An evaluation of predictive methods for estimating cumulative spinal loading

Effect of muscular fatigue on the cumulative lumbar damage during repetitive lifting task: a comparative study of damage calculation methods

Several methods have been put forward to quantify cumulative loads; however, limited evidence exists as to the subsequent damages and the role of muscular fatigue. The present study assessed whether muscular fatigue could affect cumulative damage imposed on the L5-S1 joint. Trunk muscle electromyographic (EMG) activities and kinematics/kinetics of 18 healthy male individuals were evaluated during a simulated repetitive lifting task. A traditional EMG-assisted model of the lumbar spine was modified to account for the effect of erector spinae fatigue. L5-S1 compressive loads for each lifting cycle were estimated based on varying (i.e. actual), fatigue-modified, and constant Gain factors. The corresponding damages were integrated to calculate the cumulative damage. Moreover, the damage calculated for one lifting cycle was multiplied by the lifting frequency, as the traditional approach. Compressive loads and the damages obtained through the fatigue-modified model were predicted in close agreement with the actual values. Similarly, the difference between actual damages and those driven by the traditional approach was not statistically significant (p = 0.219). However, damages based on a constant Gain factor were significantly greater than those based on the actual (p = 0.012), fatigue-modified (p = 0.017), and traditional (p = 0.007) approaches.Practitioner summary: In this study, we managed to include the effect of muscular fatigue on cumulative lumbar damage calculations. Including the effect of muscular fatigue leads to an accurate estimation of cumulative damages while eliminating computational complexity. However, using the traditional approach also appears to provide acceptable estimates for ergonomic assessments.

Problematic video gaming is negatively associated with bone mineral density in adolescents

Adolescent bone health may be negatively impacted by problematic video gaming (PVG) due to factors such as prolonged screen time, poor sleep quality, and increased depression. Although sedentary behaviors have been linked to decreased bone mass, there is limited research on how PVG impacts bone health. We aimed to evaluate the association between PVG and bone mineral density (BMD) in adolescents by comparing the BMD z-scores of adolescents with and without PVG and by identifying PVG-related risk factors that may affect low BMD scores. This cross-sectional study took place between May 2019 and August 2021 with 110 adolescents who played video games for at least two hours per day. Data on screen time, game genre, tobacco, alcohol, caffeine consumption, and vigorous physical activity status were recorded. PVG was assessed using the Internet Gaming Disorder-Short Form (IGDS9-SF), with scores ≤ 16 comprising the control group and > 16 the PVG group. Sleep quality was assessed by Pittsburgh Sleep Quality Index, and depression was evaluated by Children's Depression Inventory. Dual-energy X-ray absorptiometry measurements of femoral neck and lumbar spine BMD were compared between the two groups. The mean age of the participants was 14.2 ± 1.8 years, and 86.4% were males. The PVG group exhibited lower femoral neck z-scores (p = 0.013) and a higher proportion of adolescents with low femoral neck BMD risk (27.8% vs 9.7%, p = 0.041). Lumber spine z-scores did not differ (p = 0.271). Despite poorer depressive symptoms and sleep quality in the PVG group, they were not associated with low BMD risk (OR 1.02, 95% CI 0.97-1.08, p = 0.398 and OR 1.00, 95% CI 0.87-1.18, p = 0.972, respectively). Among all PVG-related risk factors, video game time (aOR = 1.22, 95% CI = 1.06-1.41, p = 0.006) and vigorous physical activity amount (aOR = 2.86, 95% CI = 0.93-8.76, p = 0.080) showed the strongest associations with femoral neck z-scores.  Conclusion: The results of this study, showing a negative association between PVG and femoral neck BMD in adolescents, underscore the importance evaluating, monitoring, and supporting lower extremity bone health in adolescents with PVG. What is Known: • Adolescents with problematic video gaming are at risk for depression, impaired sleep; sedentary lifestyle; consumption of tobacco, alcohol, and drugs; and high caffeine intake. • These risk factors might lead to compromised bone health. What is New: • Problematic video gaming is associated with the low femoral neck bone mineral density risk in adolescents. • Extended video game time and reduced physical activity are found to be the primary risk factors.

Spinal injury rates and specific causation in motor vehicle collisions

Motor vehicle collisions (MVCs) are a leading cause of acute spinal injuries. Chronic spinal pathologies are common in the population. Thus, determining the incidence of different types of spinal injuries due to MVCs and understanding biomechanical mechanism of these injuries is important for distinguishing acute injuries from chronic degenerative disease. This paper describes methods for determining causation of spinal pathologies from MVCs based on rates of injury and analysis of the biomechanics require to produce these injuries. Rates of spinal injuries in MVCs were determined using two distinct methodologies and interpreted using a focused review of salient biomechanical literature. One methodology used incidence data from the Nationwide Emergency Department Sample and exposure data from the Crash Report Sample System supplemented with a telephone survey to estimate total national exposure to MVC. The other used incidence and exposure data from the Crash Investigation Sampling System. Linking the clinical and biomechanical findings yielded several conclusions. First, spinal injuries caused by an MVC are relatively rare (511 injured occupants per 10,000 exposed to an MVC), which is consistent with the biomechanical forces required to generate injury. Second, spinal injury rates increase as impact severity increases, and fractures are more common in higher-severity exposures. Third, the rate of sprain/strain in the cervical spine is greater than in the lumbar spine. Fourth, spinal disc injuries are extremely rare in MVCs (0.01 occupants per 10,000 exposed) and typically occur with concomitant trauma, which is consistent with the biomechanical findings 1) that disc herniations are fatigue injuries caused by cyclic loading, 2) the disc is almost never the first structure to be injured in impact loading unless it is highly flexed and compressed, and 3) that most crashes involve predominantly tensile loading in the spine, which does not cause isolated disc herniations. These biomechanical findings illustrate that determining causation when an MVC occupant presents with disc pathology must be based on the specifics of that presentation and the crash circumstances and, more broadly, that any causation determination must be informed by competent biomechanical analysis.

