Prevention Of Musculoskeletal Disorders Research Articles

Musculoskeletal Diseases as the Most Prevalent Component of Multimorbidity: A Population-Based Study

Background/Objectives: Due to their high frequency, common risk factors, and similar pathogenic mechanisms, musculoskeletal disorders (MSDs) are more likely to occur with other chronic illnesses, making them a “component disorder“ of multimorbidity. Our objective was to assess the prevalence of multimorbidity and to identify the most common clusters of diagnosis within multimorbidity states, with the primary hypothesis that the most common clusters of multimorbidity are MSDs. Methods: The current study employed data from a population-based 2019 European Health Interview Survey (EHIS). Multimorbidity was defined as a ≥2 diagnosis from the list of 17 chronic non-communicable diseases, and to define clusters, the statistical method of hierarchical cluster analysis (HCA) was performed. Results: Out of 13,178 respondents, multimorbidity was present among 4398 (33.4%). The HCA method yielded six multimorbidity clusters representing the most common diagnoses. The primary multimorbidity cluster, which was prevalent among both genders, age groups, incomes per capita, and statistical regions, consisted of three diagnoses: (1) lower spine deformity or other chronic back problem (back pain), (2) cervical deformity or other chronic problem with the cervical spine, and (3) osteoarthritis. Conclusions: Given the influence of musculoskeletal disorders on multimorbidity, it is imperative to implement appropriate measures to assist patients in relieving the physical discomfort and pain they endure. Public health information, programs, and campaigns should be utilized to promote a healthy lifestyle. Policymakers should prioritize the prevention of MSDs by encouraging increased physical activity and a healthy diet, as well as focusing on improving functional abilities.

Biomechanical Posture Analysis in Healthy Adults with Machine Learning: Applicability and Reliability.

Posture analysis is important in musculoskeletal disorder prevention but relies on subjective assessment. This study investigates the applicability and reliability of a machine learning (ML) pose estimation model for the human posture assessment, while also exploring the underlying structure of the data through principal component and cluster analyses. A cohort of 200 healthy individuals with a mean age of 24.4 ± 4.2 years was photographed from the frontal, dorsal, and lateral views. We used Student's t-test and Cohen's effect size (d) to identify gender-specific postural differences and used the Intraclass Correlation Coefficient (ICC) to assess the reliability of this method. Our findings demonstrate distinct sex differences in shoulder adduction angle (men: 16.1° ± 1.9°, women: 14.1° ± 1.5°, d = 1.14) and hip adduction angle (men: 9.9° ± 2.2°, women: 6.7° ± 1.5°, d = 1.67), with no significant differences in horizontal inclinations. ICC analysis, with the highest value of 0.95, confirms the reliability of the approach. Principal component and clustering analyses revealed potential new patterns in postural analysis such as significant differences in shoulder-hip distance, highlighting the potential of unsupervised ML for objective posture analysis, offering a promising non-invasive method for rapid, reliable screening in physical therapy, ergonomics, and sports.

Reliability and validity tests of the Chinese version of the Geriatric Locomotive Function Scale (GLFS-25) in tumor survivors

ObjectiveTo evaluate the reliability and validity of the Chinese-translated Geriatric Locomotive Function Scale (GLFS-25) for the assessment of locomotive syndrome (LS) in individuals surviving malignancies. Methods393 tumor survivors at a general hospital in China were recruited. The Chinese version of GLFS-25 was utilized to conduct a cross-sectional survey to ascertain the tool's efficacy in measuring LS in this cohort. The scale's validity was examined through content, structural and discriminant validity assessments, while its reliability was investigated by determining the internal consistency (via Cronbach's α coefficient) and test-retest reliability (via intragroup correlation coefficient, ICC). ResultsThe Chinese-adapted GLFS-25 demonstrated a robust scale-level content validity index of 0.94, while item-level content validity indices ranged from 0.83 to 1.00 across individual items. The suitability of the scale for structural validity assessment was confirmed via exploratory factor analysis, yielding a Kaiser-Meyer-Olkin measure of 0.930 and a significant Bartlett's test of sphericity (χ2 = 3217.714, df = 300, P < 0.001). Subsequent confirmatory factor analysis (CFA) extracted four distinct factors: Social Activity Engagement, Daily Living Ability, Pain Experience and Physical Mobility. These factors accounted for 72.668 % of the variance, indicating substantial construct validity for measuring LS among this population. CFA supported the model's fit with the following indices: χ2/df = 1.559, RMSEA = 0.077, GFI = 0.924, CFI = 0.941, NFI = 0.919, and TLI = 0.933. The factor loadings for the four factors ranged from 0.771 to 0.931, indicating the items corresponding to the four factors effectively represented the constructs they were designed to measure. The correlation coefficients among the four factors were between 0.306 and 0.469, all lower than the square roots of the respective AVEs (0.838–0.867). This suggests a moderate correlation among the four factors and a distinct differentiation between them, indicating the Chinese version of the GLFS-25 exhibits strong discriminant validity in Chinese tumor survivors. Reliability testing revealed a high Cronbach's α coefficient for the overall scale at 0.961, with the subscales yielding coefficients of 0.751, 0.836, 0.930, and 0.952. The overall ICC was determined to be 0.935, with subscale ICCs ranging from 0.857 to 0.941, reinforcing the scale's reliability in this context. ConclusionsThe Chinese version of the GLFS-25 exhibits strong reliability and validity for the assessment of LS in tumor survivors. It may serve as a diagnostic tool for LS, contributing to the prevention and management of musculoskeletal disorders and enhancing the prognosis for this patient population.

