Influence of measurement accuracy on the application of the 1991 NIOSH equation

Adaptive Lifting Index (aLI) for Real-Time Instrumental Biomechanical Risk Assessment: Concepts, Mathematics, and First Experimental Results

When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment.

Revised NIOSH lifting equation: a critical evaluation

The revised NIOSH lifting equation (RNLE) aims to manage lifting-related lower back pain (LBP), by determining safe load limits. Many researchers have studied the multiplier development criteria, the universal applicability of the equation and its ability to identify an increased risk of LBP in lifting tasks. Although a number of strengths of the equation have been highlighted, many limitations have also been identified. The need for new multipliers, such as worker and environmental characteristics, was highlighted in order to make the equation more adaptable. The RNLE was designed to protect 75% of female workers and is therefore inherently conservative. Additionally, as all multipliers have values less than or equal to 1, the recommended weight limits (RWLs) can be further reduced. Thus, new multipliers may be defined, by combining two or more existing multipliers, to make the RWLs more realistic.

Development and evaluation of RAMP II - a practitioner's tool for assessing musculoskeletal disorder risk factors in industrial manual handling

RAMP II is an observation-based tool developed for assessing a wide range of musculoskeletal disorder risk factors related to industrial manual handling. RAMP II, which is part of the RAMP tool, is based on research studies and expert judgments. The assessment relies mainly on direct or video observations of the work being assessed, but additionally on measured push/pull forces and weights of handled objects, and on perceived workload and discomfort. Over 80 practitioners participated in the development of the tool. According to the evaluations, 73% of the assessment items evaluated had acceptable reliability, and the majority of the potential end-users reported that RAMP II is usable for assessing risks and as a decision base. It is concluded that this study provides support that RAMP II is usable for risk assessment of musculoskeletal disorder risk factors in industrial manual handling. Practitioner summary: RAMP II is an observation-based assessment tool for screening and assessing major musculoskeletal exposures in industrial manual handling jobs. Over 80 practitioners participated in the development of the tool. This study provides support that RAMP II is usable for risk assessment of musculoskeletal disorder risk factors in industrial manual handling. Abbreviations: CTS: carpal tunnel syndrome; HARM: the Hand Arm Risk Assessment method; IMP: intramuscular pressure; κ_w: linearly weighted kappa; LBD: lower back disorders; LBP: lower back pain; MAWL: maximum acceptable weight of lift; MHO: manual handling operations; MSD: musculoskeletal disorder; MNSD: neck-shoulder disorder; NSP: neck-shoulder pain; OCRA: the Occupational Repetitive Action methods; OHS: occupational health and safety; PABAK: prevalence and bias adjusted kappa; p₀: proportion of agreement; RAMP: Risk Assessment and Management tool for manual handling Proactively; ROM: range of motion; RPL: risk and priority level; RSI: the Revised Strain Index; RULA: the Rapid Upper Limb Assessment; SWEA: Swedish Work Environment Authority; UEMSDs: upper-extremity work-related musculoskeletal disorders; WMSD: work-related musculoskeletal disorder; WRMSD: work-related musculoskeletal disorder; workday_8h: eight hours workday.

Lifting Activity Assessment Using Kinematic Features and Neural Networks

Work-related low-back disorders (WLBDs) can be caused by manual lifting tasks. Wearable devices used to monitor these tasks can be one possible way to assess the main risk factors for WLBDs. This study aims at analyzing the sensitivity of kinematic data to the risk level changes, and to define an instrument-based tool for risk classification by using kinematic data and artificial neural networks (ANNs). Twenty workers performed lifting tasks, designed by following the rules of the revised NIOSH lifting equation, with an increasing lifting index (LI). From the acquired kinematic data, we computed smoothness parameters together with kinetic, potential and mechanical energy. We used ANNs for mapping different set of features on LI levels to obtain an automatic risk estimation during these tasks. The results show that most of the calculated kinematic indexes are significantly affected by changes in LI and that all the lifting condition pairs can be correctly distinguished. Furthermore, using specific set of features, different topologies of ANNs can lead to a reliable classification of the biomechanical risk related to lifting tasks. In particular, the training sets and numbers of neurons in each hidden layer influence the ANNs performance, which is instead independent from the numbers of hidden layers. Reliable biomechanical risk estimation can be obtained by using training sets combining body and load kinematic features.

Wearable Monitoring Devices for Biomechanical Risk Assessment at Work: Current Status and Future Challenges-A Systematic Review

Background: In order to reduce the risk of work-related musculoskeletal disorders (WMSDs) several methods have been developed, accepted by the international literature and used in the workplace. The purpose of this systematic review was to describe recent implementations of wearable sensors for quantitative instrumental-based biomechanical risk assessments in prevention of WMSDs. Methods: Articles written until 7 May 2018 were selected from PubMed, Scopus, Google Scholar and Web of Science using specific keywords. Results: Instrumental approaches based on inertial measurement units and sEMG sensors have been used for direct evaluations to classify lifting tasks into low and high risk categories. Wearable sensors have also been used for direct instrumental evaluations in handling of low loads at high frequency activities by using the local myoelectric manifestation of muscle fatigue estimation. In the field of the rating of standard methods, on-body wireless sensors network-based approaches for real-time ergonomic assessment in industrial manufacturing have been proposed. Conclusions: Few studies foresee the use of wearable technologies for biomechanical risk assessment although the requirement to obtain increasingly quantitative evaluations, the recent miniaturization process and the need to follow a constantly evolving manual handling scenario is prompting their use.

