• The Journal of Korean Physical Therapy
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• v.36 no.1
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• pp.45-51
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• 2024

Purpose: Since core competence-based training is in demand, this study aimed to develop a suitable talent model and major competencies for the Department of Physical Therapy at U University and use it to propose appropriate educational subjects. Methods: This case study was conducted at U university in Gyeongju-si, Gyeongsangbuk-do. To study curricula based on major competence, related documents were analyzed, expert opinions were obtained, and a consumer survey was conducted. Results: U University assigns major competencies for each department, develops subjects accordingly, maps them, and constructs a competency matrix. The four major competencies of physical therapy were defined as musculoskeletal system, nervous system, cardiorespiratory system and sports injury, and physical management abilities. In order to realize these major competencies, U University added subjects to its curriculum. Conclusion: The results of internal and external environmental analysis should be more actively considered to enable changes in subjects at the departmental level. In addition, the setting of major competencies should be subjected to more detailed, specific reviews to maintain the basic principles of major curricula.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.785-790
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• 2011

The goal of this study is to estimate the force acting on the knee joint in the human body by using the Hilltype muscle model based on a musculoskeletal model of the human lower extremity in the sagittal plane. For estimating the force applied, the human leg is modeled using multi-body modeling. This leg model comprises biarticular muscles acting on two joints of the upper and lower limbs, and the muscles include some of the major muscles such as the hamstring. In order to analyze the uncertainty of the applied forces acting on the knee joint, statistical distributions of human body, leg part, parameters are required and to obtain the parameter's statistical characteristic of the part sample survey method is employed. Finally, by using the sensitivity information of the parameters, the force acting on the knee joint can be estimated.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.64-71
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• 2013

Purpose: The purpose of this study was to select standing posture parameters that have a significant difference according to the severity of spinal deformity, and to develop a novel Cobb angle prediction model for adolescent girls with idiopathic scoliosis. Methods: Five normal adolescents girls with no history of musculoskeletal disorders, 13 mild scoliosis patients (Cobb angle: $10^{\circ}-25^{\circ}$), and 14 severe scoliosis patients (Cobb angle: $25^{\circ}-50^{\circ}$) participated in this study. Six infrared cameras (VICON) were used to acquire data and 35 standing parameters of scoliosis patients were extracted from previous studies. Using the ANOVA and post-hoc test, parameters that had significant differences were extracted. In addition, these standing posture parameters were utilized to develop a Cobb-angle prediction model through multiple regression analysis. Results: Twenty two of the parameters showed differences between at least two of the three groups and these parameters were used to develop the multi-linear regression model. This model showed a good agreement ($R^2$ = 0.92) between the predicted and the measured Cobb angle. Also, a blind study was performed using 5 random datasets that had not been used in the model and the errors were approximately $3.2{\pm}1.8$. Conclusions: In this study, we demonstrated the possibility of clinically predicting the Cobb angle using a non-invasive technique. Also, monitoring changes in patients with a progressive disease, such as scoliosis, will make possible to have determine the appropriate treatment and rehabilitation strategies without the need for radiation exposure.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.1
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• pp.115-122
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• 2011

Recently, we have proposed a hypothesis that spinal structures have a stress sensor driving feedback mechanism, In the human spine, spinal structure could react to modify muscular action in such a way so as to equalize stress at the disc, therefore reduce the risk of injury, In this analysis, abdominal muscle and abdominal pressure, which were not included in the previous study, were added to identify those effects in spine stability during upright stance posture for the case where the intervertebral disc plays the role of mechanoreceptor, The musculoskeletal FE model was consisted with detailed whole lumbar spine, pelvis, sacrum, coccyx and simplified trunk model. Muscle architecture with 46 local muscles containing paraspinal muscle and 6 rectus abdominal muscles were assigned according to the acting directions. The magnitude of 4kPa was considered for abdominal pressure. Minimization of the nucleus pressure deviation and annulus fiber average tension stress deviation was chosen for cost function. Developed model provide nice coincidence with in-vivo measurement (nucleus pressure). Analysis was conducted according to existence of co-activation of abdominal muscle and abdominal pressure. Antagonistic activity of abdominal muscle produced stability of spinal column with relatively small amount of total muscle force. In contrast to the abdominal muscle, effect of abdominal pressure was not clear that was partly depending on the assumption of constant abdominal pressure.

• Journal of Korean society of Dental Hygiene
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• v.15 no.4
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• pp.649-659
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• 2015

