• Korean Journal of Computational Design and Engineering
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• v.17 no.1
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• pp.62-70
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• 2012

This paper proposes a novel discomfort assessment method for truck ingress and egress motions based on the maximum-voluntary-contraction (MVC) ratios of muscles obtained by biomechanical analysis of human musculoskeletal models. In this study, a human motion to enter and exit a truck cabin with different types and heights of footsteps is first measured using an optical motion capture system and load sensors. Next, in a biomechanical analysis system, a human musculoskeletal model with contacting conditions on footsteps and handles is modeled, and then joint torques and muscles forces are calculated by inverse dynamics of the musculoskeletal model with the motion data. Finally, the MVC ratios for the muscles are calculated and their statistical values are used as the measure of discomfort. To ensure the feasibility of our method, subjective discomfort levels have been investigated through the participants' experiments and questionnaires and compared to the results of our method. Comparing to the existing methods based on joint angles or torques, our approach provide a more essential criterion for discomfort because it is based on the muscle contraction by which an active human motion is basically generated.

• Proceedings of the Safety Management and Science Conference
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• 2008.11a
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• pp.329-341
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• 2008

The psychosocial stress and musculoskeletal disorders(MSDs) have been one of major health problems for hospital workers. This study tried to understand the relationship between symptoms associated with MSDs and risk factors such as working posture, job stress, psychosocial stress and fatigue. A total number of 655 hospital workers participated in this study. Specifically, REBA was applied for evaluating working posture and a checklist prepared by KOSHA(Korean Occupational Safety and Health Agency) was used for symptom survey. A questionnaire from KOSHA was also used for collecting data associated with job stress, psychosocial stress and fatigue. All these data were formulated and modeled by path analysis which was one of major statistical tools in this study. Specifically, path analysis for the data we collected came up with several major findings. The risk scores from working posture based on REBA had indirect effects via fatigue factor(MFS) as well as direct effects on symptoms. The factors associated with job stress(KOSS) and psychosocial stress(PWI-SF) had significant effects on symptoms. Specifically, indirect effect of job stress factors via fatigue factors(MFS) had bigger than that of direct effect of job stress on symptom.

• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.302-307
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• 2006

The aim of applying Functional Electrical Stimulation (FES) is to restore a person's motor function by directly supplying the controlled electrical currents to the site of the paralyzed muscles. However, most clinically utilized FES systems have adapted an open-loop control scheme. Recently the closed-loop control scheme has been considered for setting up the FES system, but due to the inherent nonlinearities in the musculoskeletal system, the nonlinearities were not fully compensated and it caused the oscillatory responses for tracking the output variables. In this study, a nonlinear controller model that has two inverse compensation units is proposed with the compromising feedback linearization method and this will eventually be used to design the FES control system for stimulating a knee joint musculoskeletal system.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.13 no.2
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• pp.140-148
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• 2009

The primary market of acupuncture treatment is concentrated on disorders of the musculoskeletal system. This study researches the clinical use of the musculoskeletal system evaluation with a computer simulation. Two fields are examined - patient evaluation and patient treatment. In the field of evaluation, the simulation is used to evaluates the prognosis of medical treatment. In the field of treatment, the simulation is used to decide the most suitable way to perform surgery using the quantitative evaluation about various cases of surgical results.

• Journal of muscle and joint health
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• v.22 no.1
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• pp.20-29
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• 2015

Purpose: The study was undertaken to investigate effects of susceptibility to musculoskeletal disorder, social support, and environmental aids on exercise adherence intention and to identify factors contributing to exercise adherence intention among university students. Methods: The study was a descriptive study with 277 students from 3 universities. Data were collected from March 5 to May 30, 2014 using a structured self-report questionnaire. Data were analyzed using descriptive statistics, t-test, one-way ANOVA, Pearson correlation coefficients, and Hierarchical multiple regression. Results: The explanatory power of the predictive model involving the demographic factors, susceptibility to musculoskeletal disorder, social support, and environmental aids was 29%, and the subjects' gender, health concern, experience of musculoskeletal injury, regular exercise, and social support were identified as main factors having influence. Conclusion: The results of this study will be helpful in understanding the importance of environmental factors for increasing physical activities and will be used as basic data for development of exercise programs to increase exercise adherence intention for their continuous exercise.

