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 in
2019, occupational diseases of the osteomuscular system and connective tissue accounted for 66% of the total number of
diseases reported to INAIL. Many factors can contribute to the establishment of a condition of biomechanical overload
and therefore to the onset of work-related musculoskeletal disorders (WMSDs). Among these, work-related low-back
disorders (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 several
international 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 lifting
of 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 even
in modern working scenarios where the use of exoskeletons by workers and the sharing of working space with cobots is
becoming increasingly widespread. In fact, the methods currently used are incomplete and ineffective in assessing the
real 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 observational
methodologies. These modern technologies, evaluating how a subject moves his joints and uses his muscles during the
execution 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 biomechanical
risk even in those areas where the currently most widespread methodologies are not able to give exhaustive answers. In
particular, the innovative methodologies based on IMUs and sEMG, allow the instrumental quantitative assessment of
biomechanical risk directly in the field thanks to the fact that the sensors are miniaturized, wearable, easily transportable
and based on “wireless” transmission of data acquired on the worker who performs the task. These aspects facilitate
data recording, allowing accurate signal acquisition even in unfavorable environments and in work situations where the
worker interacts with a cobot or uses an exoskeleton. Previous studies have involved studies of non-fatiguing lifts, where
the movement and relative risk of single repetitions of lifting were studied. Currently, we wonder what happens when the
work activity becomes fatiguing and whether it is still possible to use these methods to classify risk. In addition, another
unexplored question concerns the presence of workers who continue to perform work activity during the first phase of
onset of musculoskeletal disorders: can the risk to which these workers are exposed be considered the same as that
involving workers without pain? To answer these questions, we conducted an experimental campaign at the University
of Birmingham in collaboration with Roma Tre University and INAIL in which subjects with and without back disorders
performed fatiguing lifts of 15 minutes in three risk levels determined by three different lifting frequencies. We studied
trunk muscle activity in terms of muscle coactivation of the trunk flexor and extensor muscles. The results show how
coactivation can classify risk during manual load lifting activities by distinguishing not only the level of risk but also
the presence or absence of back disorders. These results suggest that the use of electromyographic features to assess the
biomechanical risk associated with work activities can also be used in the presence of fatiguing lifting also to distinguish
the risk in case of subjects with back pain. This methodology could be used to monitor fatigue and extend the possibilities
offered by currently available instrumental-based approaches.