• Journal of Nutrition and Health
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• v.34 no.4
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• pp.449-457
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• 2001

This study was performed to show change of fat-free mass(FFM), representing mostly the muscle mass change, and muscle strength with increasing age, and relationship between dietary, exercise behaviors and FFM in healthy middle-and old aged women who are of age over 55 years. The FFM and correspondingly hand grip strength showed significant positive correlation with age. But concentration of serum albumin showed no significant relationship with age. The subjects were categorized into groups according to FFM tertile. The anthropometry such as weight, BMI, fat mass, circumferences of waist and hip, WHR, and hand grip strength decreased significantly in the lowest FFM group. But the albumin level showed no change according to FFM level. The FFM showed significant correlation with nutrient intakes such as energy, carbohydrate, protein, Fe, P, Ca. No association, however, was shown with exercise behavior probably because of no case with resistance exercise habits. The variance of FFM was explained 55.2% by height and carbohydrate intake. The variance of height-adjusted FFM could be explained only 16.2% by intake amount of carbohydrate. In conclusion, the decrease of FFM may cause to reduce muscle strength in female elderly. The increasing nutrient intakes were associated with the increased FFM and may protect from risk of sarcopenia. However, only the carbohydrate intake could influence independently the FFM in middle- and old-aged women. The FFM has no association with endurance exercise habits. (Korean J Nutrition 34(4) : 449∼457, 2001)

• Nutritional Sciences
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• v.4 no.2
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• pp.112-119
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• 2001

This study was performed fir the purpose of finding the relationship between fat-free mass (FFM) which mainly represents muscle mass change, and muscle strength. The correlation between diet and exercise behaviors and FFM in healthy elderly men over age 55 was also investigated. FFM and corresponding hand grip strength declined significantly with increasing age. However the concentration of serum albumin, the indicator of protein nutritional status, showed no change with increases in age. The subjects were categorized into three groups according to FFM textiles. Anthropometry such as height, BMI, circumferences of waist and hips, body fat mass percent and hand grip strength decreased significantly in the lowest FFM group. But albumin level showed no change relative to FFM level. FFM showed a significant relationship to nutrient intake such as energy and fat. However, no association was found with exercise behavior probably because there were no instances of resistance exercise habits among the subjects studied. The variance in FFM could be attributed 86.2% to height and age. The variance of height-adjusted FFM could be attributed only 40.6% to age and fat intake. In conclusion decreases in FFM may cause reductions in muscle strength in elderly men. Increasing energy and fat intake were associated with increased FFM and may protect elderly men from the risk of sarcopenia. FFM had no association with endurance exercise habits.

• Journal of the Korea Society for Simulation
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• v.25 no.3
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• pp.41-51
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• 2016

In this study, we propose an improved Floor Field Model(FFM) that considers the physical characteristics of pedestrians, i.e., body size, shape, and posture. Also we analyse limits of FFM and features of improved model compared with existing evacuation simulation models. FFM is a typical microscopic pedestrian model using CA, but it does not reflect the physical characteristics of pedestrians. Because of this, FFM is difficult to modeling phenomena such as collision, friction between pedestrians. As a result, FFM calculates a very short evacuation time when compared with the other models. We performed a computational experiment to compare improved model with other models such as FFM, Simulex, Pathfinder in an actual campus building. We carried out a comparison of evacuation aspect according to the change in number of evacuees. Also we compared evacuation aspect by exit. Finally, we confirmed that improved model reflects physical phenomena which were not reflected in FFM. Especially, experimental results were very similar to the Simulex.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.2
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• pp.56-67
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• 2018

In general, fire and evacuation simulators are used independently to diagnose the safety of building. Because this method does not reflect the movement of pedestrians considering fire spread, it is difficult to expect diagnosis of safety with high accuracy. In this study, we propose the simulation method that can describe the movement of pedestrians in the fire emergency. Our method reflects the FDS fire spread data into FFM and explains the situation in which a pedestrian recognize a fire and escapes to a safe route. This study consists of data linkage between FDS and FFM and development of improved FFM. Experiment of the proposed method is progressed using the EgresSIM. Simulation result shows that the number of evacuees on each exit is affected by the presence or absence of fire and it was confirmed that the evacuation time increase and the bottleneck phenomenon deepened by exit.

