Search

Estimates of the amount of force exerted by a muscle using electromyography (EMG) rely partially upon the accuracy of the reference point used in the normalization technique. Accurate representations of muscle activities are essential for use in EMG-driven spinal loading models. The expected maximum contraction (EMC) normalization method was evaluated to explore whether it could be used to assess individuals who are not capable of performing a maximum exertion such as a person with a low back injury. Hence, this study evaluated the utility of an EMG normalization method (Marras and Davis, A non-MVC EMG normalization technique, Part 1, method development. Journal of Electromyography and Kinesiology 2000) that draws upon sub-maximal exertions to determine the reference points needed for normalization of the muscle activities. The EMC normalization technique was compared to traditional MVC-based EMG normalization by evaluating the spinal loads for 20 subjects (10 males and 10 females) performing dynamic lifts. The spinal loads (estimated via an EMG-assisted model) for the two normalization techniques were very similar with differences being <8%. The model performance variables indicated that both normalization techniques performed well (r(2)>0.9 and average error below 6%) with only the muscle gain being affected by normalization method as a result in different reference points. Based on these results, the proposed normalization technique was considered to be a viable method for EMG normalization and for use in EMG-assisted models. This technique should permit the quantitative evaluation of muscle activity for subjects unable to produce maximum exertions.

Normalization of muscle activity has been commonly used to determine the amount of force exerted by a muscle. The most widely used reference point for normalization is the maximum voluntary contraction (MVC). However, MVCs are often subjective, and potentially limited by sensation of pain in injured individuals. The objective of the current study was to develop a normalization technique that predicts an electromyographic (EMG) reference point from sub-maximal exertions. Regression equations predicting maximum exerted trunk moments were developed from anthropometric measurements of 120 subjects. In addition, 20 subjects performed sub-maximal and maximal exertions to determine the necessary characteristic exertions needed for normalization purposes. For most of the trunk muscles, a highly linear relationship was found between EMG muscle activity and trunk moment exerted. This analysis determined that an EMG-moment reference point can be obtained via a set of sub-maximal exertions in combination with a predicted maximal exertion (expected maximum contraction or EMC) based upon anthropometric measurements. This normalization technique overcomes the limitations of the subjective nature for the MVC method providing a viable assessment method of individuals with a low back injury or those unwilling to exert an MVC as well as could be extended to other joints/muscles.

Study Design: An experimental study of fatiguing isometric trunk extension was conducted to investigate the spinal loading estimated from an electromyogram-assisted biomechanical model., Objective: To evaluate the sensitivity of the model outputs to two crucial assumptions: electromyogram-force relationship and method of gain estimation., Summary of Background Data: In the proposed electromyogram-assisted models of the trunk, the nature of the electromyogram-force relationship and the wide variation in reported muscle gains can result in a wide variation in estimates of spinal loading. Given the absence of any gold standard for validation of muscle forces, the delineation of confidence intervals for the estimated loads has become critical., Methods: Ten subjects performed a fatiguing isometric trunk extension while the net muscular torque output and trunk muscular activity were measured. An electromyogram-assisted model was used to estimate the torque output and spinal loading. Linear and nonlinear erector spinae electromyogram-force relationships and three methods for gain estimation were investigated: constant gain determined from an initial maximum extension exertion, constant gain based on the fatiguing exertion, and a time-varying gain from the fatigue test., Results: The predicted torque was not sensitive to the electromyogram-force relationship; the nonlinear model produced 10% lower estimates of peak spinal compression force and 14% higher estimates of peak anterior shear force. The gain determined from an initial calibration exertion underestimated the external torque and underpredicted the peak compression force by 20%, compared with gains calculated in the fatigue test., Conclusion: The nature of the electromyogram-force relationship and of the method for estimating the gain significantly affect the outcomes of an electromyogram-assisted model of spinal loading.

One of the continuing challenges in biomechanics has been to assess loading of the spine during dynamic lifting exertions. A model was developed to accurately simulate multi-dimensional spinal loads and trunk moments from measured muscle coactivity and external forces during free-dynamic lifting exertions. Model validity was demonstrated by comparing measured and predicted trunk extension moments. Its purpose was to examine realistic representations of lifting kinetics, kinematics, and dynamic trunk mechanics that may influence spinal loading, and to demonstrate that EMG-assisted modeling techniques can be applied to the analysis of free-dynamic exertions. Spinal loads and trunk moments were predicted from the muscle force vectors and external loads. Muscle tensile forces were determined from the product of normalized EMG data modulated to account for contractile dynamics, muscle cross sectional area, and muscle force per unit cross-sectional area. Model output was physiologically valid, i.e. average predicted muscle force per unit cross-sectional area of 50-65 N cm-2, and accurately predicted measured, dynamic, lifting moments, with an average R2 = 0.81 in the sagittal plane and R2 = 0.76 in the lateral plane. Results indicated that compressive and shear loading increased significantly with exertion load, lifting velocity, and trunk asymmetry.

