• International Journal of CAD/CAM
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• v.12 no.1
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• pp.1-8
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• 2012

This study analyzes the characteristics of two different kinds of squat exercise through physical experiments and a computer simulation, i.e. one with a free weight and the other with a Smith machine are studied. This study also proposes a new design for the Smith machine, which has both the advantages of each type based on the results of the analysis. The muscle force and level of stimulation of the lower extremities during squatting were calculated by running an inverse dynamics analysis program on a musculoskeletal model together with the measured motion data. The calculated results were verified by comparing with the measured EMG data. The analysis showed that squatting using free weight is more effective than squatting using the Smith machine. Meanwhile, in order to design an improved Smith machine, which is the final goal of this study, the trajectory of the barbell of the subjects during free weight squatting was measured on the sagittal plane. The measurement showed that the average slope of the trajectory of the barbell is tilted backward by $10.7^{\circ}$. Based on this measurement, this study proposes a tilted design for an improved Smith machine.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.209-215
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• 2019

In order to provide a safe free-weight-training environment to people without workout trainers, we suggest a smart bench press machine with an automatic weight control system sensitive to user tiredness. Physical weight plates on the machine are replaced with a hydraulic cylinder as a press load and the cylinder knob is coupled with a step motor to change its tensile force automatically in-between lifting exercises. Three subjects participated to verify the usability of the smart bench press machine. They were asked to lift a 6-RM press load 10 times with 3 different lifting conditions: 1) no assistance, 2) a human assistance, and 3) the automatic weight control. All subjects were not able to complete the 10 sets without assistance due to tiredness, but they finished the full sets under the two assistive conditions. Average lifting speeds under the automatic weight control condition showed the most consistent level. Normalized quasi-tension data based on surface electromyogram signals of both Pectoralis Majors revealed that the subjects maintained the target muscle activation level above 50% but not more than 80% throughout the 10 sets. Therefore, the smart bench press machine is expected to both keep pace with the lifting exercise and reduce risk of injuries due to excessive muscle tensions.

• Asian-Australasian Journal of Animal Sciences
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• v.11 no.6
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• pp.746-750
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• 1998

This experiment was conducted to investigate the water requirement of exercising sheep. Nine Merino ewes were allocated into three groups differing in water supply after exercise, group 1(G1) supplied water ad libitum, group 2 (G2) supplied with water twice a day, and group 3 (G3) supplied with water once a day. The ewes were exercised outdoors using a circular exercising machine at a speed of 5 km/h for 1 hour for 12 consecutive days. Total daily water intake (TDWI) of animals in G3 was significantly lower (p < 0.05) than that of those in G1 and G2. TDWI of the 2 later groups was not different. TDWI of G3 was about 60% of that of G1. Feed intake of G3 was significantly (p < 0.05) lower than that of the other two groups. Immediately after exercise, rectal temperature (RT) of animals in G1 was significantly (p < 0.05) lower than those in the other groups. Respiration rate (RR) of animals in all three groups was not significantly different. Faecal moisture of animals in G3 was significantly lower (p < 0.05) than those in the other groups. The results indicate that for optimum productivity sheep should be given water at least twice a day.

• The Korean Journal of Food & Health Convergence
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• v.7 no.3
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• pp.25-32
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• 2021

This study examined the effects of kinesio taping on recovery from fatigue induced by an exercise of concentric contraction using an isokinetic machine. The fatigue was introduced by a mode of exercise at 60°/sec, 50 repetitions for three sessions. The changes of blood ammonia, lactate, LDH, and CK as a marker of fatigue were monitored. Eight healthy collegiate students participated in two experiments; 1) kinesio taping application condition and 2) no kinesio taping application condition. Before experiments, their physical characteristics were measured. For the experiment, blood samples were taken before and immediately after exercise, and 24hr as well as 72hr of recovery period. Window SPSS package 12.0 version was used and one-way ANOVA with repeated measures were employed. The results were as follows. 1) Blood ammonia tended to reduce along the recovery, but no differences between conditions were noticed. 2) Blood lactate tended to reduce during the recovery period, but differences between conditions were not noticed. 3) The LDH was not different between conditions and CK tended to reduce during the recovery period, but differences between conditions were not noticed. Based on the results, kinesio taping did not influence on recovery phase of blood ammonia, lactate concentration, LDH, and CK.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.29-34
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• 2023

Recently, the rapid development of artificial intelligence technology, many studies are being conducted to predict the risk of heart disease in order to lower the mortality rate of cardiovascular diseases worldwide. This study presents exercise or dietary improvement contents in the form of a software app or web to patients with cardiovascular disease, and cardiovascular disease through digital devices such as mobile phones and PCs. LR, LDA, SVM, XGBoost for the purpose of developing "Life style Improvement Contents (Digital Therapy)" for cardiovascular disease care to help with management or treatment We compared and analyzed cardiovascular disease prediction models using machine learning algorithms. Research Results XGBoost. The algorithm model showed the best predictive model performance with overall accuracy of 80% before and after. Overall, accuracy was 80.0%, F1 Score was 0.77~0.79, and ROC-AUC was 80%~84%, resulting in predictive model performance. Therefore, it was found that the algorithm used in this study can be used as a reference model necessary to verify the validity and accuracy of cardiovascular disease prediction. A cardiovascular disease prediction analysis algorithm that can enter accurate biometric data collected in future clinical trials, add lifestyle management (exercise, eating habits, etc.) elements, and verify the effect and efficacy on cardiovascular-related bio-signals and disease risk. development, ultimately suggesting that it is possible to develop lifestyle improvement contents (Digital Therapy).

