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Ergonomic are known as the study of work. It helps the worker to fit with the environment of the workplace for example the tools, equipment and the work station. Poor ergonomic practice can affect the performance of the worker and the quality of the product besides causing loss to the company. This study have three main purposes which is to establish the optimal set up of the dynamic RULA analysis in UTHM, to compare the performance of static RULA analysis with the current dynamic RULA analysis and to identify the effect of current working posture to the musculoskeletal disorder of the university staffs. The ergonomic tools that was used in this study are Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) and Rapid upper limb assessment (RULA). Besides that, motion captures system and Kinect camera were used for 3D dynamic RULA analysis. Meanwhile, 2D static analysis recorded the video of the subject motion simultaneously to quantitatively compare the result to 3D dynamic analysis. This research found that the 3D dynamic analysis is more accurate compare with the 2D static analysis. This can be proved by comparing the length of the joint point of 2D static analysis and 3D dynamic analysis with the actual length. 3D dynamic method provided 3 axes while the other method only provided 2 axes. 3D dynamic method in this paper was analyzed numerically by a software while 2D static method was analyzed manually by the user and prone to human error and thus not entirely accurate. The result for comparing the performance of the 2D static analysis and 3D dynamic analysis showed that the respondent 1 and 2 have high risk on getting neck pain based on the RULA score. CMDQ analysis showed that the body part of respondent 1 and 2 that are most probably affected by MSD was leg.

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Abstract. Motion capture system has recently being brought to light and drawn much attention in many fields of research, especially in biomechanics. Marker-based motion capture systems have been used as the main tool in capturing motion for years. Marker-based motion capture systems are very pricey, lab-based and beyond reach of many researchers, hence it cannot be applied to ubiquitous applications. The game however has changed with the introduction of depth camera technology, a markerless yet affordable motion capture system. By means of this system, motion capture has been promoted as more portable application and does not require substantial time in setting up the system. Limitation in terms of nodal coverage of single depth camera has widely accepted but the performance of dual depth camera system is still doubtful since it is expected to improve the coverage issue but at the same time has bigger issues on data merging and accuracy. This work appraises the accuracy performance of dual depth camera motion capture system specifically for athletes' running biomechanics analysis. Kinect sensors were selected to capture motions of an athlete simultaneously in three-dimension, and fused the recorded data into an analysable data. Running was chosen as the biomechanics motion and interpreted in the form of angle-time, angleangle and continuous relative phase plot. The linear and angular kinematics were analysed and represented graphically. Quantitative interpretations of the result allowed the deep insight of the movement and joint coordination of the athlete. The result showed that the root-mean-square error of the Kinect sensor measurement to exact measurement data and rigid transformation were 0.0045 and 0.0077291 respectively. The velocity and acceleration of the subject were determined to be 3.3479 ms -1 and −4.1444 ms -2 . The result showed that the dual Kinect camera motion capture system was feasible to perform athletes' biomechanics analysis.