An EMG-assisted, low-back, lifting model is presented which simulates spinal loading as a function of dynamic, asymmetric, lifting exertions. The purpose of this study has been to develop a model which overcomes the limitations of previous models including static or isokinetic mechanics, inaccurate predictions of muscle coactivity, static interpretation of myoelectric activity, and physiologically unrealistic or variable muscle force per unit area. The present model predicts individual muscle forces from processed EMG data, normalized as a function of trunk angle and asymmetry, and modified to account for muscle length and velocity artifacts. The normalized EMGs are combined with muscle cross-sectional area and intrinsic strength capacity as determined on a per subject basis, to represent tensile force amplitudes. Dynamic internal and external force vectors are employed to predict trunk moments, spinal compression, lateral and anterior shear forces. Data from 20 subjects performing a total of 2160 exertions showed good agreement between predicted and measured values under all trunk angle, asymmetry, velocity, and acceleration conditions. The design represents a significant step toward accurate, fully dynamic modeling of the low-back in multiple dimensions. The benefits of such a model are the insights provided into the effects of motion induced, muscle co-activity on spinal loading in multiple dimensions.

This study examined the effects of trunk speed and exertion level on temporal aspects of trunk muscle activity patterns during dynamic, asymmetric lifting. Electromyographic (EMG) data from eight trunk muscles were collected along with trunk torque output, position, and velocity data during several repetitions of four speed/loading combination conditions. During analysis, each muscle's EMG record was reduced to three key events: a start, a peak, and an end point. For each subject, temporally ordered event lists were constructed for each test condition. Networks of events that consistently occurred regardless of loading or speed levels were constructed for each subject. Two event pairs occurred consistently for all subjects under all conditions, whereas some pairs occurred in association with specific speed or resistance levels. Temporal information related to muscle activity could be used in biomechanical models in order to predict changes in spinal loading during the course of workplace tasks.

Most biomechanical assessments of spinal loading during industrial work have focused on estimating peak spinal compressive forces under static and sagittally symmetric conditions. The main objective of this study was to explore the potential of feasibly predicting three-dimensional (3D) spinal loading in industry from various combinations of trunk kinematics, kinetics, and subject-load characteristics. The study used spinal loading, predicted by a validated electromyography-assisted model, from 11 male participants who performed a series of symmetric and asymmetric lifts. Three classes of models were developed: (a) models using workplace, subject, and trunk motion parameters as independent variables (kinematic models); (b) models using workplace, subject, and measured moments variables (kinetic models); and (c) models incorporating workplace, subject, trunk motion, and measured moments variables (combined models). The results showed that peak 3D spinal loading during symmetric and asymmetric lifting were predicted equally well using all three types of regression models. Continuous 3D loading was predicted best using the combined models. When the use of such models is infeasible, the kinematic models can provide adequate predictions. Finally, lateral shear forces (peak and continuous) were consistently underestimated using all three types of models. The study demonstrated the feasibility of predicting 3D loads on the spine under specific symmetric and asymmetric lifting tasks without the need for collecting EMG information. However, further validation and development of the models should be conducted to assess and extend their applicability to lifting conditions other than those presented in this study. Actual or potential applications of this research include exposure assessment in epidemiological studies, ergonomic intervention, and laboratory task assessment. [ABSTRACT FROM AUTHOR]

Traditionally most biomechanical models that are used to estimate the loading experienced by the spine during work focus on static, two-dimensional representations of the work. However, most work tasks impose loads on the lumbar spine under dynamic, three-dimensional conditions. The objective of this study was to describe the structure and logic of a model that is capable of producing estimates of spine loading under three-dimensional motion conditions. This model is intended for use primarily under laboratory conditions. The model was designed initially for workplace simulation in which the trunk is moving under symmetric and asymmetric constant velocity lifting conditions. Future embellishments may enable the model to be used under free dynamic conditions. The model predicts lumbar spine compression, shear, and torsional forces as well as trunk torque production continuously throughout the exertion. This information may be compared with spine tolerance limits so that the risk of causing a vertebral end-plate microfracture by workplace requirements could be determined. [ABSTRACT FROM AUTHOR]

A three-dimensional motion model has been developed that estimates loads on the lumbar spine under laboratory conditions that simulate manual materials handling conditions. Eleven subjects experienced spinal loading during an experiment in which conditions of trunk velocity, trunk torque output, and trunk asymmetric posture were varied in a series of isokinetic velocity trunk extensions. The electromyographic activity of 10 trunk muscles, subject anthropometry, and trunk kinetics were used as input to a biomechanical simulation model described in Part I of this study. The model calculated estimates of compression, shear, and torsion loading in the lumbar spine, as well as the torque production of the trunk, continuously throughout the exertion. Trunk torque estimates derived from this model were compared with measured trunk torque. The effects of trunk motion, posture, and torque level on spine loading as estimated by the model are discussed. It was concluded that this approach provides a straightforward means of assessing loading of the spine attributable to laboratory simulations of workplace conditions. [ABSTRACT FROM AUTHOR]