Estimating Trunk Angle Kinematics During Lifting Using a Computationally Efficient Computer Vision Method

OBJECTIVE

A computer vision method was developed for estimating the trunk flexion angle, angular speed, and angular acceleration by extracting simple features from the moving image during lifting.

BACKGROUND

Trunk kinematics is an important risk factor for lower back pain, but is often difficult to measure by practitioners for lifting risk assessments.

METHODS

Mannequins representing a wide range of hand locations for different lifting postures were systematically generated using the University of Michigan 3DSSPP software. A bounding box was drawn tightly around each mannequin and regression models estimated trunk angles. The estimates were validated against human posture data for 216 lifts collected using a laboratory-grade motion capture system and synchronized video recordings. Trunk kinematics, based on bounding box dimensions drawn around the subjects in the video recordings of the lifts, were modeled for consecutive video frames.

RESULTS

The mean absolute difference between predicted and motion capture measured trunk angles was 14.7°, and there was a significant linear relationship between predicted and measured trunk angles (R² = .80, p < .001). The training error for the kinematics model was 2.3°.

CONCLUSION

Using simple computer vision-extracted features, the bounding box method indirectly estimated trunk angle and associated kinematics, albeit with limited precision.

APPLICATION

This computer vision method may be implemented on handheld devices such as smartphones to facilitate automatic lifting risk assessments in the workplace.

+Gz Exposure and Flight Duty Limitations

BACKGROUND: High +G_z exposure is known to cause spinal problems in fighter pilots, but the amount of tolerable cumulative +G_z exposure or its intensity is not known. The aims of this study were to assess possible breaking points during a flight career and to evaluate possible determinants affecting pilots' spines.METHODS: Survival analysis was performed on the population who started their jet training in 1995-2015. The endpoint was permanent flight duty restriction due to spinal disorder. Then the quantified G_z exposure and possible confounding factors were compared between those pilots with permanent flying restriction and their matched controls. Cumulative G_z exposure was measured sortie by sortie with fatigue index (FI) recordings. FI is determined by the number of times certain levels of G_z are exceeded during the sorties.RESULTS: The linear trend of the survival curve indicates an annual 0.86% drop out rate due to spinal problems among the fighter pilot population. A conditional logistic regression did not find any difference in the FI between cases and controls (OR 0.96, 95%CI 0.87-1.06). No statistical difference was found for flight hours, a sum of intensive flying periods, fitness tests, or with nicotine product use. Additionally, a maximum +G_z limitation without airframe restriction was assessed and is presented as a useful tool to manage loading and developed symptoms.DISCUSSION: No particular breaking point during follow-up or individual factor was found for G_z induced spinal disorders. The results of the study outline the multifactorial nature of the problem. Thus, multifactorial countermeasures are also needed to protect pilots' health.Sovelius R, Honkanen T, Janhunen M, Mäntylä M, Huhtala H, Leino T. +Gz exposure and flight duty limitations. Aerosp Med Hum Perform. 2022; 93(4):390-395.

Why cumulative loading calculated using non-weighted integration may not be suitable for assessing physical stress of the lower back: an empirical investigation of strain during lifting and lowering tasks

When work-related physical stress is assessed using non-weighted integration, it is assumed that different loading conditions have a sufficiently comparable effect on the human body as long as the area under the loading curve is the same. Growing evidence cast doubt on whether this simple calculation can adequately estimate physical work-related strain. This study investigates in vivo, focussing on the lower back, whether the non-weighted method adequately reflects work-related physical strain of the lower back. Strain data resulting from lifting/lowering tasks performed in a laboratory study with an identical area under the loading curve but different load intensities were compared. Results showed that the non-weighted method does not sufficiently reflect the resulting muscular, cardiovascular and perceived strain but underestimates the influence of higher load intensity even in the range of medium physical exposure. Further research is needed regarding the determination of weighting factors and limit values. Practitioner Summary Given the dynamic nature of most physical work activities, the assessment of time-varying loading of the lower back is of particular interest in practice. Results show that the widely used non-weighted calculation method does not accurately reflect the resulting physical strain but underestimates the influence of higher load intensity.Abbreviations: MSD: musculoskeletal disorders; WMSD: work-related musculoskeletal disorders; KIM-LHC: Key Indicator Method Lifting, Holding, Carrying; RES: right erector spinae longissimus; LES: left erector spinae longissimus; HR: heart rate; RPE: rating of perceived exertion; EMG: surface electromyography; ECG: electrocardiography; SENIAM: Surface ElectroMyoGraphy for the Non-Invasive Assessment of Muscles; MVC: maximum voluntary contraction; ANOVA: analysis of variance; Std. error: standard error HIGHLIGHTSResults of this empirical investigation suggest that the widely used non-weighted calculation method is not fully suitable for calculating cumulative loading of the lower back.Even in the range of medium physical exposure the non-weighted calculation method does not accurately reflect the resulting strain on the human body but tends to underestimate the influence of higher load intensity due to higher external weight.Despite the same cumulative loading value obtained when using the non-weighted method, the resulting physical strain values are generally about 20-25% higher.The results may be used to further develop ergonomic assessment methods in order to avoid a misclassification of loading conditions and to prevent the risk of overexertion.

