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Low back disorders are more predominant among construction trade workers than their counterparts in other industry sectors. Floor layers are among the top artisans that are severely affected by low back disorders. Exoskeletons are increasingly being perceived as ergonomic solutions. This study aims to compare the efficacy of passive and active back-support exoskeletons by measuring range of motion, perceived discomfort, usability, perceived rate of exertion and cognitive load during a simulated flooring task experiment.

In this study eight participants were engaged in a repetitive timber flooring task performed with passive and active back-support exoskeletons. Subjective and objective data were collected to assess the risks associated with using both exoskeletons. Descriptive statistics were used for analysis. Scheirer-Ray-Hare test and Wilcoxon signed-rank test were adopted to compare the exoskeleton conditions.

The results show no significant differences in the range of motion (except for a lifting cycle), perceived level of discomfort and perceived level of exertion between the two exoskeletons. Significant difference in overall cognitive load was observed. The usability results show that the active back-support exoskeleton made task execution easier with less restriction on movement.

The flooring task is simulated in a laboratory environment with only eight male participants.

This study contributes to the scarce body of knowledge on the usage comparison of passive and active exoskeletons for construction work.

Carpenters are constantly vulnerable to musculoskeletal disorders. Their work consists of subtasks that promote nonfatal injuries and pains that affect different body segments. The purpose of this study is to examine ergonomic exposures of carpentry subtasks involved in floor framing, how they lead to musculoskeletal injuries, and how preventive and protective interventions around them can be effective.

Using wearable sensors, this study characterizes ergonomic exposures of carpenters by measuring and analyzing body movement data relating to major subtasks in carpentry flooring work. The exposures are assessed using Postural Ergonomic Risk Assessment classification, which is based on tasks involving repetitive subtasks and nonstatic postures.

The findings of this paper suggest severe risk impositions on the trunk, shoulder and elbow as a result of the measuring and marking and cutting out vent locations, as well as in placing and nailing boards into place.

Because of the type and size of wearable sensor used, only results of risk exposures of four body-parts are presented.

This study draws insights on how to benchmark trade-specific measurement of work-related musculoskeletal disorders. Safety efforts can be targeted toward these risk areas and subtasks. Specifically, results from these will assist designers and innovators in designing effective and adaptable protective interventions and safety trainings.

Extant studies have failed to provide adequate evidence regarding the relationships between subtasks and musculoskeletal disorders; they have only mimicked construction tasks through laboratory experimental scenarios. This study adds value to the existing literature, in particular by providing insights into hazards associated with floor carpentry subtasks.

Work-related low back disorders (LBDs) are prevalent among rebar workers although their causes remain uncertain. The purpose of this study is to examine the self-reported discomfort and spinal biomechanics (muscle activity and spinal kinematics) experienced by rebar workers.

In all, 20 healthy male participants performed simulated repetitive rebar lifting tasks with three different lifting weights, using either a stoop (n = 10) or a squat (n = 10) lifting posture, until subjective fatigue was reached. During these tasks, trunk muscle activity and spinal kinematics were recorded using surface electromyography and motion sensors, respectively.

A mixed-model, repeated measures analysis of variance revealed that an increase in lifting weight significantly increased lower back muscle activity at L3 level but decreased fatigue and time to fatigue (endurance time) (p < 0.05). Lifting postures had no significant effect on spinal biomechanics (p < 0.05). Test results revealed that lifting different weights causes disproportional loading upon muscles, which shortens the time to reach working endurance and increases the risk of developing LBDs among rebar workers.

Future research is required to: broaden the research scope to include other trades; investigate the effects of using assistive lifting devices to reduce manual handling risks posed; and develop automated human condition-based solutions to monitor trunk muscle activity and spinal kinematics.

This study fulfils an identified need to study laboratory-based simulated task conducted to investigate the risk of developing LBDs among rebar workers primarily caused by repetitive rebar lifting.

Concrete workers perform physically demanding work in awkward postures, exposing their backs to musculoskeletal disorders. Back-support exoskeletons are promising ergonomic interventions designed to reduce the risks of back disorders. However, the suitability of exoskeletons for enhancing performance of concrete workers has not been largely explored. This study aims to assess a passive back-support exoskeleton for concrete work in terms of the impact on the body, usability and benefits of the exoskeleton, and potential design modifications.

Concrete workers performed work with a passive back-support exoskeleton. Subjective and qualitative measures were employed to capture their perception of the exoskeleton, at the middle and end of the work, in terms of discomfort to their body parts, ease of use, comfort, performance and safety of the exoskeleton, and their experience using the exoskeleton. These were analyzed using descriptive statistics and thematic analysis.

The exoskeleton reduced stress on the lower back but caused discomfort to other body parts. Significant correlations were observed between perceived discomfort and usability measures. Design modifications are needed to improve the compatibility of the exoskeleton with the existing safety gears, reduce discomfort at chest and thigh, and improve ease of use of the exoskeleton.

The study was conducted with eight concrete workers who used the exoskeleton for four hours.

This study contributes to existing knowledge on human-wearable robot interaction and provides suggestions for adapting exoskeleton designs for construction work.

Work-related musculoskeletal disorders constitute a severe problem in the construction industry. Workers' lower backs are often affected by heavy or repetitive lifting and prolonged awkward postures. Exoskeletal interventions are effective for tasks involving manual lifting and repetitive movements. This study aims to examine the potential of a postural-assist exoskeleton (a passive exoskeleton) for manual material handling tasks.

