Musculoskeletal disorders (MSD) are a highly prevalent work-related health problem. Biomechanical exposure to hazardous postures during work is a risk factor for the development of MSD. This study focused on developing an inertial sensor-based approach to evaluate posture in industrial contexts, particularly in automotive assembly lines. The analysis was divided into two stages: 1) a comparative study of joint angles calculated during movements of the upper body segments using the proposed motion tracking framework and the ones provided by a state-of-the-art inertial motion capture system and 2) a work-related posture risk evaluation of operators working in an automative assembly line. For the comparative study, we selected data collected in laboratory (N = 8 participants) and assembly line settings (N = 9 participants), while for the work-related posture risk evaluation, we only considered data acquired within the automotive assembly line. The results revealed that the proposed framework could be applied to track industrial tasks movements performed on the sagittal plane, and the posture evaluation uncovered posture risk differences among different operators that are not considered in traditional posture risk assessment instruments.

Cumulative fatigue during repetitive work is associated with occupational risk and productivity reduction. Usually, subjective measures or muscle activity are used for a cumulative evaluation; however, Industry 4.0 wearables allow overcoming the challenges observed in those methods. Thus, the aim of this study is to analyze alterations in respiratory inductance plethysmography (RIP) to measure the asynchrony between thorax and abdomen walls during repetitive work and its relationship with local fatigue. A total of 22 healthy participants (age: 27.0 ± 8.3 yrs; height: 1.72 ± 0.09 m; mass: 63.4 ± 12.9 kg) were recruited to perform a task that includes grabbing, moving, and placing a box in an upper and lower shelf. This task was repeated for 10 min in three trials with a fatigue protocol between them. Significant main effects were found from Baseline trial to the Fatigue trials (p < 0.001) for both RIP correlation and phase synchrony. Similar results were found for the activation amplitude of agonist muscle (p < 0.001), and to the muscle acting mainly as a joint stabilizer (p < 0.001). The latter showed a significant effect in predicting both RIP correlation and phase synchronization. Both RIP correlation and phase synchronization can be used for an overall fatigue assessment during repetitive work.

Gestational diabetes mellitus (GDM) is a pregnancy complication affecting many women, requiring changes in behaviours, which command them to learn self-care practices shortly. Digital interventions have been developed to support women with GDM. However, they have often overlooked women’s needs and characteristics and failed to frame self-care theories into their design. To address this issue, we adopted a mixed methods approach to develop and refine a user-centred, evidence-based digital Toolkit for supporting self-care in GDM, providing behavioural and educational content, particularly about nutrition. To inform the development and refinement of the Toolkit, we conducted a literature review, observed sixty-six nutrition appointments, interviewed eleven dietitians and seventeen patients, and held co-creation sessions with two dietitians, all of which were analysed using a deductive Thematic Analysis. To validate the Toolkit, we conducted a survey with seventeen healthcare professionals, which was analysed using descriptive statistics. The final version of the NUTRIA Toolkit consists of four main modules with thirty-eight artefacts, including behavioural tools to assist women in GDM management. Despite some limitations, this study robustly endorsed the development and refinement of a user-centred, evidence-based Toolkit for supporting self-care in GDM, aiming for future feasibility and trial testing.

Gestational Diabetes (GD) is a common perinatal condition that can strongly impact the health of both the mother and the foetus. To avoid complications, people living with GD need to quickly learn to monitor their blood glucose levels and implement relevant changes to their diet and physical activity. Despite the importance of self-monitoring in GD, there is limited understanding of how people living with GD monitor their blood glucose in everyday life. This paper describes the self-monitoring practices of people living with GD in Portugal, drawing on 25 interviews with women who had GD, complemented by observations of glucose monitoring training sessions and interviews with five nurses. Our findings show that people living with GD learned complex practices within weeks of diagnosis, including measuring on the move, measuring while task-switching, and performing repeated measurements. We reflect on the impact of practices in everyday life and outline three implications for the design of self-monitoring technologies for GD.