• 척추신경추나의학회지
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• 제10권1호
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• pp.47-61
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• 2015

Objectives : The purpose of this study is body parameters characteristics through posture analysis system of musculoskeletal problem patient Methods : Posture analysis system were performed for 164 patients to measure body parameters such as Q-angle, body inclination, neck inclination, PCMT(posterior cervical muscle tension), Knee flexion and posture balance. Statistical analysis using statistical analysis techniques and Pearson correlation coefficients was performed to assess the body parameters obtained by posture analysis system. Results : More than half of people out of 164 reported low back pain, 34.8% of the total was found to have neck pain. There was not a significant difference between genders from the characteristics of gender based body parameters expect for the statistical difference in Q angle, PCMT. There was a significant correlation between low back pain and multiple response status. There was a significant correlations between knee pain and Q angle. Also There was a significant correlations between pelvic pain and posture balance of ankle. Conclusions : Posture analysis system can be used to perform the analysis in place of X-ray measuring body posture and clinical parameters. The results of this study are expected to be the basis for further research on the clinical application of posture analysis system.

• 한방재활의학과학회지
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• 제24권4호
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• pp.177-185
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• 2014

Objectives This study analyzed the correlation between body parameters measured using X-ray and Chuna posture analysis system to determine their clinical value in diagnosing and evaluating skeletomuscular diseases. Methods X-ray and Chuna posture analysis system were performed for 105 patients to measure physical characteristics such as Interacromial angle, Pelvic obliquity angle, Structural leg length discrepancy (SLLD), Midpatella-midtalus angle (MMA) and Q-angle, Anterior head translation (AHT), Anterior superior iliac spine to posterior superior iliac spine angle (ASIS-PSIS angle), Interscapular angle, Scoliotic angle and Cobb's angle. Statistical analysis using statistical analysis techniques and Pearson correlation coefficients was performed to assess the body parameters obtained by X-ray and Chuna posture analysis system. Results Significant correlations were observed between the values for Interacromial angle, Pelvic obliquity angle, SLLD, MMA and Q-angle, AHT, ASIS-PSIS angle, Interscapular angle, Scoliotic angle and Cobb's angle obtained by X-ray and Chuna posture analysis system. Significant correlations were also observed between right MMA and left Q-angle as well as between left MMA and right Q-angle. Conclusions Chuna posture analysis system can be used instead of X-ray measure body parameters and perform posture analysis in clinical practice. This study's findings are expected to serve as a basis for further research on the clinical application of Chuna posture analysis system.

• 대한인간공학회지
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• 제14권1호
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• pp.69-81
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• 1995

Few studies on the biomechanical analysis of hand postures and tool handling tasks exist because of the lack of appropriate measurement techniques for hand force. A measurement system for the finger forces and joint angles for the analysis of manual tool handling tasks was developed in this study. The measurement system consists of a force sensing glove made from twelve Force Sensitive Resistors and an angle-measuring glove (Cyberglove$^{TM}$, Virtual technologies) with eighteem joint angle sensors. A biomechanical model of the hand using the data from the measurement system was also developed. Systems of computerized procedures were implemented inte- grating the hand posture measurement system, biomechanical analysis system, and the task analysis system for manual tool handling tasks. The measurement system was useful in providing the hand force data needed for an existing task analysis system used in CTD risk evaluation. It is expected that the hand posture measurement developed in this study will provide an efficient and cost-effective solution to task analysis of manual tool handling tasks.s.

• 한국운동역학회지
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• 제14권3호
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• pp.49-65
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• 2004

The purpose of this study is development of posture evaluation and Range of Motion(ROM) system by using digital vision analysis method. The results of this study are as follows. First, Scoliosis evaluation through this research measurement system represent 3mm error in 7 cervical point and deepest lumbar point, 0.7mm error in other point. This mean this research measurement system have a reliability for scoliosis evaluation. Second, for spine line evaluation on high fat subject, we need reconstrection spine line after measurement for fat thickness in 7 cervical point and deepest lumbar point. Third, In pedioscope error test, it present 0.01848cm in X axis and 0.01757cm in Y axis. This results mean pedioscope have a reliability foot evaluation. Forth, Posture evaluation and Range of Motion measurement system by using digital vision analysis method can fast measure in range of motion and foot evaluation and posture. therefore we can expect this system application in young people posture clinic center and hospital and so on.