• Journal of the Korea Society for Simulation
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• v.25 no.2
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• pp.1-11
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• 2016

The floor field model (hereafter referred to as FFM) is a cellular automata (hereafter referred to as CA)-based walk model used to model pedestrian behavior. Existing studies on FFM conducted experiments with simple structures (that have one room or one obstacle in a room) or relatively complicated structures (that have many rooms). In order to apply the FFM to real buildings, it is necessary to have additional methodologies to process information about the number of rooms, floors, stairs, and exit doors. In particular, it is necessary to process exit doors during this procedure. Exit doors that are recognized by pedestrians are of many types such as exit doors in rooms, stairs connected to corridors, and exit doors in a building. When calculating the static floor field (hereafter referred to as SFF) in the FFM, information about exit doors is needed and simulation results will be different depending on how the SFF is calculated using an exit door among the above-mentioned exit doors. In this study, an XML-format building data model is proposed according to data structures required by the FFM. This study also defines a methodology to process a number of exit doors. Accordingly, this study developed a building data construction and evacuation simulator and simulation experiments were conducted with university campus building.

• Journal of Sensor Science and Technology
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• v.26 no.5
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• pp.314-323
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• 2017

Indicators to quantitatively evaluate the body function may help to optimize the effectiveness of rehabilitation therapy for stroke patients. In this study, we analyzed the body composition in the paretic and nonparetic regions of stroke patients with hemiplegia caused by cerebral hemorrhage (7 cases) and cerebral infarction (13 cases) using multifrequency bioelectrical impedance. Specifically, we considered fat mass (FM), fat-free mass (FFM), FFMI index (FFMI), FM/FFM relation, body cell mass (BCM), basal metabolic rate (BMR), and BMR/FFM relation to evaluate the bodily function in the paretic and nonparetic regions. These values showed considerable differences according to grades determined by the stroke causes and the paralysis status. In the paretic regions, the FFM, FFMI, BCM, and BMR were low and the FM was high. In contrast, the nonparetic regions showed a high FFM and low FM. Furthermore, the paretic and nonparetic regions of all patients suitably fit a linear relation (slope: 22.17 kcal/day/kg) between BMR and FFM. Therefore, bio-electrical impedance measurements can be very useful to quantitatively assess paretic and nonparetic regions in hemiplegic stroke patients.

• Journal of Korean Medicine for Obesity Research
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• v.5 no.1
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• pp.57-66
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• 2005

Objectives : The purpose of this study is to examine accuracy of predicted resting energy expenditure (REE), relationship fat free mass (FFM) and REE. Methods : 60 normal, obese women $(body\;mass\;index\;{\geq}25kg/m^2)$ were recruited for this study, they had low calorie diet for 8 weeks. At week 0, 4, and 8, REE was measured by MedGem (indirect calorimeter), Bioelectrical impedance analysis (BIA) using Cunningham equation, and Harris-Benedict (H-B) equation, FFM was also measured by BIA. Results : The REE predicted by BIA was lower than the REE measured by MedGem (MG) in every measurement. The REE predicted by H-B equation predicted REE was lower than that of MG in the second measurement (p<0.01). The REE measured by MedGem was declined after 8 weeks, BIA and H-B equation predicted REE were declined after 4 weeks (p<0.01). H-B equation predicted REE had more significant correlation with the REE measured by MedGem than that of BIA. There was significant correlation between measured REE and FFM, but measured REE declined after 8 weeks, FFM declined after 4 weeks (p<0.01). We derived a prediction equation as follows : REE = 108.36+31.42 (FFM), $R^2=0.23$.

