Experimental investigation and model-based simulation on lifting biomechanics : an emphasis on age effects

• Main Author: Song, Jiahong
• Other Authors: Qu Xingda
• Format: Theses and Dissertations
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Industrial engineering::Human factors engineering
• Online Access: https://hdl.handle.net/10356/62505
• Institution: Nanyang Technological University

Lifting tasks are closely associated with low back pain (LBP) which is a highly prevalent musculoskeletal disorder (MSD) and causes tremendous economic costs for the society. Also, Load lifting makes perturbations to postural stability, and thus is often associated with an increased incidence of falls. Therefore, examining lifting biomechanics and postural stability can help provide implications on ergonomic interventions including optimal lifting task designs and effective training programs, and eventually well address occupational LBP and fall injury problems related to manual lifting. In this dissertation, lifting biomechanics and postural stability were investigated using a combination of experimental studies and model-based simulation. Experimental studies In the experimental studies, age-related biomechanical differences were examined during symmetric and asymmetric lifting. Eleven younger and twelve older participants were instructed to perform lifting tasks defined by different combinations of destination positions and load weights. Lifting biomechanics was assessed using the whole-body kinematics and low back moment. Postural stability was examined using the inclination angles of the centre of mass (COM) and the centre of pressure (COP) as well as ground reaction forces. The results regarding the lifting biomechanics showed that older adults adopted safer lifting strategies compared with younger adults in order to reduce low back load. For instance, the peak trunk sagittal flexion and transverse twisting angles were significantly lower (32% and 22% less, respectively) in older adults compared with those in younger ones. However, the average low back moment was significantly higher (about 32%) in older adults than that in younger ones, most probably due to the age-related increased body weight. Based on these findings, we recommend that physical exercise programs may be a more effective ergonomic intervention for reducing the risks of low back pain (LBP) in lifting among older adults, compared with instructions of safe lifting strategies. As for younger workers, instructions of safe lifting strategies would be effective in LBP risk reduction. The results on the lifting postural stability showed that older adults had smaller peak posterior and leftward ground reaction forces than did younger adults (56.5% and 38.6% less, respectively), but there was no age-related differences in the peak COM-COP inclination angles. It was also found that asymmetric lifting and larger load weights were associated with poorer postural stability. Based on the findings, it might be suggested that in order to maintain postural stability during lifting, especially in older adults, the lifted load weight be adjusted according to individual strengths, and asymmetric lifting be avoided if possible. Lifting motion simulation In the model-based simulation, two hybrid models using single- and multi-objective optimization, respectively, are developed for lifting motion simulation. The human body is modelled using a 2-D five-segment model. The lifting motions are predicted by solving a non-linear optimization problem subject to various kinematic and kinetic constraints. Specifically, the joint angular velocities are bounded by time-dependent constraints constructed from actual motions. In the single-objective optimization model, the objective function is defined based on a minimum-physical-effort performance criterion. In the multi-objective optimization (MOO) model, two performance criteria, including minimum physical effort and maximum load motion smoothness, were optimized simultaneously using a weighted-sum MOO approach. Symmetric lifting motions performed by younger and older adults under varied task conditions were simulated. Comparisons between the simulated motions and their corresponding actual motions were made to evaluate both models. The results showed that the absolute joint angle errors were less than 10°, which suggests the proposed model is able to accurately simulate 2-D lifting motions. The proposed models are also comparable with the existing motion simulation models in terms of the prediction accuracy. Moreover, the prediction accuracy is improved for both age groups (6.3% - 28.3% decreases in prediction errors) after using the MOO approach, compared to the single-objective optimization approach. Therefore, the MOO approach is recommended as a superior method for 2-D lifting motion simulation compared with the single-objective optimization. In summary, age-related differences in lifting biomechanics have been examined in experimental and model-based studies. The experimental results show that, compared with younger adults, older adults tend to use safer lifting strategies (e.g. reduced trunk flexion and lifting velocity) to reduce LBP risks and enhance postural stability during lifting. However, older adults may still have higher risks of LBP due to their relative larger low back load. Two hybrid models were developed for lifting motion simulation using the single-objective optimization and multi-optimization approaches, respectively. The models are able to predict accurate symmetric lifting motions for both younger and older adults, and reveal age-related differences in the mechanisms for planning lifting motions.