Minimizing Low Back Cumulative Loading during Design of Manual Material Handling Tasks: An Optimization Approach

OCCUPATIONAL APPLICATIONSWe present a practical method for minimizing low-back cumulative loading that leverages digital human modeling capabilities and optimization using an evolutionary algorithm. We demonstrate use of the method in a simulated lifting task. Our results show that this method is robust to different routines for calculating cumulative loading. The proposed method can aid ergonomics engineers in addressing a potential risk factor early in the design stage, even in the absence of an established threshold limit value, and it provides a time saving by eliminating the need to adjust workplace parameters across many design possibilities.

Risk assessments using the Strain Index and the TLV for HAL, Part II: Multi-task jobs and prevalence of CTS

The Strain Index (SI) and the American Conference of Governmental Industrial Hygienists (ACGIH) threshold limit value for hand activity level (TLV for HAL) have been shown to be associated with prevalence of distal upper-limb musculoskeletal disorders such as carpal tunnel syndrome (CTS). The SI and TLV for HAL disagree on more than half of task exposure classifications. Similarly, time-weighted average (TWA), peak, and typical exposure techniques used to quantity physical exposure from multi-task jobs have shown between-technique agreement ranging from 61% to 93%, depending upon whether the SI or TLV for HAL model was used. This study compared exposure-response relationships between each model-technique combination and prevalence of CTS. Physical exposure data from 1,834 workers (710 with multi-task jobs) were analyzed using the SI and TLV for HAL and the TWA, typical, and peak multi-task job exposure techniques. Additionally, exposure classifications from the SI and TLV for HAL were combined into a single measure and evaluated. Prevalent CTS cases were identified using symptoms and nerve-conduction studies. Mixed effects logistic regression was used to quantify exposure-response relationships between categorized (i.e., low, medium, and high) physical exposure and CTS prevalence for all model-technique combinations, and for multi-task workers, mono-task workers, and all workers combined. Except for TWA TLV for HAL, all model-technique combinations showed monotonic increases in risk of CTS with increased physical exposure. The combined-models approach showed stronger association than the SI or TLV for HAL for multi-task workers. Despite differences in exposure classifications, nearly all model-technique combinations showed exposure-response relationships with prevalence of CTS for the combined sample of mono-task and multi-task workers. Both the TLV for HAL and the SI, with the TWA or typical techniques, appear useful for epidemiological studies and surveillance. However, the utility of TWA, typical, and peak techniques for job design and intervention is dubious.

Wearable Technologies: How Will We Overcome Barriers to Enhance Worker Performance, Health, And Safety?

Wearable technologies are changing the way that people interact with the world. Personal physical activity monitors are becoming ubiquitous in our society and are helping to advance user health and performance, yet, many workplaces have not broadly adopted the technologies beyond either low fidelity/complexity pedometer-based applications or, inversely, high fidelity/complexity lab- based evaluations. Considering adoption of wearable technologies in the workplace, some technology-related concerns include; (1) types of data needed to be captured (motion, muscle, temperature, etc.), (2) constraints of sensor design, such as human-sensor system integration (embedded in clothing versus strapped to person), ruggedness, form factor, or weight, and (3) types of data interpretation and feedback applications that exist to translate data into useful information (communication, trend mapping, situational awareness).

From the research design perspective, there is difficulty in conducting studies capable of demonstrating a safety or productivity that supports employing wearable technology in the workplace. Difficulties include poor access to workplaces and varied worker populations to conduct research, lack of funding, and the need for extended time periods to demonstrate utility (often longer than the lifecycle of the technology in question). Considering the industry perspective, barriers to adopting wearable technologies include lack of convincing data, cost, and anticipation of reduced productivity, poor usability, and/or information overload. Additionally, employee privacy concerns and public policy implications may provide challenges. Another potential barrier may be that some practitioners, however, believe that innovative technologies may be adopted without rigorous testing. This may have short term success to garner interest but may create a barrier to adoption in the long term if the devices are found to have no near or mid- term efficacy.