• 한국인터넷방송통신학회논문지
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• 제11권5호
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• pp.151-157
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• 2011

본 논문은 인체의 일정한 운동을 하는 동안에 시간의 변화에 따른 자세균형을 분석한다. 자세균형은 자세에 움직임 변화를 주어 다중파라미터로 변화 산출 값으로 나타냈다. 이렇게 산출된 값을 분석하여 균형자세 시스템을 구성하였다. 자세의 움직임 변화는 3가지 방법으로 눈을 감고 뜨는 방법, 머리를 앞뒤로 움직이는 방법과 상체 움직임 방법이다. 측정한 다중파라미터의 항목은 시각(Vision), 전정기관(Vestibular), 체성감각(Somatosensory), 중추신경계(CNS)이고, 측정파라미터의 평가는 안정성(Stability)으로 확인하였다. 균형자세 시스템은 이러한 변화에서 발생한 신호를 데이터 획득 장치에서 얻고, 신호를 신호 전달 장치를 통하여 전달하였으며, 데이터 분석을 통하여 자세에 대한 평가로 활용하였다. 궤환 시스템은 획득한 데이터를 재조정하는데 사용하였다. 발생되는 신호는 푸리에변환 하였고, 사용되는 주파수는 0.1Hz, 0.1-0.5Hz, 0.5-1Hz와 1Hz 이상을 사용하였다. 본연구의 결과로 시간 변화에서 운동부하를 부여함에 따라 인체의 자세변화에 따라 발생된 신호를 멀티파라미터 상에서 장시간 변화에 대한 파라미터 간의 변화를 통하여 개별 신체의 자세균형에 검증할 수 있는 시스템이 이루어져야 하며, 이를 통하여 새로운 검증 시스템에 활용할 수 있을 것으로 예상한다.

• 대한인간공학회지
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• 제24권3호
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• pp.43-52
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• 2005

A two-dimensional posture measurement system was developed to evaluate the risks of work-related musculoskeletal disorders(MSDs) easily on various conditions of work. The posture measurement system is an essential tool to analyze the workload for preventing work-related musculoskeletal disorders. Although several posture measurement systems have been developed for workload assessment, some restrictions in industry still exist because of its difficulty on measuring work postures. In this study, an image recognition algorithm was developed based on a neural network method to measure work posture. Each joint angle of human body was automatically measured from the recognized images through the algorithm, and the measurement system makes it possible to evaluate the risks of work-related musculoskeletal disorders easily on various working conditions. The validation test on upper body postures was carried out to examine the accuracy of the measured joint angle data from the system, and the results showed good measuring performance for each joint angle. The differences between the joint angles measured directly and the angles measured by posture measurement software were not statistically significant. It is expected that the result help to properly estimate physical workload and can be used as a postural analysis system to evaluate the risk of work-related musculoskeletal disorders in industry.

• 농업과학연구
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• 제42권2호
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• pp.117-124
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• 2015

In forest work, working conditions are very hard to improve. The good posture is believed to bring about direct improvements such as accident prevention. Therefore, this research carried on analysis of working posture in forest work (construct in stepping-stone) using OWAS analysis system. According to the analytical results provided by OWAS, the ratio of category III (Work posture has a distinctly harmful effect on the musculoskeletal system) has shawn that worker 2 was 32.2%, worker 1 was 25.2% and worker 3 was 15.5%. Furthermore, the ratio of category IV (Work posture with an extremely harmful effect on the musculoskeletal system) has shown that worker 2 was 9.8%, worker 3 was 1.4% and worker 1 was 1.2%. According to the OWAS method, percentage of OWAS action categories III and IV in the worker 2 was higher than another workers.

