Gregory G. Knapik

Spine loading at different lumbar levels during pushing and pulling

As the nature of many materials handling tasks have begun to change from lifting to pushing and pulling, it is important that one understands the biomechanical nature of the risk to which the lumbar spine is exposed. Most previous assessments of push–pull tasks have employed models that may not be sensitive enough to consider the effects of the antagonistic cocontraction occurring during complex pushing and pulling motions in understanding the risk to the spine and the few that have considered the impact of cocontraction only consider spine load at one lumbar level. This study used an electromyography-assisted biomechanical model sensitive to complex motions to assess spine loadings throughout the lumbar spine as 10 males and 10 females pushed and pulled loads at three different handle heights and of three different load magnitudes. Pulling induced greater spine compressive loads than pushing, whereas the reverse was true for shear loads at the different lumbar levels. The results indicate that, under these conditions, anterior–posterior (A/P) shear loads were of sufficient magnitude to be of concern especially at the upper lumbar levels. Pushing and pulling loads equivalent to 20% of body weight appeared to be the limit of acceptable exertions, while pulling at low and medium handle heights (50% and 65% of stature) minimised A/P shear. These findings provide insight to the nature of spine loads and their potential risk to the low back during modern exertions.

Loading along the lumbar spine as influence by speed, control, load magnitude, and handle height during pushing

BACKGROUND Low back loading and risk associated with pushing activities have been poorly understood. Previous studies have demonstrated that increases in anterior/posterior shear forces are primarily initiated by antagonistic coactivity within the torso. Yet, few studies have considered the range of activities that might contribute to the antagonistic coactivation and subsequent spine loading. METHODS Twenty subjects were tested to examine how various physical factors might influence spine loads during pushing tasks that workers might experience in industrial settings. Load magnitude, speed of push, required control, and handle height were varied while pushing both carts and overhead suspended loads. A biologically-assisted biomechanical model was used to assess compression, anterior/posterior shear, and lateral shear over the various levels of the lumbar spine. FINDINGS Anterior/posterior shear loads were greatest at the upper levels of the lumbar spine and of a magnitude that would be of concern. Anterior/posterior shear was influenced by all experimental factors to varying degrees except for the nature of the load (cart vs. suspended). INTERPRETATION This study confirms the notion that pushing and pulling is not as simple a task as once believed since it entails a complex biomechanical activity. Spine shear forces result from a complex coactivation of trunk muscle activities and spine orientations that are influenced by several occupational factors. This study may help explain why low back pain rates in some work environments associated with lifting may not be reduced even when lifting interventions (that change the task from lifting to pushing) are employed.

An EMG-assisted model calibration technique that does not require MVCs

As personalized biologically-assisted models of the spine have evolved, the normalization of raw electromyographic (EMG) signals has become increasingly important. The traditional method of normalizing myoelectric signals, relative to measured maximum voluntary contractions (MVCs), is susceptible to error and is problematic for evaluating symptomatic low back pain (LBP) patients. Additionally, efforts to circumvent MVCs have not been validated during complex free-dynamic exertions. Therefore, the objective of this study was to develop an MVC-independent biologically-assisted model calibration technique that overcomes the limitations of previous normalization efforts, and to validate this technique over a variety of complex free-dynamic conditions including symmetrical and asymmetrical lifting. The newly developed technique (non-MVC) eliminates the need to collect MVCs by combining gain (maximum strength per unit area) and MVC into a single muscle property (gain ratio) that can be determined during model calibration. Ten subjects (five male, five female) were evaluated to compare gain ratio prediction variability, spinal load predictions, and model fidelity between the new non-MVC and established MVC-based model calibration techniques. The new non-MVC model calibration technique demonstrated at least as low gain ratio prediction variability, similar spinal loads, and similar model fidelity when compared to the MVC-based technique, indicating that it is a valid alternative to traditional MVC-based EMG normalization. Spinal loading for individuals who are unwilling or unable to produce reliable MVCs can now be evaluated. In particular, this technique will be valuable for evaluating symptomatic LBP patients, which may provide significant insight into the underlying nature of the LBP disorder.

