Electromyographic (EMG)-assisted biomechanical models have been used to predict spinal reactions forces and evaluate risk of low back disorders (LBDs). One of the challenges facing previous EMG-assisted biomechanical models is that they rely heavily on the active muscle force component. In certain kinds of exertions (eccentric exertions and exertions at or near the full flexion trunk postures) the passive components of the extensor mechanism play a significant role in the net extensor moment, and these are not captured in the traditional EMG-assisted modeling technique.; This study introduces a new EMG assisted biomechanical model that includes passive components. Empirical experiments were conducted to evaluate the improvements in model predictions when these passive tissue components were considered. Eighteen subjects participated in two groups of experiments. In experiment one, subjects performed repetitive, eccentric and concentric lifting motions in a controlled dynamometer task environment. In experiment two, subjects performed a repetitive, free dynamic lifting and lowering exertions. In both experiments, the subjects were asked to reach their full trunk flexion posture during the lifting motion. As they performed these tasks, the EMG activity of the major trunk muscles was collected. The passive tissue forces were estimated through the use of a finite element model of the lumbar region. Estimates of the net internal moment from two different EMG-assisted models (with and without passive components) were compared with the measured net external moment to provide insight into the utility of the inclusion of these passive tissue forces.; The results indicated the necessity of involving passive components in the EMG-assisted biomechanical model when studying the trunk flexion/extension exertions at full trunk flexion postures. The mean absolute error between the measured moment and model predicted moment was significantly smaller for the model with passive components as compared to the model without passive components (19.6 Nm vs. 25.5 Nm in experiment one, and 19.4 Nm vs. 54.9 Nm in experiment two, respectively). The R squared value of the measured and predicted load demonstrated great improvements by involving passive components (37% to 66% in experiment one, 12% to 75% in experiment two, respectively).; In a second phase of this research, this new EMG-assisted model was used to study the differences in the biomechanical response between lowering (eccentric) and lifting (concentric) exertions. Eccentric exertions induced significantly (p0.05) higher mean maximum spine compression forces in both experiments as compared to concentric exertions (3680N vs. 3114N in experiment one, and 2516N vs. 1870N in experiment two, respectively). The variability of the spinal load in these two types of exertions was also compared in terms of the average absolute deviation from the median (AADM) of the compression values (where the median refers to the median values of the multiple repetitions of the same task). This AADM of the maximum compression force was 281N for concentric versus 472N for eccentric exertions in experiment one, and 134N for concentric versus 207N for eccentric exertions in experiment two. These differences were shown to be affected by the lifting/lowering velocity, knee posture and load levels. This result has significant meaning when considering the relative risk of lifting and lowering exertions in the workplace.; This study demonstrated an innovative method to quantitatively include the effects of the passive components of the spine into the EMG-assisted biomechanical model and showed the importance of involving these passive components in the estimation of the spinal load at the full flexed posture and eccentric exertions. The results of this study have also provided some insight into the relative risk of eccentric vs. concentric exertions by understanding the trade-offs between the active and passive tissues o
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