The association between diabetes mellitus and musculoskeletal disorders: a systematic review and meta-analysis.

Despite the fact that DM patients are living longer, research on the prevalence of MSDs and other related illnesses is still lacking compared to that of other comorbidities. This study systematically reviewed and meta-analyzed cohort studies to determine the association between diabetes mellitus (DM) and musculoskeletal disorders (MSDs). A comprehensive search of international databases, including Medline (PubMed), Web of Science, Scopus, and Embase, was conducted up to June 2023 to identify relevant studies investigating the association between MSDs and DM. The meta-analysis included ten cohort studies with a total of 308,445 participants. The pooled risk ratio (RR) estimate for the association between MSDs and DM was 1.03 (95% CI 1.00-1.06). Based on subgroup analysis, the association between longer duration (more than 7), European, below the age of 70, and female patients was higher than the others. In conclusion, the results of this meta-analysis suggest that there may be an association between MSDs and diabetes in people with diabetes. These findings add to the existing knowledge on this topic and highlight the importance of recognition and management of MSDs in people with DM. There is a need for further research to investigate the underlying mechanisms and to develop targeted interventions for the prevention and management of MSDs in this population. https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=381787, identifier CRD42022381787.

Work-related musculoskeletal disorders in oral health professionals: an umbrella review protocol.

The objective of this review is to synthesize the evidence on the prevalence, incidence, risk factors, and preventive and management interventions for work-related musculoskeletal disorders (MSD) in oral health professionals. Oral health professionals face a considerable risk of developing work-related MSD due to the nature of their work. These disorders can lead to loss of employment, reduced job quality, increased occupational injuries, and early retirement. They can also lead to significant financial burdens for employers and society. This umbrella review will include systematic reviews and meta-analyses that have oral health professionals as a population group and address at least one of the following topics: the prevalence or incidence, risk factors, and the efficiency or effectiveness of interventions for the prevention or management of work-related MSD. A systematic search will be conducted across CINAHL Complete (EBSCOhost), Dentistry and Oral Sciences Source (EBSCOhost), MEDLINE (EBSCOhost), Cochrane Library (OVID), Scopus, PsycINFO (Ovid), AMED Allied and Complementary Medicine (Ovid), Epistemonikos, Ergonomics Abstracts Online (EBSCOhost), and Google Scholar (first 200 articles). The search will be limited to articles published in English, with no restrictions on geographical location. Two independent reviewers will screen the titles and abstracts against the inclusion criteria. The studies will be assessed using the JBI critical appraisal instrument for systematic reviews and research syntheses, and data will be extracted from each study using a modified version of the JBI data extraction tool. The GRADE approach will be used to rate the overall quality and strength of the evidence. PROSPERO CRD42023388779.

Improved REBA: deep learning based rapid entire body risk assessment for prevention of musculoskeletal disorders

Preventing work-related musculoskeletal disorders (WMSDs) is crucial in reducing their impact on individuals and society. However, the existing mainstream 2D image-based approach is insufficient in capturing the complex 3D movements and postures involved in many occupational tasks. To address this, an improved deep learning-based rapid entire body assessment (REBA) method has been proposed. The method takes working videos as input and automatically outputs the corresponding REBA score through 3D pose reconstruction. The proposed method achieves an average precision of 94.7% on real-world data, which is comparable to that of ergonomic experts. Furthermore, the method has the potential to be applied across a wide range of industries as it has demonstrated good generalisation in multiple scenarios. The proposed method offers a promising solution for automated and accurate risk assessment of WMSDs, with implications for various industries to ensure the safety and well-being of workers.

