• Journal of the Ergonomics Society of Korea
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• v.24 no.3
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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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.9
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• pp.2191-2204
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• 1993

A sensor system has been developed to measure the posture(position and orientation) of mobile robots working in industrial environments. The proposed sensor system consists of a CCD camera, retro-reflective landmarks, a strobe unit and an image processing board. The proposed hardware system can be built in economic price compared to commercial vision systems. The system has the capability of measuring the posture of mobile robots within 60 msec when a 386 personal computer is used as the host computer. The experimental results demonstrated a remarkable performance of the proposed sensor system in the posture measurement of mobile robots - the average error in position is less than 3 mm and the average error in orientation is less than 1.5.

• Journal of the Ergonomics Society of Korea
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• v.14 no.1
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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.

• Korean Journal of Applied Biomechanics
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• v.14 no.3
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.596-605
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• 1994

An efficient measurement and evaluation system for hand tool tasks will provide a practical solution to the problem of designing and evaluating manual tool tasks in the workplace. 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 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 eighteen 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 integrating 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. These tasks are becoming increasingly important areas of occupational health and safety of the country.

• Physical Therapy Korea
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• v.30 no.3
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• pp.174-183
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• 2023

Background: Office workers experience neck or back pain due to poor posture, such as flexed head and forward head posture, during long-term sedentary work. Posture correction is used to reduce pain caused by poor posture and ensures proper alignment of the body. Several assistive devices have been developed to assist in maintaining an ideal posture; however, there are limitations in practical use due to vast size, unproven long-term effects or inconsistency of maintaining posture alignment. We developed a headphone and necklace posture correction system (HANPCS) for posture correction using an inertial measurement unit (IMU) sensor that provides visual or auditory feedback. Objects: To demonstrate the test-retest reliability and concurrent validity of neck and upper trunk flexion measurements using a HANPCS, compared with a three-dimensional motion analysis system (3DMAS). Methods: Twenty-nine participants were included in this study. The HANPCS was applied to each participant. The angle for each action was measured simultaneously using the HANPCS and 3DMAS. The data were analyzed using the intraclass correlation coefficient (ICC) = [3,3] with 95% confidence intervals (CIs). Results: The angular measurements of the HANPCS for neck and upper trunk flexions showed high intra- (ICC = 0.954-0.971) and inter-day (ICC = 0.865-0.937) values, standard error of measurement (SEM) values (1.05°-2.04°), and minimal detectable change (MDC) values (2.92°-5.65°). Also, the angular measurements between the HANPCS and 3DMAS had excellent ICC values (> 0.90) for all sessions, which indicates high concurrent validity. Conclusion: Our study demonstrates that the HANPCS is as accurate in measuring angle as the gold standard, 3DMAS. Therefore, the HANPCS is reliable and valid because of its angular measurement reliability and validity.

• Journal of Biomedical Engineering Research
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• v.39 no.1
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• pp.10-15
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• 2018

In this paper, we present a wearable measurement system for monitoring rounded shoulders. The system contains a shoulder correction band and a stretch sensor that can correct and measure shoulder posture, respectively. The capacitance of the stretch sensor changes linearly according to changes in the shoulders. To verify measurement, a motion analysis system was used as the reference to compare the change in the rounded angles of the shoulders and the change in the stretch sensor's capacitance. The results indicated that there is a high correlation between the two changes and the system can be used as a monitoring device for rounded shoulders.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.97-103
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• 2020

The proposed system is composed of two parts, an AI physical fitness measurement part and an AI physical fitness management part. In the AI fitness measurement part, a guide to physical fitness measurement and accurate calculation of the measured value are performed through deep learning-based pose recognition. Based on these measurements, the AI fitness management part designs personalized exercise programs and provides them to dedicated smart applications. To guide the measurement posture, the posture of the subject to be measured is photographed through a webcam and the skeleton line is extracted. Next, the skeletal line of the learned preparation posture is compared with the extracted skeletal line to determine whether or not it is normal, and voice guidance is provided to maintain the normal posture.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.99-104
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• 2019

Recently, modern people are increasing the incidence of various musculoskeletal diseases due to wrong posture. Prevention is possible through proper posture habit, but it is not easy to recognize posture by oneself. Various studies have been conducted to monitor persistent posture in daily life, but most studies using constrained measurement methods and high-cost measurement equipment are not suitable for daily life. In this paper, we implemented a posture discrimination system using a FSR sensor array that can induce posture correction spontaneously through sitting posture monitoring in daily life. The implemented system is designed as a cushion type so it is easy to apply to existing chair. In addition, it can identify five most common postures in everyday life, and can monitor real-time through Android-based smart-phone monitoring application. For the performance evaluation of the implemented system, each posture was measured 50 times repeatedly. As a result, 97.6% accuracy was confirmed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.87-91
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• 2004

High aged society is rapidly progressing in Japan. The rate of aged person more than 65 years old in the population are estimated 25 % in 2017 and rate of younger population will be decreased at same time. As a result, it is estimated that the human resources that is looking after or supporting for the aged person will be drained in Japan. In the other hand, the society has to provide high quality of life in order to be improved living environment for aged person. To decrease the share of nursing and caring for the aged person, it is required that new supporting systems for aged person have to build up as soon as possible. But it is required that various kind of measurement for posture and movement in activities with a simple and single detector for the aged person. The measurement instrument has to be lightweight and simple structure. The results give us a simple measurement method are classified that the posture of sitting down, lying down in stationary statuses and walking, running and going to up and down on the stairs in moving statuses. The detected data will plane to transmit to wireless mobile system to the host computer.