From an experimental observation of participants, the effects of postural-assist exoskeleton on tasks and workers were measured. Associated benefits of the exoskeleton were assessed through task performance, range of motion and discomfort.

Findings suggest that the exoskeleton influenced discomfort significantly, however range of motion decreased with lifting tasks. The reduced back flexion and increased hip flexion were also indicatives of the participants' responsiveness to the feedback from the exoskeleton. In addition, task completion time increased by 20%, and participants' back pain did not reduce.

The work tasks were performed in a controlled laboratory environment and only wearable inertia measurement units (IMUs) were used to assess the risk exposures of the body parts.

This study opens a practical pathway to human-exoskeleton integration, artificial regeneration or enablement of impaired workforce and a window toward a new order of productivity scaling. Results from this study provide preliminary insights to designers and innovators on the influence of postural assist exoskeleton on construction work. Project stakeholders can be informed of the suitability of the postural assist exoskeletons for manual material handling tasks.

Little has been reported on the benefits and impact of exoskeletons on tasks' physical demands and construction workers' performance. This study adds value to the existing literature, in particular by providing insights into the effectiveness and consequences of the postural-assist exoskeleton for manual material handling tasks.

Low back disorder is one of the most prevalent and costly injuries in the construction industry. Back-support exoskeletons are increasingly perceived as promising solutions. However, the intended benefits of exoskeletons may not be realized if intention-to-use the device is low. Social influence could increase intention-to-use exoskeletons. This study aims to evaluate the impact of social influence on construction workers' intention-to-use back-support exoskeletons.

A field study involving 37 construction workers was conducted, with workers who used exoskeleton for one week, and their peers and supervisors. Data were collected using questionnaires and semi-structured interviews, and analyzed using descriptive statistics and thematic analysis, respectively.

The workers felt that the exoskeleton is easy to use and the functions are well integrated. Workers' intention-to-use exoskeleton was mainly influenced by employers providing and requiring the use of the device. The attitude of the workers and the perception of peers and supervisors did not have a significant impact on workers' intention-to-use exoskeleton, whereas the subjective norm of construction workers had a positive impact on the intention-to-use exoskeletons.

The study involved only 37 workers, including 15 workers who used the exoskeleton, and 14 peers and 8 supervisors of the workers.

This study contributes to existing knowledge on the influence of social influence on intention-to-use exoskeletons. The study also highlights how exoskeleton designs and the construction workplace can influence behavioral intention-to-use exoskeletons.

The purpose of this paper is to review the prevalence and risk factors of work-related musculoskeletal disorders (WMSDs) among healthcare workers (HCWs) in order to ascertain the occupation with the highest susceptibility to WMSD in the health sector. This paper will also review the effective interventions which have been used to prevent WMSDs among HCWs.

This study is a literature review of 11 papers related to the prevalence and risk factors of WMSDs and 12 papers about the interventions being used to prevent WMSDs among HCWs. The papers were retrieved from respectable databases such as PubMed, Science Direct, Google Scholar and E-Thesis.

Nurses belong to the major group of HCWs who had the highest prevalence of WMSDs compared with other health professionals and other hospital workers. Although there are several interventions being commonly used to prevent WMSD risk factors, some interventions were unsuccessful in the prevention of WMSDs in healthcare tasks. Therefore, it is necessary that future research focuses on the tasks of HCWs that are WMSD risk factors and tries to innovate or redesign ergonomic workstations to prevent those risk factors.

The expected benefit of this study is to motivate ergonomists to provide appropriate and innovative interventions to ensure health and safety for nurses and other HCWs.

The demanding nature of firefighting exposes firefighters to unprecedented work stress and work-related musculoskeletal disorders (WMSDs). Even though relationships among work demand, work stress and WMSDs have been examined, the mediating role of work stress in the relationship between work demand and WMSDs requires more attention, particularly among emergency workers. The purpose of this paper is to therefore assess the mediation role of firefighters’ work stress in the pathway of work demand and WMSDs.

A quantitative research design was used. Convenient sampling was employed to select 320 firefighters from the Greater Accra region of Ghana. Data were analyzed using descriptive, correlation and regression.

The findings revealed that work demand and stress significantly affect WMSDs. Also, work demand has a significant positive effect on work stress. It was further found that work stress partially mediates the relationship between work demand and WMSDs.

The usage of cross-sectional data limits the strength of causality and observation of changes within units of observation over time, hence the need to use longitudinal data in future studies.

The novelty of this study lies in the revelation of the influence of stress in the pathway of work demand and WMSDs among emergency professionals, using an African lens.

The purpose of this paper is to develop an expert system capable of assessing risk associated with manual lifting in construction tasks and proffer some first aid advices which are comparable with those obtainable from human experts.

The expert system, musculoskeletal disorders – risk evaluation expert system (MSDs-REES), used Microsoft.Net C# programming language to write the algorithm of the fuzzy inference system with variables load, posture and frequency of lift as inputs and risk of low back pain as the output. The algorithm of the inference engine applied sets of rules to generate the output variable in crisp value.

The result of validation, between the human experts’ calculated risk values and MSDs-REES-predicted risk values, indicated a correlation coefficient of 0.87. Between the predicted risk values generated using MSDs-REES and the existing package (MATLAB version 7.8), there was a strong positive relationship statistically with correlation coefficient of 0.97.

The study provided a very simple expert system which has the ability to provide some medical-related injury prevention advice and first aid information for injury management, giving it a unique attribute over the existing applications.

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.