Biomechanical risk in fatiguing frequency-dependent lifting activities: muscle coactivation in people with and without low back pain

Abstract

Musculoskeletal diseases and disorders from biomechanical overload are very common among workers. In Italy in2019, occupational diseases of the osteomuscular system and connective tissue accounted for 66% of the total number ofdiseases reported to INAIL. Many factors can contribute to the establishment of a condition of biomechanical overloadand therefore to the onset of work-related musculoskeletal disorders (WMSDs). Among these, work-related low-backdisorders (WLBDs), caused mainly by handling heavy loads, are very common.In recent years, several methods have been developed to assess the risk of biomechanical overload, included in severalinternational standards (ISO-11228, ISO-11226, ISO/TR 12295 and 12296) aimed at identifying high-risk work activities and assessing the effectiveness of ergonomic interventions. Among the best known, with regard to the manual liftingof heavy loads, there is the Revised NIOSH Lifting Equation that, while presenting many advantages (cost-effectiveness,non-invasiveness, speed of application ...) at the same time also has limitations concerning mainly the high subjectivity(subject of scientific debate) and the impossibility of these methods to assess all work tasks.From these premises, it is clear the usefulness of being able to use new quantitative risk assessment methodologies,objectifiable and repeatable, which provide for the possibility of assessing the risk from biomechanical overload evenin modern working scenarios where the use of exoskeletons by workers and the sharing of working space with cobots isbecoming increasingly widespread. In fact, the methods currently used are incomplete and ineffective in assessing thereal impact that these technologies have on the health and safety of workers in Industry 4.0.Recent studies (some of which we were involved in) have introduced the possibilities offered by optoelectronic systems, inertial sensors (IMUs) and surface electromyography (sEMG), to integrate the most widely used observationalmethodologies. These modern technologies, evaluating how a subject moves his joints and uses his muscles during theexecution of a work task, can integrate the observational methods, quantify the elements that characterize the risk minimizing the evaluation errors caused by individual subjectivity and allow to carry out the assessment of biomechanicalrisk even in those areas where the currently most widespread methodologies are not able to give exhaustive answers. Inparticular, the innovative methodologies based on IMUs and sEMG, allow the instrumental quantitative assessment ofbiomechanical risk directly in the field thanks to the fact that the sensors are miniaturized, wearable, easily transportableand based on “wireless” transmission of data acquired on the worker who performs the task. These aspects facilitatedata recording, allowing accurate signal acquisition even in unfavorable environments and in work situations where theworker interacts with a cobot or uses an exoskeleton. Previous studies have involved studies of non-fatiguing lifts, wherethe movement and relative risk of single repetitions of lifting were studied. Currently, we wonder what happens when thework activity becomes fatiguing and whether it is still possible to use these methods to classify risk. In addition, anotherunexplored question concerns the presence of workers who continue to perform work activity during the first phase ofonset of musculoskeletal disorders: can the risk to which these workers are exposed be considered the same as thatinvolving workers without pain? To answer these questions, we conducted an experimental campaign at the Universityof Birmingham in collaboration with Roma Tre University and INAIL in which subjects with and without back disordersperformed fatiguing lifts of 15 minutes in three risk levels determined by three different lifting frequencies. We studiedtrunk muscle activity in terms of muscle coactivation of the trunk flexor and extensor muscles. The results show howcoactivation can classify risk during manual load lifting activities by distinguishing not only the level of risk but alsothe presence or absence of back disorders. These results suggest that the use of electromyographic features to assess thebiomechanical risk associated with work activities can also be used in the presence of fatiguing lifting also to distinguishthe risk in case of subjects with back pain. This methodology could be used to monitor fatigue and extend the possibilitiesoffered by currently available instrumental-based approaches.