Mechanical lifting energy consumption in work activities designed by means of the "revised NIOSH lifting equation"

The aims of the present work were: to calculate lifting energy consumption (LEC) in work activities designed to have a growing lifting index (LI) by means of revised NIOSH lifting equation; to evaluate the relationship between LEC and forces at the L₅-S₁ joint. The kinematic and kinetic data of 20 workers were recorded during the execution of lifting tasks in three conditions. We computed kinetic, potential and mechanical energy and the corresponding LEC by considering three different centers of mass of: 1) the load (CoM_L); 2) the multi-segment upper body model and load together (CoM_Upp+L); 3) the whole body and load together (CoM_Tot). We also estimated compression and shear forces. Results shows that LEC calculated for CoM_Upp+L and CoM_Tot grew significantly with the LI and that all the lifting condition pairs are discriminated. The correlation analysis highlighted a relationship between LEC and forces that determine injuries at the L₅-S₁ joint.

Evaluation of the Impact of the Revised National Institute for Occupational Safety and Health Lifting Equation

OBJECTIVE

The objective of this article is to evaluate the impact of the Revised National Institute for Occupational Safety and Health Lifting Equation (RNLE).

BACKGROUND

The RNLE has been used extensively as a risk assessment method for prevention of low back pain (LBP). However, the impact of the RNLE has not been documented.

METHODS

A systematic review of the literature on the RNLE was conducted. The review consisted of three parts: characterization of the RNLE publications, assessment of the impact of the RNLE, and evaluation of the influences of the RNLE on ergonomic standards. The literature for assessing the impact was categorized into four research areas: methodology, laboratory, field, and risk assessment studies using the Lifting Index (LI) or Composite LI (CLI), both of which are the products of the RNLE.

RESULTS

The impact of the RNLE has been both widespread and influential. We found 24 studies that examined the criteria used to define lifting capacity used by the RNLE, 28 studies that compared risk assessment methods for identifying LBP, 23 studies that found the RNLE useful in identifying the risk of LBP with different work populations, and 13 studies on the relationship between LI/CLI and LBP outcomes. We also found evidence on the adoption of the RNLE as an ergonomic standard for use by various local, state, and international entities.

CONCLUSION

The review found 13 studies that link LI/CLI to adverse LBP outcomes. These studies showed a positive relationship between LI/CLI metrics and the severity of LBP outcomes.

Evaluation of ergonomic physical risk factors in a truck manufacturing plant: case study in SCANIA Production Angers

The aims of this study were 1) to assess the ergonomic physical risk factors from practitioner's viewpoint in a truck assembly plant with an in-house observational method and the NIOSH lifting equation, and 2) to compare the results of both methods and their differences. The in-house ergonomic observational method for truck assembly i.e. the SCANIA Ergonomics Standard (SES) and the NIOSH lifting equation were applied to evaluate physical risk factors and lifting of loads by operators. Both risk assessment approaches revealed various levels of risk, ranging from low to high. Two workstations were identified by the SES method as high risk. The NIOSH lifting index (LI) was greater than two for four lifting tasks. The results of the SES method disagreed with the NIOSH lifting equation for lifting tasks. Moreover, meaningful variations in ergonomic risk patterns were found for various truck models at each workstation. These results provide a better understanding of the physical ergonomic exposure from practitioner's point of view in the automotive assembly plant.

An evaluation of methods assessing the physical demands of manual lifting in scaffolding

Four methods assessing the physical demands of manual lifting were compared. The scaffolding job was evaluated and three distinct scaffolding tasks were ranked using: (1) the revised NIOSH lifting equation (NIOSH method), (2) lifting guidelines for the Dutch construction industry (Arbouw method), (3) rapid appraisal of the NIOSH lifting equation (practitioners' method), and (4) systematic observations. For the three first-mentioned methods the same dataset was used; observation took place in a different setting in the same company. At job level, all methods indicated that ergonomic interventions are required to protect scaffolders from an increased risk for low back pain. The NIOSH, Arbouw and practitioners' method resulted in a similar ranking order of tasks (transport>construction>dismantlement). In contrast, the observational method gave transport the lowest ranking. The underlying cause was probably that the observational method is more sensitive to durations of tasks and lifting within tasks than the three other methods.

Self-assessed and directly measured occupational physical activities--influence of musculoskeletal complaints, age and gender

This study compares questionnaire assessed physical activity with direct technical measurements among cleaners and office workers, stratified regarding age, gender and self-reported neck/shoulder complaints. During two full working days number of steps was recorded by a pedometer, sitting/standing positions by a posimeter and heart rate by a Sport-Tester. In addition the subjects kept a work task diary for 10 days. There were high intra-individual variations in exposure between the days. Subjects with complaints rated their exposure higher than those without, although they in fact showed lower direct measured exposure. This may imply underestimation of exposure-effect relationships. Rate of perceived exertion showed low correlation with heart rate ratio within the two occupational groups, but high, 0.64 when the two groups were combined. Age and complaints explained 31% of the variance for the cleaners.

Usability of the revised NIOSH lifting equation

Following the revision of the 1981 National Institute for Occupational Safety and Health (NIOSH) lifting equation, research needs related to the new equation were outlined. Aside from epidemiological studies, the need to evaluate the usability of the 1991 NIOSH equation in realistic work environments was expressed. This paper reports on extensive experiences with training users and application of the equation in varied work settings. Qualitative results from training sessions indicated that frequency, asymmetry and duration were the parameters that required relatively longer instruction periods and resulted in the most questions. Field applications indicated that the variable nature of lifting/lowering demands found in many jobs resulted in difficulty applying the equation. Approximately 35% of 1103 lifting and lowering tasks had at least one parameter outside of acceptable ranges, while a majority of workers (62.8%) reported other manual handling tasks that are counter to assumptions made in the development of the equation. The practical implications of the findings are discussed.