• Korean Journal of Exercise Nutrition
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• v.24 no.1
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• pp.9-13
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• 2020

[Purpose] This preliminary study aimed to develop a regression model to estimate the resting metabolic rate (RMR) of young and middle-aged Koreans using various easy-to-measure dependent variables. [Methods] The RMR and the dependent variables for its estimation (e.g. age, height, body mass index, fat-free mass; FFM, fat mass, % body fat, systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and resting heart rate) were measured in 53 young (male n = 18, female n = 16) and middle-aged (male n = 5, female n = 14) healthy adults. Statistical analysis was performed to develop an RMR estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and age were important variables in both the regression models based on the regression coefficients. Mean explanatory power of RMR₁ regression models estimated only by FFM was 66.7% (R²) and 66.0% (adjusted R²), while mean standard errors of estimates (SEE) was 219.85 kcal/day. Additionally, mean explanatory power of RMR₂ regression models developed by FFM and age were 70.0% (R²) and 68.8% (adjusted R²), while the mean SEE was 210.64 kcal/day. There was no significant difference between the measured RMR by the canopy method using a metabolic gas analyzer and the predicted RMR by RMR₁ and RMR₂ equations. [Conclusion] This preliminary study developed a regression model to estimate the RMR of young and middle-age healthy Koreans. The regression model was as follows: RMR₁ = 24.383 × FFM + 634.310, RMR₂ = 23.691 × FFM - 5.745 × age + 852.341.

• 한국노년학
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• v.32 no.3
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• pp.703-714
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• 2012

The purpose of this study was to analyze the effects of combined exercise on body composition and cardiovascular disease risk factors in sarcopenic obesity elderly women. The subjects for the study were 21 obesity elderly women over 65 years old . They were divided into two groups, the sarcopenic obesity group(n=9) and non-sarcopenic obesity group(n=12). The variables of body composition and cardiovascular fitness were measured in all the subjects before and after 16-week combined exercise. All data was analyzed by two-way ANOVA with repeated measures, and paired t-test by using SPSS 18.0. The findings of this study were as follows; 1. Effects on body composition The relationship between sarcopenia and body composition were only significant for the group ${\times}$ time interaction in FFM. In the sarcopenic obesity elderly women, % body fat significantly decreased and sarcopenia reduced by 30%, but there were no significant changes in the FFM and ASM. On the other hand, the non-sarcopenic obesity elderly women significantly decreased % body fat and significantly increased FFM and ASM. 2. Effects on cardiovascular fitness Both groups significantly increased V˙ O2peak. The most important finding in this study was that sarcopenic obesity elderly women showed delayed effects of a 16-week combined exercise on FFM and ASM compared to the non-sarcopenic obesity elderly women. However, the further studies might need to confirm these results with both genders, different age groups, and various exercise types.

• Journal of Biomedical Engineering Research
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• v.23 no.5
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• pp.413-418
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• 2002

The purpose of this study was to design a single frequency BIA(Bioelectrical Impedance Analyzer) which can measure body impedance when patient is sitting on the toilet and to develope a prediction equation for designed BIA. For the purpose of this study, we acquired body impedances with designed BIA from 181 subjects composed of healthy Korean by attaching electrodes to suitable positions(wrist and thigh) for toilet measurement. We computed an appropriate FFM(Fat Free Mass) for Korean using modified-Siri equation to the same subjects instead of Siri equation which nay cause accuracy problems in hydrodensitometry when it applied to Korean. We used this FFM as reference value and developed a Korean FFM prediction equation based on body impedance index, body weight and sex. Correlation coefficient between prediction value and reference value of FFM was extremely high (r = 0.977) and SEE(Standard Error of Estimation) was low 2.47kg.(p<0.05) For comparison between existing electrode-attaching method and our method for toilet measurement, we acquired body impedance with designed BIA from same subjects attaching electrodes on existing positions (wrist and ankle) and made FFM prediction equation for BIA. Correlation coeffient between predicted value and reference value was 0.978 and SEE was 2.43kg(p<0.05). It means that the developed system has not significant differences with existing method. In conclusion bioelectrical impedance analyzer and the FFM prediction equation developed in this paper are evaluated to he adequate to compute FFM of Korean.