The overarching goal of the session will be to improve understanding of different perspectives as it relates to the use, barriers, and adoption of wearable technologies and generate discussion for overcoming such barriers to improve the process of research to practice to research (RtPtR). The panelists are from a variety of industry sectors and academia. The session will begin with a 5- minute introductory statement from each panelist; therefore, most of the session will be a discussion between panelists and audience.

The Composite Strain Index (COSI) and Cumulative Strain Index (CUSI): methodologies for quantifying biomechanical stressors for complex tasks and job rotation using the Revised Strain Index

The Composite Strain Index (COSI) quantifies biomechanical stressors for complex tasks consisting of exertions at different force levels and/or with different exertion times. The Cumulative Strain Index (CUSI) further integrates biomechanical stressors from different tasks to quantify exposure for the entire work shift. The paper provides methodologies to compute COSI and CUSI along with examples. Complex task simulation produced 169,214 distinct tasks. Use of average, time-weighted average (TWA) and peak force and COSI classified 66.9, 28.2, 100 and 38.9% of tasks as hazardous, respectively. For job rotation the simulation produced 10,920 distinct jobs. TWA COSI, peak task COSI and CUSI classified 36.5, 78.1 and 66.6% jobs as hazardous, respectively. The results suggest that the TWA approach systematically underestimates the biomechanical stressors and peak approach overestimates biomechanical stressors, both at the task and job level. It is believed that the COSI and CUSI partially address these underestimations and overestimations of biomechanical stressors. Practitioner Summary: COSI quantifies exposure when applied hand force and/or duration of that force changes during a task cycle. CUSI integrates physical exposures from job rotation. These should be valuable tools for designing and analysing tasks and job rotation to determine risk of musculoskeletal injuries.

3D peak and cumulative low back and shoulder loads and postures during greenhouse pepper harvesting using a video-based approach

BACKGROUND

In agricultural field work many tasks have been cited as high priority risk factors for the development of work-related musculoskeletal disorders (WRMDs). Although video-based biomechanical approaches have been effective in documenting the physical demands and risks associated with various occupational and non-occupational tasks, to date, this method has yet to be used to document jobs such as crop harvesting in a greenhouse environment.

OBJECTIVE

To document and assess the postural characteristics and 3D peak and cumulative low back and shoulder loads associated with greenhouse pepper harvesting using a video-based posture sampling approach.

METHODS

Nine male (28.2 (4.1) years) pepper harvesters from a greenhouse in Southwestern Ontario, Canada were videotaped during a normal shift. 3DMatch was used to document working trunk and shoulder postures, from which 3D peak and cumulative forces and moments were quantified.

RESULTS

On average, workers spent the majority of their time in neutral trunk postures (lateral bend: 99.1%; axial twist: 59.9%; flexion: 89.8%). Consistent results were found for the left and right shoulder, with the arms held in a neutral flexion posture 50% of the time or more. Four participants experienced peak L4/L5 compression forces (between 4116.3 N and 5937.0 N) which exceeded the NIOSH Action Limit (3400 N) during the cart pushing/pulling task, but remained below the threshold during picking. Mean cumulative L4/L5 extension and shoulder flexion moments ranged in magnitude from 18.5 Nm to 28.2 Nm, and between 19.4 Nm and 23.2 Nm, respectively, across all tasks.

CONCLUSIONS

The postural characteristics and biomechanical loads associated with greenhouse pepper harvesting were quantified with a video-based biomechanical approach. Further investigations of the physical risk factors for low back and shoulder musculoskeletal disorders is warranted in pepper harvesting, given the postures and loads documented in this study.

Cumulative loads increase at the knee joint with slow-speed running compared to faster running: a biomechanical study

STUDY DESIGN

Biomechanical cross-sectional study.

OBJECTIVE

To investigate the hypothesis that the cumulative load at the knee during running increases as running speed decreases.

BACKGROUND

The knee joint load per stride decreases as running speed decreases. However, by decreasing running speed, the number of strides per given distance is increased. Running a given distance at a slower speed may increase the cumulative load at the knee joint compared with running the same distance at a higher speed, hence increasing the risk of running-related injuries in the knee.

METHODS

Kinematic and ground reaction force data were collected from 16 recreational runners, during steady-state running with a rearfoot strike pattern at 3 different speeds (mean ± SD): 8.02 ± 0.17 km/h, 11.79 ± 0.21 km/h, and 15.78 ± 0.22 km/h. The cumulative load (cumulative impulse) over a 1000-m distance was calculated at the knee joint on the basis of a standard 3-D inverse-dynamics approach.

RESULTS

Based on a 1000-m running distance, the cumulative load at the knee was significantly higher at a slow running speed than at a high running speed (relative difference, 80%). The mean load per stride at the knee increased significantly across all biomechanical parameters, except impulse, following an increase in running speed.

CONCLUSION

Slow-speed running decreases knee joint loads per stride and increases the cumulative load at the knee joint for a given running distance compared to faster running. The primary reason for the increase in cumulative load at slower speeds is an increase in number of strides needed to cover the same distance.

