Trunk kinematics and low back pain during pruning among vineyard workers-A field study at the Chateau Larose-Trintaudon

Influence of brick laying height on biomechanical load in masons: Cross-sectional field study with technical measurements

BACKGROUND

Work-related musculoskeletal disorders (WMSDs) located in the low back and neck/shoulder regions are major concerns for both workers, workplaces, and society. Masons are prone to WMSD, because their work is characterized by repetitive work and high physical workload. However, the knowledge on the physical workload during bricklaying is primarily based on subjective measurements.

OBJECTIVE

This cross-sectional field study with technical measurements aimed to quantify physical workload in terms of muscular activity and degree of forward bending during bricklaying at different working heights among masons, i.e., knee, hip, shoulder, and above shoulder height.

METHODS

Twelve male (36.1±16.1 years) experienced masons participated in a cross-sectional field study with technical measurements. Surface electromyography from erector spinae longissimus and upper trapezius muscles and an inertial measurement unit-sensor placed on the upper back were used to assess the physical workload (level of muscle activation and degree of forward bending) different bricklaying heights. Manual video analysis was used to determine duration of work tasks, frequency, type, and working height. The working heights were categorized as 'knee', 'hip', 'shoulder', and 'above shoulder'. The 95 percentiles of the normalized Root Mean Square (RMSn) values were extracted assess from erector spinae and trapezius recordings to assess strenuous level muscle of muscle activation.

RESULTS

The RMSn of dominant erector spinae muscle increased from hip- to shoulder height (from 26.6 to 29.6, P < 0.0001), but not from hip to above shoulder height and decreased from hip to knee height (from 26.6 to 18.9, P < 0.0001). For the dominant trapezius muscle, the RMSn increased from hip- to shoulder- and above shoulder height (from 13.9 to 19.7 and 24.0, respectively, P < 0.0001) but decreased from hip- to knee height (from 13.9 to 11.5, P < 0.0001). Compared to hip height (27.9°), an increased forward bending was detected during bricklaying at knee height (34.5°, P < 0.0001) and a decreased degree of forward bending at shoulder- and above shoulder height (17.6° and 12.5°, P < 0.0001, respectively).

CONCLUSION

Based on technical measurements, bricklaying at hip height showed the best compromise between muscular load and degree of forward bending. This study contributes to the development of the work environment for masons and can help guide preventive initiatives to reduce physical workload.

Effects of a warm-up intervention at the workplace on pain, heart rate, work performance and psychological perception among vineyard workers

OBJECTIVES

Warm-up sessions before physical activity are widely used in sports to help prevent injury and improve performance. Nowadays, companies assume that the effects observed in a sport context can be transferred to the workplace, particularly among workers exposed to biomechanical strain. Yet research on the use of warm-up interventions at the workplace is rather scarce and, when available, leads to conflicting results due to the low quality of the studies. To the best of our knowledge, there are no published studies to date assessing the effects of warm-up sessions among vineyard workers. The present study was designed to investigate if and how a single supervised warm-up session could be effective on perceived pain intensity, heart rate, work performance, and psychological perceptions among vineyard workers.

METHODS

A total of 31 vineyard workers completed a randomized crossover study at the workplace. They were observed in real work settings, i.e. during the pruning activity. Each participant performed the activity under two conditions: 1) with a warm-up session beforehand (WU) and 2) without any warm-up (NWU). Heart rate (HR) was assessed continuously before and during the warm-up, and during the first hour of pruning. Perceived pain intensity over fifteen anatomical locations was assessed before (T0) and immediately after (T1) warm-up, and after the first hour of work (T2). Readiness to work was assessed at T1. Work performance was assessed in terms of the number of completed tasks (number of pruned vines). Perceived work quality and perceived work ability were assessed at T2.

RESULTS

Perceived pain intensity over the lumbopelvic region was significantly higher at T2 than at T0, and at T2 than at T1, in both WU and NWU. Perceived pain intensity was not significantly different at T2 in WU and NWU. HR at T1 was significantly higher in WU than in NWU. Work performance, readiness to work, and perceived work ability were significantly higher in WU than in NWU.

CONCLUSION

This study showed that offering vineyard workers a supervised warm-up session at the workplace can lead to promising results where work performance and psychological perception are concerned.

