• Korean Journal of Applied Biomechanics
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• v.16 no.3
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• pp.149-163
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• 2006

The purpose of this study was to compare the lower extremity's joint and segment coupling patterns between forward and backward running in subjects who were twelve healthy males. Three-dimensional kinematic data were collected with Qualisys system while subjects ran to forward and backward. The thigh internal/external rotation and tibia internal/external rotation, thigh flexion/extension and tibia flexion/extension, tibia internal/external rotation and foot inversion/eversion, knee internal/external rotation and ankle inversion/eversion, knee flexion/extension and ankle inversion/eversion, knee flexion/extension and ankle flexion/extension, and knee flexion/extension and tibia internal/external rotation coupling patterns were determined using a vector coding technique. The comparison for each coupling between forward and backward running were conducted using a dependent, two-tailed t-test at a significant level of .05 for the mean of each of five stride regions, midstance(1l-30%), toe-off(31-50%), swing acceleration(51-70%), swing deceleration(71-90), and heel-strike(91-10%), respectively. 1. The knee flexion/extension and ankle flexion/extension coupling pattern of both foreward and backward running over the stride was converged on a complete coordination. However, the ankle flexion/extension to knee flexion/extension was relatively greater at heel-strike in backward running compared with forward running. At the swing deceleration, backward running was dominantly led by the ankle flexion/extension, but forward running done by the knee flexion/extension. 2. The knee flexion/extension and ankle inversion/eversion coupling pattern for both running was also converged on a complete coordination. At the mid-stance. the ankle movement in the frontal plane was large during forward running, but the knee movement in the sagital plane was large during backward running and vice versa at the swing deceleration. 3. The knee flexion/extension and tibia internal/external rotation coupling while forward and backward run was also centered on the angle of 45 degrees, which indicate a complete coordination. However, tibia internal/external rotation dominated the knee flexion/extension at heel strike phase in forward running and vice versa in backward running. It was diametrically opposed to the swing deceleration for each running. 4. Both running was governed by the ankle movement in the frontal plane across the stride cycle within the knee internal/external rotation and tibia internal/external rotation. The knee internal/external rotation of backward running was greater than that of forward running at the swing deceleration. 5. The tibia internal/external rotation in coupling between the tibia internal/external rotation and foot inversion/eversion was relatively great compared with the foot inversion/eversion over a stride for both running. At heel strike, the tibia internal/external rotation of backward running was shown greater than that of forward(p<.05). 6. The thigh internal/external rotation took the lead for both running in the thigh internal/external rotation and tibia internal/external rotation coupling. In comparison of phase, the thigh internal/external rotation movement at the swing acceleration phase in backward running worked greater in comparison with forward running(p<.05). However, it was greater at the swing deceleration in forward running(p<.05). 7. With the exception of the swing deceleration phase in forward running, the tibia flexion/extension surpassed the thigh flexion/extension across the stride cycle in both running. Analysis of the specific stride phases revealed the forward running had greater tibia flexion/extension movement at the heel strike than backward running(p<.05). In addition, the thigh flexion/extension and tibia flexion/extension coupling displayed almost coordination at the heel strike phase in backward running. On the other hand the thigh flexion/extension of forward running at the swing deceleration phase was greater than the tibia flexion/extension, but it was opposite from backward running. In summary, coupling which were the knee flexion/extension and ankle flexion/extension, the knee flexion/extension and ankle inversion/eversion, the knee internal/external rotation and ankle inversion/eversion, the tibia internal/external rotation and foot inversion/eversion, the thigh internal/external rotation and tibia internal/external rotation, and the thigh flexion/extension and tibia flexion/extension patterns were most similar across the strike cycle in both running, but it showed that coupling patterns in the specific stride phases were different from average point of view between two running types.

