Lumbar loading during lifting: a comparative study of three measurement techniques

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Abstract

Low back loading during occupational lifting is thought to be an important causative factor in the development of low back pain. In order to regulate spinal loading in the workplace, it is necessary to measure it accurately. Various methods have been developed to do this, but each has its own limitations, and none can be considered a “gold standard”. The purpose of the current study was to compare the results of three contrasting techniques in order to gain insight into possible sources of error to which each is susceptible. The three techniques were a linked segment model (LSM), an electromyographic (EMG)-based model, and a neural network (NN) that used both EMG and inertial sensing techniques. All three techniques were applied simultaneously to calculate spinal loading when eight volunteers performed a total of eight lifts in a laboratory setting. Averaged results showed that, in comparison with the LSM, the EMG technique calculated a 25.5±33.4% higher peak torque and the NN technique a 17.3±10.5% lower peak torque. Differences between the techniques varied with lifting speed and method of lifting, and could be attributed to differences in anthropometric assumptions, antagonistic muscle activity, damping of transient force peaks by body tissues, and, specific to the NN, underestimation of trunk flexion. The results of the current study urge to reconsider the validity of other models by independent comparisons.

Introduction

Epidemiological studies generally report a positive association between work-related physical loading and the occurrence of low back pain [30]. In addition, it is argued that the relative risk of developing low back pain is underestimated if imprecise measures of this loading are used [8], [30].

Unfortunately, there is no perfect method of measuring peak spinal loading during dynamic activities. In vitro measurements of intradiscal pressure have been used to predict the compressive force acting on the lumbar intervertebral discs [29], but the relationship between pressure and compressive force varies with loading history [3] and posture [2], and invasive pressure-needle techniques cannot be applied to investigate dynamic lifting tasks. The most widely used and extensively validated non-invasive method of quantifying spinal loading is the linked segment model (LSM), which quantifies net torques around joints [18], [22], [32]. However, LSMs have several limitations. First, they are not well-suited for large scale or long-duration monitoring of low back loading, since their application is time-consuming [33]. Second, LSMs only provide an estimate of “net external loading” in terms of net reactive torques and forces. Antagonistic muscle forces are not taken into account, causing considerable underestimation of spinal loading in upright posture [16]. However, during forward bending and lifting movements, antagonistic muscle activity is less important [21]. Electromyographic (EMG)-driven [26], [28], [34] or optimization-based [9] muscle models can be used (in conjunction with LSMs) to apportion net torques to different muscles, so that antagonistic muscle forces and spinal forces can be estimated.

Another method of measuring spinal loading is to quantify joint torques by recording the skin-surface EMG activity during dynamic activities, and then calibrating EMG signals against torque generation during static contractions [11], [25], [33]. This approach requires corrections to be made to account for the effects of muscle length and contraction velocity on the EMG–torque relationship [11]. This direct technique has the potential to measure antagonistic muscle forces accurately, and it can be adapted easily for use in the workplace, but it relies heavily on correction factors which have not been fully validated.

A second method that is potentially applicable in the workplace, was recently developed by Baten et al. [4]. This method combines EMG data with measurements of trunk angle velocity and acceleration obtained from miniature skin-mounted sensors. In a calibration procedure an artificial neural network (NN) is trained to learn the relationship between these signals and the net torque.

Each of these techniques for measuring spinal loading is suitable under some (but not all) circumstances, and none can be termed a “gold standard”. Consequently, it is difficult to determine which, if any, of the techniques, is accurate. However, if two or more techniques could be shown to give similar values of spinal loading, even though they are based upon quite different principles and assumptions, then this would increase confidence that they were accurate (although it would not prove it). Any consistent differences between their estimates of spinal loading might also provide insights into the size and source of the errors to which each technique is susceptible.

The objective of the present investigation was to compare the outcome of three techniques that were used simultaneously to measure torques at the lumbosacral joint (L5-S1) during forward bending and lifting activities. The recently-developed three-dimensional linked-segment model of Kingma et al.[18] was compared with the direct EMG technique of Dolan and Adams [11] and with the method of Baten et al. [4]. To obtain a realistic view on differences between models we compared original versions of the models, and made no attempt to harmonize assumptions.

It might be expected that the relative accuracy of the three techniques would depend on muscle length, contraction velocity, and the need for stabilizing co-contractions of the trunk muscles. Therefore, a range of lifting activities was studied, including straight-leg and bent-leg lifts, performed at slow and fast speeds.