Development of Human Posture Simulation Method for Assessing Posture Angles and Spinal Loads

Video-based posture analysis employing a biomechanical model is gaining a growing popularity for ergonomic assessments. A human posture simulation method of estimating multiple body postural angles and spinal loads from a video record was developed to expedite ergonomic assessments. The method was evaluated by a repeated measures study design with three trunk flexion levels, two lift asymmetry levels, three viewing angles and three trial repetitions as experimental factors. The study comprised two phases evaluating the accuracy of simulating self and other people's lifting posture via a proxy of a computer-generated humanoid. The mean values of the accuracy of simulating self and humanoid postures were 12° and 15°, respectively. The repeatability of the method for the same lifting condition was excellent (~2°). The least simulation error was associated with side viewing angle. The estimated back compressive force and moment, calculated by a three dimensional biomechanical model, exhibited a range of 5% underestimation. The posture simulation method enables researchers to simultaneously quantify body posture angles and spinal loading variables with accuracy and precision comparable to on-screen posture matching methods.

Cumulative spine loading and clinically meaningful declines in low-back function

OBJECTIVE

The objective was to assess the role of cumulative spine loading measures in the development of a clinically meaningful decline in low-back function.

BACKGROUND

Cumulative spine loading has been a suspected risk factor for low-back pain for many years, yet the measures that characterize risk have not been well delineated.

METHODS

A total of 56 cumulative exposure measures were collected in a prospective field study of distribution center workers. An individual's risk for a clinically meaningful decline in low-back function (true cases) was explored with daily, weekly, and job tenure cumulative exposure measures using univariate and multivariate statistical modeling techniques. True noncases were individuals with no decline in low-back function.

RESULTS

An individual's risk for a clinically meaningful decline in low-back function (true cases) was predicted well versus true noncases (sensitivity/specificity = 72%/73%) using initial low-back function (p(n)), cumulative rest time, cumulative load exposure, job satisfaction, and worker age.

CONCLUSIONS

Cumulative rest time was identified as an important component for predicting an individual's risk for a clinically meaningful decline in low-back function.

APPLICATION

This information can be used to assess cumulative spine loading risk and may help establish guidelines to minimize the risk of a clinically meaningful decline in low-back function.

Estimating 3-D L5/S1 moments during manual lifting using a video coding system: validity and interrater reliability

OBJECTIVE

The aim of the study was to investigate the validity and interrater reliability of using a proposed video coding system to estimate the dynamical 3-D L5/ S1 joint moment on the basis of four key frames from video clips of asymmetric lifting tasks.

BACKGROUND

L5/S1 joint loading has been widely adopted to quantify low-back loading during lifting tasks. However, the measurement of L5/S1 joint loading usually requires a laboratory environment, which cannot be applied during field surveys.

METHOD

The validity of this system was investigated by comparing the estimated L5/S1 joint moments of various simulated lifting tasks with motion tracking system-based reference L5/S1 joint moments.

RESULTS

The comparison showed that the video coding system yielded good estimates on peak moment (r = .91, average absolute error [AAE] = 20.3 Nm) and cumulative moment (r = .88,AAE = 22.5 Nm.sec) of the sagittal plane. The interrater reliability of this system was assessed among 10 raters who used this system. The intraclass correlation ranged between .51 and .89 for the moments of different planes.

CONCLUSION

The results of the validity and interrater reliability analyses showed that the proposed video coding system could provide a good estimate of total L5/S1 joint loading on the basis of side-view video clips of the simulated lifting tasks.

APPLICATION

Although it was not as accurate as a motion tracking system for L5/S1 joint loading calculations, this approach can be an alternative for back load estimation for some lifting configurations when the use of motion tracking systems is not possible.

The contribution of load magnitude and number of load cycles to cumulative low-back load estimations: a study based on in-vitro compression data

BACKGROUND

Cumulative low-back load is suggested to be associated with low back pain, possibly due to (micro-)fractures of spinal segments. Based on available in vitro data it can be assumed that, in order to predict spine segment failure from cumulative compressive loading, load magnitude should be weighted with an exponent higher than one, whereas the number of cycles should be weighted with an exponent lower than 1. The aim of the present study was to assess both exponents based on available in-vitro data.

METHODS

Data on loading to fatigue fracture of spinal segments under cyclic compression in-vitro were used and converted to survival probability for 5 load levels and 5 levels of number of cycles. Three optimization procedures were used to estimate the exponent of load magnitude and load cycles separately, and load magnitude and load cycles combined. Goodness of fit was assessed by comparing the Akaike's Information Criterion (AIC) between models.

FINDINGS

The best fit, based on AIC and average error per data point was obtained with weighting of load magnitude and number of load cycles with exponents of approximately 2.0 and 0.2, respectively.

INTERPRETATION

The results show that a combination of load magnitude and number of load cycles weighted with exponents of approximately 2 and 0.2 respectively provides a suitable measure of cumulative spinal compression loading. This finding may be of relevance for assessing cumulative low-back loads in studies on the etiology of low-back pain.