Role of NLRP3 inflammasomes in musculoskeletal disorders

Inflammasomes are innate immune sensors and receptors that play key pathological roles in the development and progression of numerous diseases. Recent studies have shown that NLRP3 inflammasomes are critical in the pathology of diseases with a high impact on public health, such as musculoskeletal disorders. Musculoskeletal disorders, mainly caused or aggravated by work and the surrounding environment, are locomotor system disorders such as muscles, joints, bones, as well as diseases associated with neurological and circulatory system injuries. Activation of NLRP3 inflammasomes can induce inflammation and pyroptosis, leading to further bodily harm. Therefore, investigating the mechanism and function of NLRP3 inflammasomes, holds great significance and importance for the prevention and treatment of musculoskeletal disorders. This review provides a summary of the activation pathway and mechanism of NLRP3 inflammasomes, and analyzes the role in musculoskeletal disorders such as sarcopenia, osteoporosis and arthritis, with the aim to facilitate the treatment of musculoskeletal disorders.

The Role of Physical Exercise in the Prevention of Musculoskeletal Disorders in Manual Workers: A Systematic Review and Meta-Analysis.

Work-related musculoskeletal disorders (WMSDs) are the most common occupational health problem in the European Union. Physical exercise interventions have been investigated in the prevention of WMSDs in many sectors. Therefore, our aim was to assess the effect of physical exercise in manual workers for the primary and secondary prevention of WMSDs. We conducted a systematic search of the literature and papers were included if: the participants were adult employees exclusively engaged in manual labor tasks; non-acute physical exercise intervention; pain, disability, physical functioning, or health-related quality of life outcome, with pre-post intervention measurements. We retrieved 10419 unique records and included 23 studies. A random effect meta-analysis was conducted on the studies with a control group design, using a three level model to estimate the pooled effect for pain outcomes (g = 0.4339, 95% CI : 0.1267 - 0.7412, p < 0.01), and a two-level model for disability outcomes (g = 0.6279, 95% CI : 0.3983 - 0.8575, p < 0.0001). Subset analysis revealed a moderate-to-large effect on the VAS outcome (g = 0.5866, 95% CI: 0.3102 - 0.8630, p < 0.0001). Meta-regression on pain outcomes revealed a significant effect for sex, age, study quality, and body segments tested. The analyses on all outcomes except VAS showed substantial heterogeneity (I2pain = 93%, of which 72% at the study level, I2disability = 78%, and I2vas = 56%, of which 44% at the study level). Physical exercise programs seem to have a positive effect on pain and disability stemming from WRMSDs in manual workers.

ASSESMENT OF KNOWLEDGE OF LIGHT MICROSCOPIC ERGONOMICS AMONG PATHOLOGISTS

Back Ground Sound knowledge regarding ergonomics and their practical application are essential for prevention of musculoskeletal disorders (MSD). The role of microscopic ergonomics (ME) in preventing these work related ailments is significant. Methods Authors conducted a cross sectional survey among pathologist of Davangere city, Karnataka, India. The data was collected using 26 - item custom designed proforma, with questions evaluating pathologist’s basic knowledge about microscopic ergonomics. Results Of 100 subjects surveyed, 70% pathologists (staff and post graduate) stated that they came across microscopic ergonomics only through this survey. Also 100% pathologists of believed that the emphasis about microscopic ergonomics is less in the present dental curriculum. Conclusions The findings suggest that the pathologist’s comprehension regarding microscopic ergonomics is limited. This study advocates the revision of dental curricula regarding microscopic ergonomics to prevent musculoskeletal injuries. Practical Implications Increased importance should be given during formative years of dental education about this essential clinical entity either via textbook education or in continuing dental education (CDE) programs. Key Words Microscopic ergonomics; musculoskeletal disorders; micro breaks