Objectives: The purpose of the study is to investigate the musculo-skeletal pain prevalence and severity in the dental hygienists based on PRECEDE model. Methods: A self-reported questionnaire was completed by 483 dental hygienists in Gwangju from September 13 to October 12, 2013. Data were analyzed by frequency analysis, chi-square test, t-test, and multiple logistic regression analysis using SPSS 18.0 program. Musculo-skeletal pain severity was classified from 1 to 5 by PRECEDE model. The questionnaire consisted of six questions of the general characteristics of the subjects, one question of musculo-skeletal pain prevalence, one question of body part musculo-skeletal pain prevalence, one question of subjective health status, three questions of activities of daily living, six questions of working environment, one question of musculoskeletal system diseases knowledge, two questions of social support, two questions of education experience and data use method, and five questions of necessity of health education. Results: The prevalence rate of musculo-skeletal pain within a year was 83.9% and 22.8% of the dental hygienists complained of severe pain. The odds ratio of moderate pain severity was 1.99(95% CI, 1.10-3.60) and the odds ratio of unhealthiness was 3.27 (95% CI, 1.35-7.94). The odds ratio of pain severity in those working for 4-6 years was 0.21(95% CI, 0.08-0.57). The odds ratio of pain severity in those practicing 6-10 scaling cases per day was 0.33(95% CI, 0.17-0.65). The odds ratio of pain severity in wrist turning and bending was 3.56(95% CI, 1.19-10.62). Conclusions: The muscolu-skeletal pain severity in the dental hygienists was closely associated with subjective health condition, work duration, the number of scaling practice activity, and a treatment posture. Regular physical checkup for the dental hygienists will improve the musculo-skeletal pain due to scaling practice.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.2
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• pp.130-136
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• 2010

For stability analysis of the lumbar spine, the hypothesis presented is that the disc has stress sensors driving feedback mechanism, which could react to the imposed loads by adjusting the contraction of the muscles. Fusion in the motion segment of the lumbar spinal column is believed to alter the stability of the spinal column. To identify this effect finite element (FE) models combined with optimization technique was applied and quantify the role of each muscle and reaction forces in the spinal column with respect to the fusion level. The musculoskeletal FE model was consisted with detailed whole lumbar spine, pelvis, sacrum, coccyx and simplified trunk model. Vertebral body and pelvis were modeled as a rigid body and the rib cage was constructed with rigid truss element for the computational efficiency. Spinal fusion model was applied to L3-L4, L4-L5, L5-S1 (single level) and L3-L5 (two levels) segments. Muscle architecture with 46 local muscles was used as acting directions. Minimization of the nucleus pressure deviation and annulus fiber average axial stress deviation was selected for cost function. As a result, spinal fusion produced reaction changes at each motion segment as well as contribution of each muscle. Longissimus thoracis and psoas major muscle showed dramatic changes for the cases of L5-S1 and L3-L5 level fusion. Muscle force change at each muscle also generated relatively high nucleus pressure not only at the adjacent level but at another level, which can explain disc degeneration pattern observed in clinical study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.1-8
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• 2018

Whole body fatigue detection is an important phenomenon and the factors contributing to whole body fatigue can be controlled if a mathematical model is available for its assessment. This research study aims at developing a model that categorizes whole body exertion into fatigued and non-fatigued states based on physiological and perceived variables. For this purpose, logistic regression was used to categorize the fatigued and non-fatigued subject as dichotomous variable. Normalized mean power frequency of eight muscles from 25 subjects was taken as physiological variable along with the heart rate while Borg scale ratings were taken as perceived variables. The logit function was used to develop the logistic regression model. The coefficients of all the variables were found and significance level was checked. The detection accuracy of the model for fatigued and non-fatigues subjects was 83% and 95% respectively. It was observed that the mean power frequency of anterior deltoid and the Borg scale ratings of upper and lower extremities were significant in predicting the whole body fatigued when evaluated dichotomously (p < 0.05). The findings can help in better understanding of the importance of combined physiological and perceived exertion in designing the rest breaks for workers involved in squat lifting tasks in industrial as well as health sectors.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• Journal of the Ergonomics Society of Korea
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• v.24 no.3
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• pp.11-27
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• 2005

The objectives of this study are to analyze representative wrist postures while using hand tools and parts at general assembly processes, to evaluate perceived discomfort on the wrist when external loads are present, and to suggest an evaluation and prediction model of perceived discomfort. Sixteen subjects participated in an experiment to appraise perceived discomfort. Three types of the wrist postures with five levels of non-neutralities were analyzed when five levels of external load were applied to each posture. The ANOVA results showed that the perceived discomfort of wrist postures was significantly affected by both the wrist posture and external load (p$<$0.001). It was also shown that some of the interactions between external loads and the wrist postures(Flexion/$Extension^*$Load, Flexion/$Extension^*$supination/pronation, ulnar/radial $deviation^*$supination/pronation) were significant(p$<$0.001). The result implies that a new posture classification scheme for workload assessment methods may be needed to reflect such effects of external load and wrist posture. A regression model of perceived discomfort was developed with respect to wrist posture and external load from the experimental data. A subsequent experiment revealed that the correlation coefficient between the predicted values of perceived discomfort from the model and the actual values obtained from the experiment was about 0.98. It is expected that the results help to properly estimate the body stress resulting from worker's postures and external loads and can be used as a valuable design guideline to analyze potential hazard of musculoskeletal diseases in industry.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.353-366
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• 2018

This study uses mixed-effects models to predict thigh soft tissue artefact (STA), relative movement of soft tissue such as skin to femur occurring during hip joint motions. The random effects in the model were defined as STA and the fixed effects in the model were considered as skeletal motion. Five male subjects without musculoskeletal disease were selected to perform various hip joint rotational motions. Linear mixed-effects models were applied to markers' position vectors acquired from non-invasive method, photogrammetry. Predicted random effects showed similar patterns of STA among subjects. Large magnitudes of STA appeared on the points near the hip joint regardless of sides; however, small values appeared on the distal anterior.