Exploring acute effects of workplace warm-up intervention on pain, physical capacities, and productivity in agriculture:- A study protocol

BACKGROUND: Physical activity programs at the workplace have shown positive results on physical capacities and pain for several years. Due to the duration of the training session or the need for an instructor, these supervised programs are rather difficult to implement. For this reason, numerous companies, especially companies in manual sectors, are turning to another solution, i.e. warm-up intervention before the work shift. These interventions present various advantages such as short duration and the possibility to perform exercises in working clothes. Surprisingly, while the positive effects of warm-up interventions on pain, performance, and physical and psychological capacities are expansively reported in the sport context, effects of workplace warm-up intervention are lacking. OBJECTIVE: The aim of this study is to assess the acute effects of three different warm-up interventions on physical (pain, strength, flexibility) and psychological (workload) functions and also on work-related outcomes (work performance, readiness to work) among vineyard workers. METHODS: A cluster randomized study will be implemented among French vineyard workers. Four groups of 30 participants will be constituted; corresponding to four different conditions: (1) hybrid warm-up intervention (HWU); (2) dynamic warm-up intervention (DWU); (3) stretching warm-up intervention (SWU); (4) no warm-up intervention (NWU). A total of 120 vineyard workers will be recruited to participate in the study. CONCLUSION: The results will provide more evidence about the short-term effects of warm-up interventions at the workplace and will provide more evidence on which warm-up modality is the most effective on pain, performance, and physical and psychological capacities among vineyard workers.

Motion Capture Technology in Industrial Applications: A Systematic Review

The rapid technological advancements of Industry 4.0 have opened up new vectors for novel industrial processes that require advanced sensing solutions for their realization. Motion capture (MoCap) sensors, such as visual cameras and inertial measurement units (IMUs), are frequently adopted in industrial settings to support solutions in robotics, additive manufacturing, teleworking and human safety. This review synthesizes and evaluates studies investigating the use of MoCap technologies in industry-related research. A search was performed in the Embase, Scopus, Web of Science and Google Scholar. Only studies in English, from 2015 onwards, on primary and secondary industrial applications were considered. The quality of the articles was appraised with the AXIS tool. Studies were categorized based on type of used sensors, beneficiary industry sector, and type of application. Study characteristics, key methods and findings were also summarized. In total, 1682 records were identified, and 59 were included in this review. Twenty-one and 38 studies were assessed as being prone to medium and low risks of bias, respectively. Camera-based sensors and IMUs were used in 40% and 70% of the studies, respectively. Construction (30.5%), robotics (15.3%) and automotive (10.2%) were the most researched industry sectors, whilst health and safety (64.4%) and the improvement of industrial processes or products (17%) were the most targeted applications. Inertial sensors were the first choice for industrial MoCap applications. Camera-based MoCap systems performed better in robotic applications, but camera obstructions caused by workers and machinery was the most challenging issue. Advancements in machine learning algorithms have been shown to increase the capabilities of MoCap systems in applications such as activity and fatigue detection as well as tool condition monitoring and object recognition.

Trunk Flexion Monitoring among Warehouse Workers Using a Single Inertial Sensor and the Influence of Different Sampling Durations

Trunk flexion represents a risk factor for the onset of low-back disorders, yet limited quantitative data exist regarding flexion exposures in actual working conditions. In this study, we evaluated the potential of using a single inertial measurement unit (IMU) to classify trunk flexion, in terms of amplitude, frequency, and duration, and assessed the influence of alternative time durations on exposure results. Twelve warehouse workers were monitored during two hours of an actual shift while wearing a single IMU on their low back. Trunk flexion data were reduced using exposure variation analysis integrated with recommended exposure thresholds. Workers spent 5.1% of their working time with trunk flexion of 30-60° and 2.3% with flexion of 60-90°. Depending on the level of acceptable error, relatively shorter monitoring periods (up to 50 min) might be sufficient to characterize trunk flexion exposures. Future work is needed, however, to determine if these results generalize to other postural exposures and tasks.