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1153-1157
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• 2004

The report of the Korean National Statistics Office shows that Korea has been emerging as an elderly society rapidly, and it will burden the Korean society with excessive social welfare cost for the aged in the near future. If we can help the aged to live healthy in some ways, the social burden for the health care of the aged will be lessened. In order to help physical and mental health of the elderly person, we have developed an exercise apparatus called intelligent arm wrestling machine system. This paper presents the mechanism and scenario of the proposed intelligent arm wrestling machine system. The proposed mechanism and scenario are peculiar. In particular, the proposed scenario determines randomly who will win between the man and the robot and generates a game process that the arm-wrestler cannot predict in advance.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2009-2017
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• 2015

The E-Core Transverse Flux Machine is a different design of transverse flux machines combined with reluctance principle. Determination of the rotor position is important for the movement of the ETFM by switching the phase currents in synchronism with the inductance regions of the stator windings. It is the first time that rotor position estimation based on Artificial Neural Network (ANN) is purposed to eliminate the position sensor for the ETFM. Simulation and experimental tests are demonstrated for the feasibility of the proposed estimation algorithm for the exercise bike application of the ETFM.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.13 no.3
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• pp.401-408
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• 2006

Purpose: The purpose of this study was to determine the effects of a lower extremity exercise program on muscle strength and flexibility in women with knee osteoarthritis. Method: This study was conducted using a non-equivalent control group pretest-posttest design. The participants were 35 women with knee osteoarthritis. The experimental group performed the lower extremity exercise program, which was an adapted BeHaS exercise program developed by Kim(2006). It consisted of approximately 65-130 minutes per one session, two days a week, for twelve weeks. Lower extremity muscle strength was measured by the Seated Leg Press Machine (TY-H2217, made in Korea), back muscle strength by back muscle strength scale (TKK 5402, made in Japan) and flexibility, by Sit and Reach tester (01285, U.S.A). Data were gathered from September 2005 to March 2006. Frequency, $X^2$ test and t-test were used to analyze the data. SPSS Win 11.0 was used to assist analysis. For normal distribution of data, Kolmogorov-Smirnov test was done. Results: There were statistical differences in the mean strength of both legs together, strength in leg with more pain(p=.044; p=.046), sit and standing time (p=.007), and back strength (p=.021). Conclusion: Based on these results, it can be concluded that a lower extremity exercise program can help improve lower extremity muscle strength in women with osteoarthritis.

• Korean Journal of Applied Biomechanics
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• v.22 no.2
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• pp.201-208
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• 2012

The purpose of this study was to investigate the effect of leg extension exercises performed on outdoor resistance exercise machines on knee extension muscle strength and quadriceps muscle group cross sectional area (CSA) in elderly women. Two groups were recruited for this study, including an exercise group (EG: n=13, $71.38{\pm}2.79$ yrs) and a control group (CG: n=5, $73.4{\pm}5.94$), In all subjects, maximum isometric and isokinetic muscle strength of knee flexion and extension were measured using an isokinetic dynamometer (Cybex(R) Humac Norm Testing & Rehabilitation System, USA). Quadriceps muscle group CSA were measured using MRI (Philps, Intera 1.5 T, NE Netherlands). The results of this study showed that post-intervention isometric knee extension peak torque value were higher than pre-intervention measures in the EG. However, the EG did not show improvement in quadriceps muscle group CSA, Also, no differences in the shift of optimal knee joint angle were observed between pre and post-intervention exercise. Outdoor leg extension exercise showed small increases in muscle strength in comparison to other resistance training exercises. The results of this study suggest that because outdoor leg extension exercise machines lack a progressive loading mechanism, significant increases in muscle strength may not be obtained.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.93-102
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• 2019

As interest in wellness grows, There is a lot of research about monitoring individual health using wearable devices. Accordingly, a variety of methods have been studied to distinguish exercise from daily activities using wearable devices. Most of these existing studies are machine learning methods. However, there are problems with over-fitting on individual person's learning, data discontinuously recognition by independent segmenting and fake activity. This paper suggests a detection method for exercise activity based on the physiological response principle of heart rate up and down during exercise. This proposed method calculates activity intensity and heart rate from triaxial and photoplethysmography sensor to determine a heart rate recovery, then detects exercise by estimating activity intensity or detecting a heart rate rising state. Experimental results show that our proposed algorithm has 98.64% of averaged accuracy, 98.05% of averaged precision and 98.62% of averaged recall.