Objective classification of vehicle seat discomfort

The objective of this study was to identify how physiological measures relate to self-reported vehicle seating discomfort. Twelve subjects of varied anthropometric characteristics were enrolled in the study. Subjects sat in two seats over a 2-h period and were evaluated via three physiological measures (near-infrared spectroscopy, electromyography and pressure mapping) yielding six testing sessions. Subjective discomfort surveys were recorded before and after each session for nine regions of the body. Conditional classification discomfort models were developed through dichotomised physiological responses and anthropometry to predict subjective discomfort in specific body locations. Models revealed that subjects taller than 171 cm with reduced blood oxygenation in the biceps femoris or constant, low-level muscle activity in the trapezius tended to report discomfort in the lower extremities or neck, respectively. Subjects weighing less than 58 kg with reduced blood oxygenation in the biceps femoris or unevenly distributed pressure patterns tended to report discomfort in the buttocks. The sensitivities and specificities of cross-validated models ranged between 0.69 and 1.00. Practitioner Summary: Discomfort has been studied extensively in order to enhance the seating design process. However, biomechanical and physiological responses relative to subjective discomfort have been largely ignored in the literature. Considering these responses along with anthropometry may provide insight into why a specific individual reports a seat as uncomfortable.

A biologically-assisted curved muscle model of the lumbar spine: Model structure.

BACKGROUND Biomechanical models have been developed to assess the spine tissue loads of individuals. However, most models have assumed trunk muscle lines of action as straight-lines, which might be less reliable during occupational tasks that require complex lumbar motions. The objective of this study was to describe the model structure and underlying logic of a biologically-assisted curved muscle model of the lumbar spine. METHODS The developed model structure including curved muscle geometry, separation of active and passive muscle forces, and personalization of muscle properties was described. An example of the model procedure including data collection, personalization, and data evaluation was also illustrated. FINDINGS Three-dimensional curved muscle geometry was developed based on a predictive model using magnetic resonance imaging and anthropometric measures to personalize the model for each individual. Calibration algorithms were able to reverse-engineer personalized muscle properties to calculate active and passive muscle forces of each individual. INTERPRETATION This biologically-assisted curved muscle model will significantly increase the accuracy of spinal tissue load predictions for the entire lumbar spine during complex dynamic occupational tasks. Personalized active and passive muscle force algorithms will help to more robustly investigate person-specific muscle forces and spinal tissue loads.

A biologically-assisted curved muscle model of the lumbar spine: Model validation

BACKGROUND Biomechanical models have been developed to predict spinal loads in vivo to assess potential risk of injury in workplaces. Most models represent trunk muscles with straight-lines. Even though straight-line muscles behave reasonably well in simple exertions, they could be less reliable during complex dynamic exertions. A curved muscle representation was developed to overcome this issue. However, most curved muscle models have not been validated during dynamic exertions. Thus, the objective of this study was to investigate the fidelity of a curved muscle model during complex dynamic lifting tasks, and to investigate the changes in spine tissue loads. METHODS Twelve subjects (7 males and 5 females) participated in this study. Subjects performed lifting tasks as a function of load weight, load origin, and load height to simulate complex exertions. Moment matching measures were recorded to evaluate how well the model predicted spinal moments compared to measured spinal moments from T12/L1 to L5/S1 levels. FINDINGS The biologically-assisted curved muscle model demonstrated better model performance than the straight-line muscle model between various experimental conditions. In general, the curved muscle model predicted at least 80% of the variability in spinal moments, and less than 15% of average absolute error across levels. The model predicted that the compression and anterior-posterior shear load significantly increased as trunk flexion increased, whereas the lateral shear load significantly increased as trunk twisted more asymmetric during lifting tasks. INTERPRETATION A curved muscle representation in a biologically-assisted model is an empirically reasonable approach to accurately predict spinal moments and spinal tissue loads of the lumbar spine.

Musculoskeletal disorder risk during automotive assembly: current vs. seated.

Musculoskeletal disorder risk was assessed during automotive assembly processes. The risk associated with current assembly processes was compared to using a cantilever chair intervention. Spine loads and normalized shoulder muscle activity were evaluated during assembly in eight regions of the vehicle. Eight interior cabin regions of the vehicle were classified by reach distance, height from vehicle floor and front to back. The cantilever chair intervention tool was most effective in the far reach regions regardless of the height. In the front far reach regions both spine loads and normalized shoulder muscle activity levels were reduced. In the middle and close reach regions spine loads were reduced, however, shoulder muscle activity was not, thus an additional intervention would be necessary to reduce shoulder risk. In the back far reach region, spine loads were not significantly different between the current and cantilever chair conditions. Thus, the effectiveness of the cantilever chair was dependent on the region of the vehicle.