A novel vision-based real-time method for evaluating postural risk factors associated with musculoskeletal disorders

Real-time risk assessment for work-related musculoskeletal disorders (MSD) has been a challenging research problem. Previous methods such as using depth cameras suffered from limited visual range and wearable sensors could cause intrusiveness to the workers, both of which are less feasible for long-run on-site applications. This document examines a novel end-to-end implementation of a deep learning-based algorithm for rapid upper limb assessment (RULA). The algorithm takes normal RGB images as input and outputs the RULA action level, which is a further division of RULA grand score. Lifting postures collected in laboratory and posture data from Human 3.6 (a public human pose dataset) were used for training and evaluating the algorithm. Overall, the algorithm achieved 93% accuracy and 29 frames per second efficiency for detecting the RULA action level. The results also indicate that using data augmentation (a strategy to diversify the training data) can significantly improve the robustness of the model. The proposed method demonstrates its high potential for real-time on-site risk assessment for the prevention of work-related MSD. A demo video can be found at https://github.com/LLDavid/RULA_2DImage.

Biomechanical factors during common agricultural activities: Results of on-farm exposure assessments using direct measurement methods

Agricultural work is associated with increased risk of adverse musculoskeletal health outcomes. The purpose of this study was to quantify exposure to biomechanical factors among a sample (n = 55) of farmers in the Midwest region of the U.S. while they performed a variety of routine agricultural activities, and to compare exposure levels between these activities. Surface electromyography was used to estimate activity levels of the erector spinae, upper trapezius, forearm flexor, and forearm extensor muscle groups. Simultaneously, inertial sensors were used to measure kinematics of the trunk, upper arm, and wrist. In general, lower muscle activity levels, less extreme postures, and slower movement speeds were observed during activities that involved primarily the use of agricultural machinery in comparison to manual activities, suggesting a potential advantage of mechanization relative to musculoskeletal health. Median wrist movement speeds exceeding recently proposed exposure thresholds were also observed during many manual activities, such as milking animals and repairing equipment. Upper arm postures and movement speeds did not appear to confer excessive risk for shoulder-related outcomes (on the whole), but interpretation of the results is limited by a sampling approach that may not have captured the full extent of exposure variation. Not surprisingly, substantial variation in exposure levels were observed within each agricultural activity, which is related to substantial variation in the equipment, tools, and work practices used by participants. Ultimately, the results of this study contribute to an emerging literature in which the physical demands of routine agricultural work have been described on the basis of sensor-based measurements rather than more common self-report or observation-based approaches.

Sensor Technologies to Manage the Physiological Traits of Chronic Pain: A Review

Non-oncologic chronic pain is a common high-morbidity impairment worldwide and acknowledged as a condition with significant incidence on quality of life. Pain intensity is largely perceived as a subjective experience, what makes challenging its objective measurement. However, the physiological traces of pain make possible its correlation with vital signs, such as heart rate variability, skin conductance, electromyogram, etc., or health performance metrics derived from daily activity monitoring or facial expressions, which can be acquired with diverse sensor technologies and multisensory approaches. As the assessment and management of pain are essential issues for a wide range of clinical disorders and treatments, this paper reviews different sensor-based approaches applied to the objective evaluation of non-oncological chronic pain. The space of available technologies and resources aimed at pain assessment represent a diversified set of alternatives that can be exploited to address the multidimensional nature of pain.

Effects of a Participatory Ergonomics Intervention With Wearable Technical Measurements of Physical Workload in the Construction Industry: Cluster Randomized Controlled Trial

Background

Construction work frequently involves heavy physical work, and a reduction of the physical workload should have high priority. Technological development has made it possible to obtain field measurements with surface electromyography (sEMG), kinematics measured with inertial measurement units (IMUs), and video recordings. However, no studies have used these methods simultaneously to detect situations with excessive physical workload (events) during a working day. Thus, knowledge about these specific events may combat work-related risk factors. Participatory ergonomics (PE) has shown promising results, but whether it can be used as a tool to reduce the physical workload during construction work remains unknown.

Objective

This cluster randomized controlled trial investigated whether a PE intervention with technical measurements consisting of IMUs, sEMG, heart rate monitoring, and video recordings of physical workload could reduce the number of events with excessive physical workload during a working day. Furthermore, other outcomes were obtained from questionnaires.