Evaluation of the influence of mobile data terminal location on physical exposures during simulated police patrol activities

Prolonged occupational police driving combined with use of an in-vehicle computer elicits awkward, sustained postures in a scenario that lacks the adjustability to accommodate many mobile officer anthropometries and job-specific components. Twenty participants performed simulated police patrol sessions at five mobile data terminal (MDT) locations and using two seats: standard police vehicle seat and modified seat designed for police use. An MDT location self-selected prior to the session reduced perceived discomfort by up to 50% in the low back (p < .0001) and 68% in the right shoulder (p < .0001) compared to other tested locations, including the most common currently used location recorded from a representative police force. Muscle activity was lowest at the self-selected and current MDT locations for all muscles, significantly so for posterior deltoid (p < .0001) and supraspinatus (p < .0001). The modified seat reduced low back discomfort from the standard seat by 28% (p < .0001). Combining a self-selected MDT location and modified driver seat generated lower discomfort and physical loading than the currently used configuration.

Two linear regression models predicting cumulative dynamic L5/S1 joint moment during a range of lifting tasks based on static postures

Previous studies have indicated that cumulative L5/S1 joint load is a potential risk factor for low back pain. The assessment of cumulative L5/S1 joint load during a field study is challenging due to the difficulty of continuously monitoring the dynamic joint load. This study proposes two regression models predicting cumulative dynamic L5/S1 joint moment based on the static L5/S1 joint moment of a lifting task at lift-off and set-down and the lift duration. Twelve men performed lifting tasks at varying lifting ranges and asymmetric angles in a laboratory environment. The cumulative L5/S1 joint moment was calculated from continuous dynamic L5/S1 moments as the reference for comparison. The static L5/S1 joint moments at lift-off and set-down were measured for the two regression models. The prediction error of the cumulative L5/S1 joint moment was 21 ± 14 Nm × s (12% of the measured cumulative L5/S1 joint moment) and 14 ± 9 Nm × s (8%) for the first and the second models, respectively. Practitioner Summary: The proposed regression models may provide a practical approach for predicting the cumulative dynamic L5/S1 joint loading of a lifting task for field studies since it requires only the lifting duration and the static moments at the lift-off and/or set-down instants of the lift.

Estimation of 3-D peak L5/S1 joint moment during asymmetric lifting tasks with cubic spline interpolation of segment Euler angles

Previous research proposed a method using interpolation of the joint angles in key frames extracted from a field-survey video to estimate the dynamic L5/S1 joint loading for symmetric lifting tasks. The advantage of this method is that there is no need to use unwieldy equipment for capturing full body movement for the lifting tasks. The current research extends this method to asymmetric lifting tasks. The results indicate that 4-point cubic spline interpolation of segment Euler angles combined with a biomechanical model can provide a good estimation of 3-D peak L5/S1 joint moments for asymmetric lifting tasks. The average absolute error in the coronal, sagittal, and transverse planes with respect to the local pelvis axes was 16Nm, 22Nm, and 11Nm, respectively. It was also found that the dynamic component of the peak L5/S1 joint moment was not monotonously convergent when the number of interpolation points was increased. These results can be helpful for developing applied ergonomic field-survey tools such as video bases systems for estimating L5/S1 moments of manual materials handling tasks.

A comparison of low back kinetic estimates obtained through posture matching, rigid link modeling and an EMG-assisted model

This study examined errors introduced by a posture matching approach (3DMatch) relative to dynamic three-dimensional rigid link and EMG-assisted models. Eighty-eight lifting trials of various combinations of heights (floor, 0.67, 1.2 m), asymmetry (left, right and center) and mass (7.6 and 9.7 kg) were videotaped while spine postures, ground reaction forces, segment orientations and muscle activations were documented and used to estimate joint moments and forces (L5/S1). Posture matching over predicted peak and cumulative extension moment (p < 0.0001 for all variables). There was no difference between peak compression estimates obtained with posture matching or EMG-assisted approaches (p = 0.7987). Posture matching over predicted cumulative (p < 0.0001) compressive loading due to a bias in standing, however, individualized bias correction eliminated the differences. Therefore, posture matching provides a method to analyze industrial lifting exposures that will predict kinetic values similar to those of more sophisticated models, provided necessary corrections are applied.

Continuous assessment of low back loads in long-term care nurses

Considerable effort has been spent evaluating aspects of low back injury risk in nursing yet comprehensive evaluation of all work tasks has been limited. The purpose of this study was to evaluate peak and cumulative lumbar spine loads experienced by personal support workers. A total of 20 female long-term care workers were observed and had trunk posture monitored via an inclinometer throughout their shift. When adjusted for an 8-h workday, workers experienced cumulative loads of 21.3 +/- 4.6 MNs, 1.8 +/- 0.6 MNs and 2.9 +/- 1.4 MNs for compression, lateral and anterior shear, respectively. Patient care, unloaded standing, walking and miscellaneous tasks accounted for almost 80% of cumulative compression, while lifts and transfers accounted for less than 10%. Mechanical lift assists reduced peak loads and contributed minimally to cumulative loading. These findings suggest that both peak and cumulative spine loads should be considered when evaluating injury risk in the nursing profession. STATEMENT OF RELEVANCE: This study has shown that tasks other than patient transfers and lifts are important in the assessment of low back injury risk in nurses. The method developed is a relatively straightforward approach that can be used to estimate peak and cumulative spine load to provide insight to risk of injury in many occupational settings.

