| For the last several decades, manual materials handling has attracted great interest from researchers in many disciplines, primarily because of the huge amount of work and financial losses, and human sufferings caused by low back pain and injuries. Consequently, it is a major concern to researchers and organizations to develop means to predict, control, and prevent such injuries. Therefore, research has focused on the establishment of ergonomic workspace designs and employee training.; Biomechanic modeling plays an important role in estimating individuals' lifting capacities, comparing different lifting modes, and designing workspace conditions. Using such models, the potential for injuries can be estimated in advance and greatly reduce the need for often difficult, expensive and potentially invasive laboratory measurements.; This research is primarily intended to develop a dynamic simulation model to form lifting trajectories, and to predict associated joint moments during lifting. A two-dimensional human body model provides a sagittally symmetric five-rigid-link mechanism. The equations of motion are derived using a Newton-Euler formulation. Simulation results are then compared with experimental findings.; Since the dynamic models of complex systems, such as biomechanical ones, tend to be of high dimension and severely nonlinear, and as such can require extensive computation. Therefore, this research's primary focus is on the development of a robust and efficient algorithm for dynamics simulation of multibody biomechanical systems.; Furthermore, human body is highly redundant because any task can be accomplished in infinitely many different ways. Thus, there is no unique solution to the problem of generating lifting trajectories. However, it is believed that human locomotion obeys a certain “principle of optimality.” Hence, this problem is overcome with the use of optimization techniques.; A number of proposed objective functions appearing in the literature, including jerk, work, moment minimization, and a linear combination of these three, are assessed and quantified to properly choose a cost function reflecting most of the aspects of locomotion. In addition, the moment cost function is revised by embedding dynamic joint strengths instead of static ones. Moreover, the importance of considering kinetic as well as kinematic measures is emphasized.; Lastly, a prediction tool is coded to generate optimum trajectories and animate this lift for a given set of input parameters, e.g. weight and posture. The results presented in this study are proof of how effective, timesaving, and economical biomechanic simulations are in both suggesting design and evaluating ergonomic tasks. |