• 전자공학회논문지
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• 제52권6호
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• pp.117-125
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• 2015

앉아있는 시간이 긴 현대인들에게 바른 자세를 유지하도록 하는 것은 중요하다. 자세 교정을 위한 치료는 많은 시간과 비용이 소요되며, 전문의의 지속적인 관찰이 필요하다. 그러므로 사용자 스스로 자신의 자세를 판단하고 교정하기 위한 시스템이 필요하다. 본 논문에서는 사용자의 자세 데이터를 취득하여 취득된 자세가 정상자세인지 비정상자세인지 판단한다. 사용자의 자세 데이터 취득을 위해 관성 센서를 이용한 4개 관절 기반 모션캡쳐 시스템을 제안한다. 이 시스템을 통해 대상자의 자세 데이터를 취득하고, 취득한 데이터를 기반으로 특징을 추출하여 DB를 구축한다. 구축한 DB를 K-means 클러스터링 알고리즘을 이용하여 자세 학습을 수행한 후, 정상자세와 비정상자세를 분류한다. 관절의 회전각도, 위치정보, 분석정보를 이용하여 자세분류를 수행한 결과, 정상자세 판단 성공률은 99.79%로 나타났다. 이 결과로 미루어 4개 관절에 대한 특징을 이용하여 사용자의 자세를 판단 가능하며, 향후 척추질환 예방 시스템에 적용하여 사용자의 자세를 교정하는 데 도움을 줄 수 있을 것으로 판단된다.

• 대한정형도수물리치료학회지
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• 제19권2호
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• pp.1-9
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• 2013

Background: The purpose of this study is to analysis of correlation upper body according to forward head posture. Methods: The subjects of this study were 40 female university students who were equally and randomly allocated to a forward head posture group, normal group. Using general posture system, electromyograph, visual analogue scale, tape measurement, neck disability index were evaluated. Results: There was positive correlation between posture analysis and Sternocleidomastoid, neck flexion (p<.05). There was positive correlation between Craniovertebral angle (CVA) and trapezius upper, VAS (p<.05). There was negative correlation between posture analysis and CVA (p<.05). There was negative correlation between Cranial rotation angle and CVA (p<.05). Conclusion: Increased forward head posture lead to increase of pain, muscles activity, so it suggests to be necessary on the prevention of dysfunction and limited activities daily living.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.74-83
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• 2019

This study designs a squat posture recognition system that can provide correct squat posture guidelines. This system comprises two modules: a Kinect camera for monitoring users' body movements and a Wii Balance Board(WBB) for measuring balanced postures with legs. Squat posture recognition involves two states: "Stand" and "Squat." Further, each state is divided into two postures: correct and incorrect. The incorrect postures of the Stand and Squat states were classified into three and two different types of postures, respectively. The factors that determine whether a posture is incorrect or correct include the difference between shoulder width and ankle width, knee angle, and coordinate of center of pressure(CoP). An expert and 10 participants participated in experiments, and the three factors used to determine the posture were measured using both Kinect and WBB. The acquired data from each device show that the expert's posture is more stable than that of the subjects. This data was classified using a support vector machine (SVM) and $na{\ddot{i}}ve$ Bayes classifier. The classification results showed that the accuracy achieved using the SVM and $na{\ddot{i}}ve$ Bayes classifier was 95.61% and 81.82%, respectively. Therefore, the developed system that used Kinect and WBB could classify correct and incorrect postures with high accuracy. Unlike in other studies, we obtained the spatial coordinates using Kinect and measured the length of the body. The balance of the body was measured using CoP coordinates obtained from the WBB, and meaningful results were obtained from the measured values. Finally, the developed system can help people analyze the squat posture easily and conveniently anywhere and can help present correct squat posture guidelines. By using this system, users can easily analyze the squat posture in daily life and suggest safe and accurate postures.