Continuous assessment of work activities and posture in long-term care nurses

The high prevalence of low back injuries in nursing has prompted the use of mechanical lift assists while overall assessment of activities and postures remains limited. The purpose of this study was to chronicle trunk posture and work tasks of long-term healthcare professionals. An inclinometer monitored trunk posture for 27 workers, 20 of whom were also observed continuously throughout their shift. Patient lifts and transfers accounted for less than 4% of the shift while patient care, unloaded standing and walking and miscellaneous tasks accounted for 85%. Manual lifts and transfers occurred twice as often as mechanically assisted lifts but took only half the time. The workers had a median trunk flexion angle of 9.2 degrees , spent 25% of their time flexed beyond 30 degrees and had peak flexion angles greater than 75 degrees in many tasks. Analysis of posture throughout the entire working shift indicates that, in addition to lifts and transfers, emphasis needs to be placed on patient care and miscellaneous activities when assessing injury risk for nurses. STATEMENT OF RELEVANCE: Patient handling has been the focus in the effort to reduce back pain and injury in nursing. In addition to the use of mechanical lifts, there is a need to examine other aspects of nursing, including patient care and other ancillary tasks, which comprise the majority of the work shift and, while often unloaded, exhibit extreme postures that may also lead to injury.

The Spineangel: Examining the validity and reliability of a novel clinical device for monitoring trunk motion

Spinal loading in excessive and repeated trunk flexion may hinder recovery from acute low back pain. The Spineangel device provides real-time patient biofeedback on trunk flexion and may facilitate recovery from lower back injury. This cross-sectional study evaluates validity and reliability of this device in the laboratory setting. Participants included 18 healthy males. Angular displacements were simultaneously obtained from a Spineangel device placed on the hip and criterion measures of hip, lumbar and total sagittal rotation, and pelvic tilt obtained via 3D Motion Analysis. Each participant repeated four movements five times in a random order (forward bending fingertips-to-knees and to mid-lower leg, full flexion, and full extension). Intraclass correlation coefficients (ICC) for Spineangel measurement of trunk motion were excellent (ICC>0.9). The coefficient of repeatability was less than 5.2 degrees in both flexion and extension. Spineangel showed the highest correlation with Motion Analysis((R)) measurement of pelvic tilt with no statistical difference between measures when bending forward to fingertips-to-knees. Given its high reliability, the Spineangel device has potential as a trunk flexion biofeedback device. Further investigation is required to see if these laboratory results can be reproduced in the clinical setting and to determine the clinical benefits of such a device.

Determining the optimal size for posture categories used in video-based posture assessment methods

Currently, there are no standards for the development of posture classification systems used in observation-based ergonomic posture assessment methods. This study was conducted to determine if an optimal posture category size for different body segments and posture views could be established by examining the trade-off between magnitude of error and the number of posture category misclassification errors made. Three groups (trunk flexion/extension and lateral bend; shoulder flexion/extension and adduction/abduction; elbow flexion/extension) of 30 participants each selected postures they perceived to correctly represent the video image shown on a computer screen. For each view, 10 images were presented for five different posture category sizes, three times each. The optimal posture category sizes established were 30 degrees for trunk, shoulder and elbow flexion/extension, 30 degrees for shoulder adduction/abduction and 15 degrees for trunk lateral bend, suggesting that posture category size should be based on the body segment and view of the image being assessed. Across all conditions, the posture category sizes were comparable to those used in published ergonomic tools.

Inter-rater reliability of output measures for a posture matching assessment approach: a pilot study with food service workers

Despite the ongoing health problem of repetitive strain injuries, there are few tools currently available for ergonomic applications evaluating cumulative loading that have well-documented evidence of reliability and validity. The purpose of this study was to determine the inter-rater reliability of a posture matching based analysis tool (3DMatch, University of Waterloo) for predicting cumulative and peak spinal loads. A total of 30 food service workers were each videotaped for a 1-h period while performing typical work activities and a single work task was randomly selected from each for analysis by two raters. Inter-rater reliability was determined using intraclass correlation coefficients (ICC) model 2,1 and standard errors of measurement for cumulative and peak spinal and shoulder loading variables across all subjects. Overall, 85.5% of variables had moderate to excellent inter-rater reliability, with ICCs ranging from 0.30-0.99 for all cumulative and peak loading variables. 3DMatch was found to be a reliable ergonomic tool when more than one rater is involved.

