Low-back disorders (LBDs) are the most common and costly musculoskeletal problem. Muscle co-activation, a mechanism that stabilises the spine, is adopted by the central nervous system to provide added protection and avoid LBDs. However, during high-risk lifting tasks, the compressive load on the spine grows owing to increased co-activation. The aim of this study was to develop a method for the sample-by-sample monitoring of the co-activation of more than two muscles, and to compare this method with agonist-antagonist methods. We propose a time-varying multi-muscle co-activation function that considers electromyographic (EMG) signals as input. EMG data of 10 healthy subjects were recorded while they manually lifted loads at three progressively heavier conditions. The repeated measures ANOVA revealed a significant effect of lifting condition on our co-activation index. Heavier conditions resulted in higher muscle co-activation values. Significant correlations were found between the time-varying multi-muscle co-activation index and other agonist-antagonist methods. Practitioner Summary: We have developed a method to quantify muscle co-activation during the execution of a lifting task. To do this we used surface electromyography. Our algorithm provides a measure of time-varying co-activation between more than two muscles.

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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.

An experiment was carried out on supermarket cashiers to evaluate the time, kinematic and electromyographic changes, in both sitting and standing positions, following the redesign of a checkout counter. The novelty of the prototype checkout counter is a disk wheel placed in the bagging area, which is designed to avoid the cashier having to manually push products along the bagging area. The kinematic evaluation was based on the upper limb and trunk range of motions (RoM). The electromyographic parameters assessed were mean and maximum muscular activations. Three factors were taken into account: design (before and after redesign), posture (standing or sitting) and bagging area (anterior or posterior). The results show that the RoM values are lowest after the intervention and in the standing position. Mean and maximum muscular activation patterns are similar. Differences related to the bagging area in which the goods were released also emerged. The disk wheel represents a valid aid for reducing biomechanical overload in cashiers; the standing position is biomechanically more advantageous. Practitioner Summary: EMG and optoelectronic motion analysis systems are useful for the quantitative assessment of the effects of the redesign of the workplace biomechanical risk. Our results suggest that a disk wheel positioned in the bagging area reduces the biomechanical risk for cashiers and increases time spent resting.

The coordinative pattern is an important feature of locomotion that has been studied in a number of pathologies. It has been observed that adaptive changes in coordination patterns are due to both external and internal constraints. Obesity is characterized by the presence of excess mass at pelvis and lower-limb areas, causing mechanical constraints that central nervous system could manage modifying the physiological interjoint coupling relationships. Since an altered coordination pattern may induce joint diseases and falls risk, the aim of this study was to analyze whether and how coordination during walking is affected by obesity. We evaluated interjoint coordination during walking in 25 obese subjects as well as in a control group. The time-distance parameters and joint kinematics were also measured. When compared with the control group, obese people displayed a substantial similarity in joint kinematic parameters and some differences in the time-distance and in the coupling parameters. Obese subjects revealed higher values in stride-to-stride intrasubjects variability in interjoint coupling parameters, whereas the coordinative mean pattern was unaltered. The increased variability in the coupling parameters is associated with an increased risk of falls and thus should be taken into account when designing treatments aimed at restoring a normal locomotion pattern.