A biomechanical comparison between expert and novice manual materials handlers using a multi-joint EMG-assisted optimization musculoskeletal model of the lumbar spine
Introduction
There is a clear relationship between low back disorders (LBD) and mechanical load (National Research Council, 2001). Manual materials handling (MMH) is a work activity associated with LBD because it can generate high mechanical load on the low back. A chief modifying factor of LBD risks is expertise (Marras, 2006), an expert being a person with high-level specific skills gained through years of practice and a clean record of work-related injuries. Ergonomic observations of MMH tasks indicate that expert workers have acquired techniques that differ from those employed by novices (Authier et al., 1996), generally leading to the speculation that expert techniques should be safer. Comprehensive measurements on experts are thus needed to create benchmark data to document their techniques and ultimately contribute in the development of MMH training programs (Plamondon et al., 2010). However, biomechanical comparisons of MMH techniques between expert and novice report mixed results on kinematic/kinetic variables (Lee and Nussbaum, 2012, Lee and Nussbaum, 2013, Plamondon et al., 2010). In the study of Plamondon et al. (2010), experts bend significantly less their trunk but their lumbar joint net moments are similar to those of novices. Hence, potential internal effect of expertise is evoked without detailed musculoskeletal analyses.
The importance of lumbar spine musculoskeletal models to assess spinal loads, stability, and risk of injury is well recognized (see Reeves and Cholewicki (2003) for a review). In MMH situations however, only novices or inexperienced subjects are tested. To our knowledge, there has been no study with such models on actual expert workers. The prediction, with sufficient biological integrity, of muscle forces and spinal loads to compare expert vs novice requires an EMG-driven model (Cholewicki et al., 1995, Gagnon et al., 2001). Moreover, a full multiple-joint musculoskeletal model of the lumbar spine should be resolved to predict coherent muscle and joint forces (Arjmand et al., 2007, Gagnon et al., 2011, Stokes and Gardner-Morse, 1995).
Consequently, the current study aims to compare experts and novices in the context of series of box transfers simulated by actual workers (Plamondon et al., 2010). A lumbar spine musculoskeletal model using a multiple-joint EMG-assisted optimization resolution method (Gagnon et al., 2011) was formulated to assess spinal loads, muscle forces, and passive spine resistance. The premise of the study is that, in equivalent external loading situations, experts use safer and more efficient techniques. It is hypothesized that experts (1) use less passive muscle forces and spine resistance, (2) deploy more active muscle forces, and (3) sustain smaller lumbar spine joint forces.
Section snippets
Experimental study
Details on data collection and processing are described elsewhere (Plamondon et al., 2010). Ten male experts (age 39.1 yr SD 10.0; mass 71.8 kg SD 9.5; height 1.72 m SD 0.08) and 10 male novices (age 23.3 yr SD 3.2; mass 69.0 kg SD 7.3; height 1.74 m SD 0.05) with complete EMG dataset were retained for the present study. Four tasks were selected (Fig. 1) to compare, in addition to expertise (Expert vs Novice), the effect of the height of lifting/deposit (H1: ground level vs H4: top of the pile) and
Results
For brevity, only the major effects and interactions with expertise are reported here. Additional results are included in the Electronic Supplementary material as well as all tables with a number ended by S.
Discussion
Results of the present study confirmed that the distribution of internal moments are modulated by worker expertise for the investigated MMH tasks. Experts flexed less their trunk and exerted more active muscle forces (hypothesis 2 accepted) while novices relied more on passive resistance of the muscles and ligamentous spine (hypothesis 1 accepted). For novices, the additional passive contributions came from global extensor muscles (ICPT and LGPT), local extensor muscles (LGPL, MUF and ICPL) and
Conclusion
In summary, the present results show that experts were more efficient than novices in partitioning internal moment contributions to balance net (external) loading. Thus, safer handling practices might be seen as a result of experience of experts. Limited use of passive tissues by experts could be associated to their good back injury record, an inclusion criterion for these subjects. Consequently, novices in manual material handling should be exposed as early as possible to proper principles,
Conflict of interest statement
There is no conflict of interest in this study.
Acknowledgements
This work was supported by grants from the Robert-Sauvé Occupational Health and Safety Research Institute (IRSST 2010-0023) of Quebec and the Natural Sciences and Engineering Research Council of Canada (NSERC 130827). Authors gratefully acknowledge Erik Salazar for assistance in post-processing of experimental data.
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