Methods

A total of 80 male full-time construction workers (aged 19 to 67 years) were randomized at the cluster level (gang) to a PE intervention consisting of 3 workshops (7 gangs and 32 workers) or to a control group (8 gangs and 48 workers). The physical workload was recorded by technical measurements, that is, IMUs, sEMG, heart rate monitoring, and video recordings during a full working day at baseline and 3 and 6 months’ follow-up. On the basis of the technical measurements, a custom-made computer program detected the situations (events) where the construction workers were exposed to excessive physical workload and used in the intervention. Differences in the number of events from baseline to follow-up between intervention and control were evaluated using linear mixed models (intention-to-treat), with individual nested in cluster as a random factor. Furthermore, questionnaires were filled out on test days.

Results

The results of the primary outcome showed no change in the number of events with excessive physical workload. However, compared with the control group, the other outcomes showed decreased general fatigue after a typical working day (P=.001) and increased influence on own work (P=.04).

Conclusions

This PE intervention with technical measurements did not reduce the number of events with excessive physical workload during construction work. However, the intervention led to decreased general fatigue and increased influence on own work.

Trial Registration

ClinicalTrials.gov NCT02498197; https://clinicaltrials.gov/ct2/show/NCT02498197 (Archived by WebCite at http://www.webcitation.org/74SZ3DIWS)

Accuracy of identification of low or high risk lifting during standardised lifting situations

The aim was to classify lifting activities into low and high risk categories (according to The Danish Working Environment Authority guidelines) based on surface electromyography (sEMG) and trunk inclination (tri-axial accelerometer) measurements. Lifting tasks with different weights, horizontal distance and technique were performed. The lifting tasks were characterised by a feature vector composed of either the 90th, 95th or 99th percentile of sEMG activity level and trunk inclinations during the task. Linear Discriminant Analysis and a subject-specific threshold scheme were applied and lifting tasks were classified with an accuracy of 65.1-65.5%. When lifts were classified based on the subject-specific threshold scheme from low and upper back accelerometers, the accuracy reached 52.1-58.1% and 72.7-78.1%, respectively. In conclusion, the use of subject-specific thresholds from sEMG from upper trapezius and erector spinae as well as inclination of the upper trunk enabled us to identify low and high risk lifts with an acceptable accuracy. Practitioner Summary: This study contributes to the development of a method enabling the automatic detection of high risk lifting tasks, i.e. exposure to high biomechanical loads, based on individual sEMG and kinematics from an entire working day. These methods may be more cost-effective and may complement observations commonly used by practitioners.

Method for measuring tri-axial lumbar motion angles using wearable sheet stretch sensors

BACKGROUND

Body movements, such as trunk flexion and rotation, are risk factors for low back pain in occupational settings, especially in healthcare workers. Wearable motion capture systems are potentially useful to monitor lower back movement in healthcare workers to help avoid the risk factors. In this study, we propose a novel system using sheet stretch sensors and investigate the system validity for estimating lower back movement.

METHODS

Six volunteers (female:male = 1:1, mean age: 24.8 ± 4.0 years, height 166.7 ± 5.6 cm, weight 56.3 ± 7.6 kg) participated in test protocols that involved executing seven types of movements. The movements were three uniaxial trunk movements (i.e., trunk flexion-extension, trunk side-bending, and trunk rotation) and four multiaxial trunk movements (i.e., flexion + rotation, flexion + side-bending, side-bending + rotation, and moving around the cranial-caudal axis). Each trial lasted for approximately 30 s. Four stretch sensors were attached to each participant's lower back. The lumbar motion angles were estimated using simple linear regression analysis based on the stretch sensor outputs and compared with those obtained by the optical motion capture system.

RESULTS

The estimated lumbar motion angles showed a good correlation with the actual angles, with correlation values of r = 0.68 (SD = 0.35), r = 0.60 (SD = 0.19), and r = 0.72 (SD = 0.18) for the flexion-extension, side bending, and rotation movements, respectively (all P < 0.05). The estimation errors in all three directions were less than 3°.

CONCLUSION

The stretch sensors mounted on the back provided reasonable estimates of the lumbar motion angles. The novel motion capture system provided three directional angles without capture space limits. The wearable system possessed great potential to monitor the lower back movement in healthcare workers and helping prevent low back pain.