A validation of a posture matching approach for the determination of 3D cumulative back loads

The purpose of this project was to investigate the amount of error in calculating cumulative lumbar spine kinetics using a posture matching approach (3DMatch) compared to a 3D coordinate electromagnetic tracking approach (FASTRAK). Six subjects were required to perform five repeats each of two symmetrical and two asymmetrical lifts while being simultaneously recorded from 4 camera views at viewing angles of 0 degrees , 45 degrees , 60 degrees and 90 degrees to the sagittal plane while wearing eight FASTRAK sensors to define an 8 segment rigid link model (RLM) of the head, arms, and trunk. Four hundred and eighty lifts (6 subjects x20 lifts x4 camera views) were analyzed using the 3DMatch posture-matching program to calculate the following cumulative loads at the L4/L5 joint: compression, anterior shear, posterior shear, reaction shear and extension moment. The errors in cumulative load calculation were determined as the difference between the values calculated for the same lifts using a 3D RLM that used electromagnetic motion tracking sensors (FASTRAK) positioned at the segment center of masses as model inputs. No significant difference (p<0.05) in the relative error for any of the cumulative loading variables between the four camera views and the 3D RLM approach was found. Furthermore the relative errors for cumulative compression, joint anterior shear, reaction anterior shear and extension moment were all below 12%. These results suggest that posture matching by trained users can provide reasonable 3D data to calculate cumulative low back loads with a biomechanical model.

The effect of camera viewing angle on posture assessment repeatability and cumulative spinal loading

Video-based task analysis in the workplace is often limited by equipment location and production line arrangement, therefore making it difficult to capture the motion in a single plane. The purpose of this study was to investigate the effects of camera placement on an observer's ability to accurately assess working postures in three dimensions and the resultant influence on the reliability and repeatability of calculated cumulative loading variables. Four video cameras were placed at viewing angles of 0 degrees, 45 degrees, 60 degrees and 90 degrees to the frontal plane, enabling the simultaneous collection of views of four lifting tasks (two symmetric and two asymmetric). A total of 11 participants were trained in the use of the 3DMatch 3-D posture matching software package (developed at the University of Waterloo) and were required to analyse 16 lifting trials. Four of the participants were randomly selected to return within 72 h and repeat the analysis protocol to test intra-observer repeatability. Posture matching agreement between camera views was higher when the body segments had a minimal range of motion during the task. There was no significant participant main effect; however, there was a significant (p < 0.05) task main effect. Intraclass correlation coefficients (ICC) were calculated to assess the between day reliability. Compression, reaction anterior shear and extension moment were all found to have excellent reliability (ICC > 0.75). Joint anterior shear and joint posterior shear both provided fair to good reliability (0.4 > ICC < 0.75). Overall, the impact of the camera viewing angle on an observer's ability to match working postural exposure was found to be small.

Spine loading in patients with low back pain during asymmetric lifting exertions

BACKGROUND CONTEXT

Recurrent low back pain (LBP) is a common and costly problem that might be related to increased spine loads in those with LBP. However, we know little about how the spine is loaded when those with LBP perform lifting exertions.

PURPOSE

Document spine loading patterns of patients with LBP performing symmetric and asymmetric lifting exertions compared with asymptomatic individuals performing the same tasks.

STUDY DESIGN

Spine loadings during lifting exertions that varied in asymmetric origin as well as horizontal and vertical distance from the spine were compared between asymptomatic subjects and patients with LBP.

METHODS

Sixty-two patients with LBP and 61 asymptomatic individuals performed a variety of lifting exertions that varied in lift origin horizontal and vertical position (region), lift asymmetry position and weight lifted. An electromyography-assisted model was used to evaluate spine loading in each subject during the lifting exertions. Differences in spine loading between the LBP and asymptomatic subjects were noted as a function of the experimental variables.

RESULTS

Patients with LBP experienced greater spine compression and shear forces when performing lifting tasks compared with asymptomatic individuals. The least taxing conditions resulted in some of the greatest differences between LBP and asymptomatic individuals.

CONCLUSIONS

Greater levels of antagonistic muscle coactivation resulted in increases in spine loading for patients with LBP. Specific lifting conditions that tend to exacerbate loading can be identified by means of physical workplace requirements. These findings may impact acceptable return-to-work conditions for those with LBP.

Determining the minimum sampling rate needed to accurately quantify cumulative spine loading from digitized video

Cumulative low back loads have been linked to the reporting of low back pain. Traditional video-based methods used to estimate these loads are time intensive for data collection and analysis. Sampling less frequently would help to reduce the associated time and cost of this type of approach. The purpose of this study was to determine how the error in estimated cumulative low back loads is affected by reducing video sampling rate. Ten healthy male university students performed three laboratory, sagittal plane lifts of varying mass (2.3, 8.8, and 15.9 kg), speed (0.2, 0.4, 0.8 m/s), and postural demand (lift from floor to table; lower from shelf to table; lift from floor over barrier and lower to floor) while being videotaped (60 frames/s). Digitized body coordinates and anthropometrics were input into a static biomechanical model, resulting in estimates of low back compression and shear forces, and moment. Load-time histories for each condition underwent rectangular integration at 60 (gold standard), 30, 20, 15, 12, 10, 6, 5, 4, 3, 2 and 1 frames/s, resulting in estimates of low back cumulative loads. Mean relative errors with respect to 60 frames/s for all cumulative loads and all conditions were found to be below 8% at 1 frame/s, and less than 3% at 2 frames/s. In addition, analyses at sampling rates above 3 frames/s were not significantly different than the cumulative loads determined at 60 frames/s, for all conditions. The accuracy of cumulative loads exhibited even at low sampling rates can be attributed, in part, to the fact that overestimations and underestimations of the integrated loads tend to cancel out over the length of the tasks considered.