiple people are difficult to proceed in a situation where a widespread epidemic such as COVID-19 is spreading, and this causes a lack of physical activity in modern people. This problem can be overcome by using online exercise contents, but it is difficult to check detailed postures such as during face-to-face exercise. In this study, we present a model that detects posture and tracks movement using IT system for better non-face-to-face exercise content management. The proposed motion tracking model defines a body model with reference to motion analysis methods widely used in physical education and defines posture and movement accordingly. Using the proposed model, it is possible to recognize and analyze movements used in exercise, know the number of specific movements in the exercise program, and detect whether or not the exercise program is performed. In order to verify the validity of the proposed model, we implemented motion tracking and exercise program tracking programs using Azure Kinect DK, a markerless motion capture device. If the proposed motion tracking model is improved and the performance of the motion capture system is improved, more detailed motion analysis is possible and the number of types of motions can be increased.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1543-1550
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• 2004

Modeling from images is a cost-effective means of obtaining 3D geometric models. These models can be effectively constructed from classical Structure from Motion algorithm. However, it's too difficult to reconstruct whole scenes using SFM method since general sites contain a very complex shapes and brilliant colours. To overcome this difficulty, the current paper proposes a new reconstruction method based on a moving Planar mirror. We devise the mirror posture instead of scene itself as a cue for reconstructing the geometry That implies that the geometric cues are inserted into the scene by compulsion. With this method, we can obtain the geometric details regardless of the scene complexity. For this purpose, we first capture image sequences through the moving mirror containing the interested scene, and then calibrate the camera through the mirror's posture. Since the calibration results are still inaccurate due to the detection error, the camera pose is revised using frame-correspondence of the comer points that are easily obtained using the initial camera posture. Finally, 3D information is computed from a set of calibrated image sequences. We validate our approach with a set of experiments on some complex objects.