• Journal of Sensor Science and Technology
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• v.25 no.1
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• pp.20-26
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• 2016

The bioelectrical impedance (BI) for the young and the elderly was measured using bioelectrical impedance spectroscopy (BIS). First, while applying a current of $600{\mu}A$ to the foot and hand, BI was measured at 50 frequencies ranging from 5 to 1000 kHz. The BI for young subjects was considerably lower than that for old subjects since young subjects have more lean mass (hydration). The prediction marker was 0.74 for young subjects and 0.78 for old subjects. Second, a Cole-Cole diagram was obtained for young subjects and old subjects, indicating the different characteristic frequencies. At 50 kHz, the average phase angle was $7.8^{\circ}$ for young subjects whereas that was $6.1^{\circ}$ for old subjects. Third, BIVA was analyzed for young subjects and old subjects. The vector length was 210.89 [${\Omega}/m$] for young subjects and 326.12 [${\Omega}/m$] for old subjects. At 50 kHz, the resistance (R/H) and the reactance ($X_C/H$) divided by height were 208.94 [${\Omega}/m$] and 28.68 [${\Omega}/m$] for young subject, and 324.33 [${\Omega}/m$] and 34.09 [${\Omega}/m$] for old subjects.

• Korean Journal of Applied Biomechanics
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• v.15 no.4
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• pp.131-142
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• 2005

This study was investigated the stability of the AK amputee gait through analysing the variability on kinematic variables between the sound leg and the prosthetic limb. The one male, AK amputee who could walk for himself with his prosthetic limb was participated in this study. Six cameras of the MCU 240 and the QTM(Qualisys Track Manager) software were used for data collecting in this study. The relative angle of both segments was the difference between the absolute angle of the distal segment and the absolute angle of the proximal segment. The coupling angles between the prosthetic limb and the sound leg were caculated on the thigh Flexion/Extension in relative to the shank Flexion/Extension and the shank Flexion/Extension n relative to the foot Flexion/Extension. In order to evaluate the variability of segment and joint angle, C.V. was used, and to evaluate the variability for coupling angles, the Relative motion calculated by vector coding method of the continuous methods was used. As stated, the gait pattern of the prosthetic limb was almost similar gait pattern of the sound leg, but the prosthetic limb showed that the gait pattern of the sound leg and the prosthetic limb were not stable against the sound leg.

• ETRI Journal
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• v.33 no.4
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• pp.537-546
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• 2011

This paper introduces an automated method for building height recovery through the integration of high-resolution satellite images and digital vector maps. A cross-correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross-correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.153-158
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• 2010

This paper showed the possibilities of performance improvement of Brain-Computer Interface (BCI) decreasing classification error rates of EEG signals by applying Variance-Considered Machine (VCM) which proposed in our previous study. BCI means controlling system such as computer by brain signals. There are many factors which affect performances of BCI. In this paper, we used suggested algorithm as a classification algorithm, the most important factor of the system, and showed the increased correct rates. For the experiments, we used data which are measured during imaginary movements of left hand and foot. The results indicated that superiority of VCM by comparing error rates of the VCM and SVM. We had shown excellence of VCM with theoretical results and simulation results. In this study, superiority of VCM is demonstrated by error rates of real data.

• Journal of the Korean Applied Science and Technology
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• v.37 no.4
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• pp.839-847
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• 2020

The purpose of this study was to analyze the effects of ankle flexibility, gender, and Q-angle on the ankle joint injury factors during one leg drop landing. For this study, 16 males(age: 20.19±1.78 years, mass: 69.54±10.12 kg, height: 173.22±4.43 cm) and 16 females(age: 21.05±1.53 years, mass: 61.75±6.97 kg, height: 159.34±4.56 cm) in their 20's majoring in physical education using the right foot as their dominant feet were selected as subjects. First, an independent t-test of joint motion and joint moment according to the experience of ankle injury was conducted to determine the effect of physical characteristics on ankle joint injury during one leg drop landing(α = .05). Second, the variable that showed a significant difference through t-test was set as the dependent variable, and the ankle flexibility, gender difference, and Q-angle were designated as independent variables to use Multiple Linear Regression(α =. 05). As a result of this study, it was found that the group that experienced an ankle joint injury was found to use a landing strategy and technique through adduction of the ankle joint and internal rotation of the knee joint, unlike the group without an injury. It was also confirmed that this movement increases the extension moment of the ankle joint and decreases the extension moment of the hip joint. In particular, it was found that the dorsi flexion flexibility of the ankle affects the ankle and knee landing strategy, and the gender difference affects the ankle extension moment. Therefore, it was confirmed that physical characteristics factors affecting ankle joint injuries during one leg drop landing.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.