A Subject-Specific Approach to Detect Fatigue-Related Changes in Spine Motion Using Wearable Sensors.

An objective method to detect muscle fatigue-related kinematic changes may reduce workplace injuries. However, heterogeneous responses to muscle fatigue suggest that subject-specific analyses are necessary. The objectives of this study were to: (1) determine if wearable inertial measurement units (IMUs) could be used in conjunction with a spine motion composite index (SMCI) to quantify subject-specific changes in spine kinematics during a repetitive spine flexion-extension (FE) task; and (2) determine if the SMCI was correlated with measures of global trunk muscle fatigue. Spine kinematics were measured using wearable IMUs in 10 healthy adults during a baseline set followed by 10 sets of 50 spine FE repetitions. After each set, two fatigue measures were collected: perceived level of fatigue using a visual analogue scale (VAS), and maximal lift strength. SMCIs incorporating 10 kinematic variables from 2 IMUs (pelvis and T8 vertebrae) were calculated and used to quantify subject-specific changes in movement. A main effect of set was observed (F (1.7, 15.32) = 10.42, p = 0.002), where the SMCI became significantly greater than set 1 starting at set 4. Significant correlations were observed between the SMCI and both fatigue VAS and maximal lift strength at the individual and study level. These findings support the use of wearable IMUs to detect subject-specific changes in spine motion associated with muscle fatigue.

A comparison of augmented feedback and didactic training approaches to reduce spine motion during occupational lifting tasks.

Manual handling training may be improved if it relied on the provision of individualized, augmented feedback about key movement features. The purpose of this study was to compare the reduction in sagittal spine motion during manual lifting tasks following two training approaches: didactic (DID) and augmented feedback (AUG). Untrained participants (n = 26) completed lifting tests (box, medication bag, and paramedic backboard) and a randomly-assigned intervention involving 50 practice box lifts. Lifting tests were performed immediately before and after training, and one-week after interventions. Both groups exhibited reductions in spine motions immediately and one-week after the interventions. However, the AUG intervention group elicited significantly greater reductions in 5 of 12 between-group comparisons (3 tasks × 4 spine motion variables). The results of the current study support the use of augmented feedback-based approaches to manual handling training over education-based approaches.

The role of machine learning in the primary prevention of work-related musculoskeletal disorders: A scoping review.

To determine the applications of machine learning (ML) techniques used for the primary prevention of work-related musculoskeletal disorders (WMSDs), a scoping review was conducted using seven literature databases. Of the 4,639 initial results, 130 primary research studies were deemed relevant for inclusion. Studies were reviewed and classified as a contribution to one of six steps within the primary WMSD prevention research framework by van der Beek et al. (2017). ML techniques provided the greatest contributions to the development of interventions (48 studies), followed by risk factor identification (33 studies), underlying mechanisms (29 studies), incidence of WMSDs (14 studies), evaluation of interventions (6 studies), and implementation of effective interventions (0 studies). Nearly a quarter (23.8%) of all included studies were published in 2020. These findings provide insight into the breadth of ML techniques used for primary WMSD prevention and can help identify areas for future research and development.

Using visual aids to influence manual lifting techniques: acute effects of viewing static images on spine motion.

Purpose. This study aimed to determine whether untrained observers alter their spine as directed via static images of different lifting techniques. Methods. Ten men and eight women, who had no lifting or visual observation training, performed box lifts. Following a self-selected lifting technique trial, participants performed four experimental lifting trials (in randomized order) wherein they were instructed to execute lifts in accordance with the techniques pictured. These techniques differed by the amount of knee, trunk and spine flexion modeled. Peak lumbar flexion angles and flexion/extension velocities were quantified, and then statistically analyzed via general linear models with two within-participant factors (condition = technique; phase = lift/lower). Results. Lumbar flexion angles and flexion/extension velocities differed between conditions (p < 0.001), although the effects depended on the combination of postural characteristics pictured. A main effect of phase was observed for peak lumbar flexion velocity only (p = 0.001). No condition × phase interaction effects were detected for any dependent variables (p > 0.050). Conclusions. Acute changes in lifting mechanics can be elicited via visual observation of pictured techniques. However, if using pictures to attenuate peak lumbar flexion displacements and velocities when lifting, auxiliary instruction may be needed to direct observers' attention to the spine curvature displayed.