Section snippets

Methods

Eight healthy young males (weight 72.3±7.2 kg, height 1.82±0.09 m) participated in the experiment after signing an informed consent. The subjects performed sagittally-symmetrical lifting movements with a 15.7 kg box, placed 5 cm in front of the feet. The box was lifted from a 10 mm shelf to hip height. The box had a handle on each side, which, at the start of the lift was 17 cm above the ground. A switch on the box generated a synchronization pulse at lift off. All subjects performed eight

Results

Over all lifting movements, application of the EMG model resulted in a 25.5±33.4% higher estimate of the peak L5-S1 torque as compared to the LSM (Table 1). In contrast, the NN model estimate of the L5-S1 peak torque was 17.3±10.5% lower in comparison with the LSM estimate. Mean torques were lower for the EMG model compared to the other models (Table 1).

Averaged curves (Fig. 1) show that the rise and fall of the L5-S1 torque was steeper in the EMG model as compared to the other two models. This

Discussion

The peak torques estimated by the three models, are all within the range of values reported previously for lifting comparable loads [12], [15], [23].

The EMG model produced higher and more variable peak torque values in comparison with the other two models. Differences between peak torque estimates of the NN model and the LSM were quite consistent: a lower peak torque was calculated by the NN model in 42 out of 45 trials.

Differences between models can be random or systematic, both within and

Idsart Kingma is a lecturer at the Faculty of Human Movement Sciences of the Vrije Universiteit Amsterdam where he is currently teaching courses on ergonomics. He has an MSc in human movement sciences and finished his PhD on the biomechanics of lifting in 1999. Currently, his main research interests are mechanical aspects of low back loading and neuromuscular control of joint stability.

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    Idsart Kingma is a lecturer at the Faculty of Human Movement Sciences of the Vrije Universiteit Amsterdam where he is currently teaching courses on ergonomics. He has an MSc in human movement sciences and finished his PhD on the biomechanics of lifting in 1999. Currently, his main research interests are mechanical aspects of low back loading and neuromuscular control of joint stability.

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    Chris Baten received a masters degree in electrical engineering with minors in biomedical engineering and mathematical teaching from Twente University in Enschede 1990. He is since employed at the Roessingh Research and Development institute in Enschede where he is a researcher and developer of “human function assessment tools”. His work is centered around practical assessment tools in rehabilitation and ergonomics addressing both fundamental and practical aspects of surface EMG and motion analysis. Currently he is heading a group and a research consortium developing ambulatory methods for (back) load exposure assessment combining inertial movement sensing and surface EMG methods.

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    Patricia Dolan is a Senior Lecturer in the Department of Anatomy, University of Bristol. She obtained a PhD in muscle physiology before developing her main research interest, which is the relationship between spinal function and back pain. She has developed EMG-based techniques for quantifying muscle forces on the spine, and for analysing fatigue in skeletal muscles. She is a member of the editorial boards of Clinical Biomechanics and European Spine Journal.

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    Huub Toussaint is associate professor at the Faculty of Human Movement Sciences of the Vrije Universiteit Amsterdam. He finished his MSc Human Movement Sciences in 1985 and Medicine in 1987. He finished his PhD on Mechanics and Energetics of Swimming in 1988. Became Principal Investigator of the Amsterdam Spine Unit in 1988. He returned to swimming research when appointed as director of the research school in 1999. He is a member of the editorial board of the Journal of Biomechanics.

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    Jaap van Dieën is associate professor at the Faculty of Human Movement Sciences of the Vrije Universiteit Amsterdam, where he teaches courses on tissue mechanics and pathophysiology of work-related musculoskeletal disorders. He leads a research group that focuses on the mechanical and neural aspects of injuries of the musculoskeletal system, with an emphasis on the lumbar spine. Currently, his main research interest is the relationship between motor control and loading of the musculoskeletal system, where especially the interaction of muscle coordination and muscle fatigue is an important research topic. He is a member of the editorial board of the Journal of Electromyography and Kinesiology and of Human Movement Science.

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    Michiel de Looze graduated as a human movement scientist in 1988 and got his PhD in 1992. As a researcher he worked at the Faculty of Human Movement Sciences until 1998. Since then, he has been doing research at TNO Work and Employment, Department of Ergonomics and Innovation. The subject of his research has always been the occupational physical load and its health consequences. Recently, the focus of his research has shifted from the effects of stressful activities like lifting, pushing and pulling towards the specific problems of low-intensity work, for instance low back pain in sitting and repetitive strain injury in computer workers (over 30 full papers in international refereed journals describe his work).

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    Michael Adams is a Senior Research Fellow in the Department of Anatomy, University of Bristol, UK. He has a BSc in natural philosophy and a PhD in spinal mechanics. Research interests include the mechanical function and failure of intervertebral discs and articular cartilage, and the tissues' biological responses to mechanical loading. With his wife Patricia Dolan he has developed techniques to quantify spinal loading in living people. He is a member of the editorial boards of Spine, Clinical Biomechanics and European Spine Journal.

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