Summary

Musculoskeletal disorders (MSD), spinal disorders in particular, are a burden for society as well as for those who suffer from them. In Québec, 21,228 cases of spinal disorder were reported in 2011, accounting for close to 30 percent of all compensated occupational injuries. The lumbar region of the spine is the area injured most often (60 percent of injuries) and overexertion is the causative agent most commonly reported (40 percent). According to the National Research Council (2001), there is a clear correlation between back injuries and mechanical load during manual handling. Better quantification of lumbar loading in the workplace is required, however, for documentation of this correlation. As lumbar loading cannot be measured directly, biomechanical models have been developed for this purpose.

The basic principle of existing biomechanical models is to estimate forces acting on active structures (muscles) as well as passive structures (discs and ligaments) of the trunk by balancing external moments (loads), which are caused by body movements and external loads, with internal moments, which result from muscle and ligament action. External measurements (model input) must thus be taken to generate model estimates (output). The estimates are of different types: muscle force, ligament stress and compressive and shear force on discs/vertebrae. In Québec, two researchers developed internal biomechanical models of the lumbar spine based on very different approaches: (1) a physiological approach based on electromyographic (EMG) measurements assisted by optimization (EMGAO model); (2) a kinematics-driven approach based on kinematic measurements, also assisted by optimization (KD model). A comparison of these two models in an earlier study showed certain weaknesses and corrections were made as a result.

This research project has four parts: the first two, which used the KD model, and the fourth, which used the EMGAO model, made it possible to evaluate model input and output sensitivity in the presence of different effects and experimental manipulations. The third part is an application of the KD model and its comparison to the most popular ergonomic tools for predicting lumbar loading.

Part 1: The main objective of this research was to find out if different external forces (different orientations, positions and magnitudes but generating the same net moment at L5-S1) called on the same muscle groups and generated the same lumbar load. The results 1) confirmed that orientation and load height have a major impact on the neuromuscular response of the trunk and lumbar loading; and 2)   made it possible to improve KD model results by considering new input.

Part 2: The objective of this research was to study the reactions of trunk muscles (reflex responses) to sudden disturbances of the trunk. There is a risk of injury with such sudden disturbances, which can occur when lifting loads or patients, or just by slipping and falling—that is, mechanisms of accidental injury. Reflex responses and their mechanical impacts were evaluated using external measurements (EMG, kinematic and external forces) and KD model estimates under different disturbance conditions likely to affect reflex responses. The results showed different physiological and biomechanical responses which were not always in the direction expected based on existing hypotheses and were not all detected by each of the different types of measurement. It appears, then, that the reflex responses of trunk muscles depend on a number of parameters that interact and that have not all been identified yet. However, this study showed that the EMG measurements and the KD model estimates provide different but complementary information. In addition, it seems that kinematic measurements of the trunk can basically provide the information required to quantify the mechanical effects of reflex responses. In other words, the KD model does not seem to add any value to the kinematic measurements for quantification of response reflexes. On the other hand, these models (KD and lumbar stability) do provide information about internal forces stemming from trunk disturbances, which helps in assessing the risk of lumbar injury.

Part 3: To compensate for the limitations of the lifting analysis tools currently available for predicting lumbar load, regression (predictive) equations were developed in earlier research using the KD model. These equations showed a simple correlation between lumbar load (at L4-L5 or L5-S1) and four independent input variables: (1) load carried in hands; (2) horizontal distance between the load and the shoulder; (3) sagittal trunk flexion; and (4) lumbar/pelvic rotation ratio. The goal of this research was to extend the use of these equations to asymmetrical loading and to compare the results yielded by these equations to estimates obtained with four of the most popular lifting analysis tools. The results indicate that these new equations are an advance over the 1991 National Institute of Occupational Safety and Health (NIOSH) lifting equation, the tool most commonly used by ergonomists. The results also show major differences between the five tools tested, but fortunately there was more agreement among them on predicted compressive force at L5-S1. It was not possible to determine which of the tools was most accurate, as there is no standard measure in this field. However, two of the tools gave results more consistent with intradiscal pressure data, including the one developed in this part of the research.

Part 4: Extremely rich and detailed data on expert and novice material handlers was collected in an earlier research project. Analyses using external measurements yielded different results for the two groups, suggesting effects on internal loading of the lumbar spine. The goal of this research was to verify these expected effects using the EMGAO model. The results demonstrated that the expert handlers were more efficient than the novices in terms of strategy used to distribute internal effort to offset equivalent external moments. With experience acquired over the years, expert handlers seem to develop safer and more efficient methods, such as less extensive use of passive spinal tissue—which could explain their low injury rate.

In sum, this four-part research project provided a better understanding of the strengths and weaknesses of the KD and EMGAO models and of their utility in explaining and quantifying internal lumbar loading.