Musculoskeletal disorder risk as a function of vehicle rotation angle during assembly tasks

Musculoskeletal disorders (MSD) are costly and common problem in automotive manufacturing. The research goal was to quantify MSD exposure as a function of vehicle rotation angle and region during assembly tasks. The study was conducted at the Center for Occupational Health in Automotive Manufacturing (COHAM) Laboratory. Twelve subjects participated in the study. The vehicle was divided into seven regions, (3 interior, 2 underbody and 2 engine regions) representative of work areas during assembly. Three vehicle rotation angles were examined for each region. The standard horizontal assembly condition (0° rotation) was the reference frame. Exposure was assessed on the spine loads and posture, shoulder posture and muscle activity, neck posture and muscle activity as well as wrist posture. In all regions, rotating the vehicle reduced musculoskeletal exposure. In five of the seven regions 45° of vehicle rotation represented the position that reduced MSD exposure most. Two of the seven regions indicated 90° of vehicle rotation had the greatest impact for reducing MSD exposure. This study demonstrated that vehicle rotation shows promise for reducing exposure to risk factors for MDS during automobile assembly tasks.

Development and testing of a moment-based coactivation index to assess complex dynamic tasks for the lumbar spine

Background Many methods exist to describe coactivation between muscles. However, most methods have limited capability in the assessment of coactivation during complex dynamic tasks for multi‐muscle systems such as the lumbar spine. The ability to assess coactivation is important for the understanding of neuromuscular inefficiency. In the context of this manuscript, inefficiency is defined as the effort or level of coactivation beyond what may be necessary to accomplish a task (e.g., muscle guarding during postural stabilization). The objectives of this study were to describe the development of an index to assess coactivity for the lumbar spine and test its ability to differentiate between various complex dynamic tasks. Methods The development of the coactivation index involved the continuous agonist/antagonist classification of moment contributions for the power‐producing muscles of the torso. Different tasks were employed to test the range of the index including lifting, pushing, and Valsalva. Findings The index appeared to be sensitive to conditions where higher coactivation would be expected. These conditions of higher coactivation included tasks involving higher degrees of control. Precision placement tasks required about 20% more coactivation than tasks not requiring precision, lifting at chest height required approximately twice the coactivation as mid‐thigh height, and pushing fast speeds with turning also required at least twice the level of coactivity as slow or preferred speeds. Interpretation Overall, this novel coactivation index could be utilized to describe the neuromuscular effort in the lumbar spine for tasks requiring different degrees of postural control. HighlightsA method to assess coactivation from a systems‐perspective is proposed.The method was tested on various complex dynamic manual materials handling tasks.The index could distinguish between tasks of differing degrees of postural control.High levels of postural control (i.e., precision tasks) result in a higher index.

Curved muscles in biomechanical models of the spine: a systematic literature review

Abstract Early biomechanical spine models represented the trunk muscles as straight-line approximations. Later models have endeavoured to accurately represent muscle curvature around the torso. However, only a few studies have systematically examined various techniques and the logic underlying curved muscle models. The objective of this review was to systematically categorise curved muscle representation techniques and compare the underlying logic in biomechanical models of the spine. Thirty-five studies met our selection criteria. The most common technique of curved muscle path was the ‘via-point’ method. Curved muscle geometry was commonly developed from MRI/CT database and cadaveric dissections, and optimisation/inverse dynamics models were typically used to estimate muscle forces. Several models have attempted to validate their results by comparing their approach with previous studies, but it could not validate of specific tasks. For future needs, personalised muscle geometry, and person- or task-specific validation of curved muscle models would be necessary to improve model fidelity. Practitioner Summary: The logic underlying the curved muscle representations in spine models is still poorly understood. This literature review systematically categorised different approaches and evaluated their underlying logic. The findings could direct future development of curved muscle models to have a better understanding of the biomechanical causal pathways of spine disorders.