• The Korean Journal of Health Service Management
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• v.6 no.1
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• pp.27-38
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• 2012

This study is to find out the correlation among the predisposing, enabling, and need factors in Anderson Behavioral Model using the data from Korea Medical Panel Survey conducted in the early part (April 1 - October 31) of 2008. The findings are as follows. It was found that the utilization rate of western medical service was far higher. the influential factor to choose western or oriental medical service taking western medical institutions as the reference group, the influential factor to choose oriental medical institution has significantly increased when the patient who have covered by medical insurance has one accompanied disease and their age was between 45 - 74, compared to the people less than 45 years old. It also increased when the age of the patient was between 45-54 years old, and in the event those who are not covered by medical insurance have accompanied disease and that the disease mobility period is 2-4 years. reviewing the several characteristics of the utilization of western and oriental medical services by the patient with musculoskeletal system disorders, the number of accompanied disease is an influential factor for the utilization of oriental medical services. And, disease mobility period is a significant factor for the utilization of both western and oriental medical services together, though it is not identified in this study. Therefore, it is expected that mutual cooperation between western and oriental medical services is more required for the patient with musculoskeletal system disorders as the aging society rapidly develops. In order to foster oriental medicine, it is required to specialize in competitive disease such as musculoskeletal system disorders.

• Korean Journal of Computational Design and Engineering
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• v.17 no.6
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• pp.443-455
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• 2012

The configuration of a musculoskeletal (MS) system is closely related to the individual motions of the human body. Many researches have been focused on evaluating the associations between the MS configuration and the individual motion using patient-specific MS models, but it still remains a challenging issue to accurately predict the motion by differed configurations of the MS system. The main objective of this paper is to predict the changes of a patient-specific gait by altering the geometric parameters of the hip joint using function-based morphing method (FBM). FBM is suitable for motion analysis since this method provide a robust way to morph a MS model while preserving the biomechanical functions of the bones. Computed-muscle control technique is used to calculate the muscle excitations to reproduce the targeted motion within a digital MS model without the motion-captured data. We applied this approach to a patient who has an abnormal gait pattern. Results showed that the femoral neck length and the angle significantly affect to the motion especially for the hip abduction angle during gait, and that this approach is suitable for gait prediction.

• Physical Therapy Korea
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• v.27 no.2
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• pp.140-148
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• 2020

Background: Scapular winging (SW) could be caused by tightness or weakness of the periscapular muscles. Although data mining techniques are useful in classifying or predicting risk of musculoskeletal disorder, predictive models for risk of musculoskeletal disorder using the results of clinical test or quantitative data are scarce. Objects: This study aimed to (1) investigate the difference between young women with and without SW, (2) establish a predictive model for presence of SW, and (3) determine the cutoff value of each variable for predicting the risk of SW using the decision tree method. Methods: Fifty young female subjects participated in this study. To classify the presence of SW as the outcome variable, scapular protractor strength, elbow flexor strength, shoulder internal rotation, and whether the scapula is in the dominant or nondominant side were determined. Results: The classification tree selected scapular protractor strength, shoulder internal rotation range of motion, and whether the scapula is in the dominant or nondominant side as predictor variables. The classification tree model correctly classified 78.79% (p = 0.02) of the training data set. The accuracy obtained by the classification tree on the test data set was 82.35% (p = 0.04). Conclusion: The classification tree showed acceptable accuracy (82.35%) and high specificity (95.65%) but low sensitivity (54.55%). Based on the predictive model in this study, we suggested that 20% of body weight in scapular protractor strength is a meaningful cutoff value for presence of SW.

• Journal of the Institute of Convergence Signal Processing
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• v.21 no.2
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• pp.73-78
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• 2020

Musculoskeletal disease is often caused by sitting down for long period's time or by bad posture habits. In order to prevent musculoskeletal disease in daily life, it is the most important to correct the bad sitting posture to the right one through real-time monitoring. In this study, to detect the sitting information of user's without any constraints, we propose posture measurement system based on multi-channel pressure sensor and CNN model for classifying sitting posture types. The proposed CNN model can analyze 5 types of sitting postures based on sitting posture information. For the performance assessment of posture classification CNN model through field test, the accuracy, recall, precision, and F1 of the classification results were checked with 10 subjects. As the experiment results, 99.84% of accuracy, 99.6% of recall, 99.6% of precision, and 99.6% of F1 were verified.

• The Journal of the Korean dental association
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• v.51 no.9
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• pp.511-517
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• 2013

To assess the association between oral health and general health, this study examined the relationship between chewing difficulty and twelve chronic health conditions such as hypertension, hyperlipidemia, diabetes, cerebro- and cardiovascular disease, musculoskeletal disease, respiratory disease, eye/nose/throat disease, stomach/intestinal ulcer, renal dysfunction, thyroid disease, depression, and cancer in Korea. The study population was 3,066 elders aged 65 years old and more from the fourth Korean National Health and Nutrition Examination Survey. Chewing difficulty was measured on a 5-point Likert scale. Chronic conditions were assessed by self-reported questionnaire. Confounders were age, gender, education, income, smoking, drinking, and obesity. Chi-square test, general linear model, and multiple logistic regression model were done with complex sampling design. Musculoskeletal disease (adjusted odds ratio=1.33), respiratory disease (adjusted odds ratio=1.52), and cancer (adjusted odds ratio=1.58) were independently associated with chewing difficulty. Multiple chronic conditions with more than 4 chronic disease showed significant association with chewing difficulty (adjusted odds ratio=1.37).