• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.1425-1426
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• 2015

Core spine muscle are related are associated with trunk stability and play a main role for the prevention of low back pain. In this study, it was investigated the effect of spine stabilization exercise device on core spinal muscles using a musculoskeletal model The forward direction of the tilt mainly induced the activation of long and superficial back muscles and the backward affected the front muscles. It was shown that spine stabilization exercise device can induce significant core muscle exercise effect.

• 한국CDE학회논문집
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• 제19권1호
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• pp.68-79
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• 2014

Human model simulation has been widely used in various industrial areas such as ergonomic design, product evaluation and characteristic analysis of work-related musculoskeletal disorders. However, the process of building digital human models and capturing their behaviors requires many costly and time-consuming fabrication iterations. To overcome the limitations of this expensive and time-consuming process, many studies have recently presented a markerless motion capture approach that reconstructs the time-varying skeletal motions from optical devices. However, the drawback of the markerless motion capture approach is that the phenomenon of occlusion of motion data occurs in real-time human simulation. In this study, we propose a systematic method of discriminating missing or inaccurate motion data due to motion occlusion and interpolating a sequence of motion frames captured by a markerless depth camera.

• The Journal of Korean Physical Therapy
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• 제36권1호
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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.

• 대한기계학회논문집A
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• 제35권7호
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• pp.785-790
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• 2011

본 연구에서는 인체의 하지부를 다물체 시스템으로 모델링하여 무릎관절에 걸리는 구속력의 불확실성을 추정하였다. 일반적으로 근육의 기계적인 특성은 Hill-type muscle model 이 사용되며 여기에 적용되는 인체의 특성과 해부학적인 데이터는 지난 십 수년 동안 크게 발전되었다. 그러나 정확하게 그것들을 안다는 것은 불가능하며 개인마다 다른점을 고려해야 할 필요가 있다. 본 논문에서는 Hill-type muscle model 과 함께 인체의 해부학적인 데이터를 통계 방법론을 이용하여 무릎 관절에 걸리는 구속력의 불확실성을 추정하였다. 초기 앉아있는 자세에서 일어서는 과정에서 작용하는 구속력을 추정하였으며 이때 인체 하지 근육의 특성을 musculoskeleton-actuator 를 이용하여 해석하였다.

• Journal of Biosystems Engineering
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• 제38권1호
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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.

• 한국정밀공학회지
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• 제28권1호
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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.

• 한국치위생학회지
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• 제15권4호
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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.

• 한국정밀공학회지
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• 제27권2호
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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.

• 산업경영시스템학회지
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• 제41권4호
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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.

• 국제물리치료학회지
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• 제12권1호
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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.