Trunk kinematic variables have been used to understand the risk of low back injuries in the workplace. Variability in the trunk kinematics as an individual performs a repetitive lifting task is an underexplored area of research. In the current study, it was hypothesized that workplace variables (starting height of lift and load weight) would have an impact on the variance in the kinematic and kinetic variables. Twenty participants performed 60 repetitions of an asymmetric lifting task under four different conditions representing two levels of load weight (5% or 10% of the participant's body weight) and two levels of starting height (80% or 120% of the participant's knee height). The Lumbar Motion Monitor was used to capture trunk kinematic variables from the concentric range of lifting motion while ground reaction forces were collected using a force platform. The primary dependent variables were the variance of kinematic and kinetic variables across these 60 repetitions. The results showed a significant effect of starting height on the variance of sagittal plane trunk kinematics with the lower starting height generating an increased variance (sagittal range of motion increased by 55%, average sagittal velocity increased by 95%, peak sagittal velocity increased by 105%, and peak sagittal acceleration increased by 130%). There was no consistent significant main effect of either independent variable on the variance of the transverse plane kinematics. Additionally, there was no significant effect of load weight on the variance of any trunk kinematic variables tested. In terms of ground reaction forces, it was shown that the starting height of the load had a significant effect on the variance of peak vertical ground reaction force, while the weight of the load had a significant effect on the variance of the peak shear force.
The electromyographic (EMG) normalization (often to maximum voluntary isometric contraction [MVIC]) is used to control for interparticipant and day-to-day variations. Repeated MVIC exertions may be inadvisable from participants’ safety perspective. This study developed a technique to predict the MVIC EMG from submaximal isometric voluntary contraction EMG. On day 1, 10 participants executed moment exertions of 100%, 60%, 40%, and 20% of the maximum (biceps brachii, rectus femoris, neck flexors, and neck extensors) as the EMG data were collected. On day 2, the participants replicated the joint moment values from day 1 (60%, 40%, and 20%) and also performed MVIC exertions. Using the ratios between the MVIC EMGs and submaximal isometric voluntary contraction EMG data values established on day 1, and the day 2 submaximal isometric voluntary contraction EMG data values, the day 2 MVIC EMGs were predicted. The average absolute percentage error between the predicted and actual MVIC EMG values for day 2 were calculated: biceps brachii, 45%; rectus femoris, 27%; right and left neck flexors, 27% and 33%, respectively; and right and left neck extensors, both 29%. There will be a trade-off between the required accuracy of the MVIC EMG and the risk of injury due to exerting actual MVIC. Thus, using the developed predictive technique may depend on the study circumstances.
Trunk kinematic variables have been used to understand the risk of low back injuries in the workplace. Variability in trunk kinematics has not been explored to the same level. In the current study, it was hypothesized that workplace variables (starting height and load weight) would have an impact on the variability in the kinematic variables describing trunk motion. Ten participants performed a repetitive lifting task under four different conditions representing two levels of load weight and starting height. The Lumbar Motion Monitor was used to capture key trunk kinematic variables from the concentric range of lifting motion. The dominant parameter in this experiment was found to be the starting height of the lift which significantly affected the variability of trunk kinematics in sagittal plane. In the transverse plane neither starting height of the load nor the weight of the load were found to influence the variability of trunk kinematics significantly.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.