Impacts and prevention of musculoskeletal disorders among odontostomatologists

Musculoskeletal disorder (MSD) is a group of periarticular conditions affecting the soft and bony tissues of the limbs and back. Its prevalence is high among odontostomatologists, ranging from 60 to 90.3%. It is therefore a real source of concern and a public health problem. The aim of this study was therefore to describe the impacts and prevention of this disorder among odontostomatologists. This is a literature review study following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. The documentary search on scientific databases was carried out using the keywords TMS, odontostomatologists, ergonomics, prevention. The study included all articles on the impacts and prevention of MSDs among odontostomatologists published over the past 10 years from 2013 to 2023 written in French or English without restriction as to article type. Incomplete, irrelevant articles published in scientific conferences were excluded . The study analyzed 32 articles and showed that the main impacts of MSDs were pain (56.5%), self-medication (17.4%), reduced quality of work and working hours (17.4%), absenteeism and early retirement (13.0%). Prevention was based on the practice of good ergonomics (73.3%), the use of magnifying glasses (33.3%) and the practice of physical exercise after work (20%). Given these results, ongoing training in MSD prevention is essential to reduce or avoid its occurrence.

Coping Strategies and Prevention Programs for Musculoskeletal Disorders among Academic Staff in Lagos State-owned Tertiary Institutions: A Descriptive Study

Musculoskeletal disorders (MSDs) pose a significant challenge for academic staff, affecting their well-being and productivity within tertiary institutions. This study explores the coping strategies and prevention programs among academic staff in Lagos State-owned tertiary institutions. Using the descriptive survey research design, data was collected from 316 academics using the convenient sampling technique. With the aid of the descriptive statistics and the content analysis, findings indicate a varied utilization of both prevention (e.g., regular exercise, ergonomic workspace) and coping strategies (e.g., pain medication, assistive devices), emphasizing potential gaps in stress management and certain preventive measures. Academics suggest recommendations for effective MSD prevention programs, including ergonomic considerations, stress reduction workshops, workload management, and physical activity breaks. Based on these findings, it is recommended that management of Lagos stateowned tertiary institutions should implement ergonomic interventions, stress reduction workshops and fostering health-conscious work cultures.

Spatial relationship-aware rapid entire body fuzzy assessment method for prevention of work-related musculoskeletal disorders

In the advent of Industry 5.0, advances in human-centered smart manufacturing (HSM) accentuate the role of humans in human–machine collaboration. This development has catapulted human health in human-machine systems to the forefront of the conversation. Although various tools have emerged to mitigate work-related musculoskeletal disorders (WMSDs), combining biomechanics with human morphology, the extant methods primarily hinge on expert scoring. Such methods display a step-wise change between risk levels, yielding inadequate assessment accuracy and posing challenges to human health assurance in HSM. To address these issues, this study proposes a spatial relationship-aware rapid entire body fuzzy assessment technique. The proposed method enhances the rapid entire body assessment (REBA) by enacting a dynamic evaluation of WMSD-related risk via a deep learning-based 3D pose reconstruction. Contrary to the step-wise transitions between REBA's different risk levels, the proposed method actualizes a fuzzy assessment of WMSD risk by introducing weights between these levels. This innovation allows for a more accurate risk assessment for workers engaged in HSM. Validation through experiments conducted on data from an automobile production line demonstrates that the proposed method can achieve a precision rate of 99.31%. Demo videos and code are available at https://github.com/giim-hf-lab/REBA-PLUS.

Measuring ergonomic interventions and prevention programs for reducing musculoskeletal injury risk in the dental workforce: A systematic review.

Pain from musculoskeletal disorders (MSD) is experienced by all types of dental clinicians, leading to forced reduction of work capacity and premature retirement. Prolonged static posture is a major contributor to MSD in dentistry. Currently, there is no uniform ergonomic training in dentistry to prevent MSD. This systematic review explored and summarized methods and technologies for baseline and ongoing measurements of ergonomic intervention and prevention programs for reducing postural risk and for prevention of MSDs. The review was conducted in accordance with PRISMA guidelines. The literature search included PUBMED, Embase, CINAHL and the Cochrane Library, and identified relevant observational, experimental, quasi-experimental, research, and intervention studies. Quality was rated using a validated standardized instrument. A total of 20 studies were included, of which 4 were rated as being of the high quality. Methods ranged from observers to motion sensors. Ten studies focused used established measuring tools (PAI, RULA, REBA), while nine studies focused on effectiveness of alternative methods of measurement. One study identified ISO standard 11226 for baseline comparisons. Evolving technologies were found to be suitable for baseline measurements of posture, and for feedback for developing sustainable postural behaviors. No studies measured ongoing postural performance improvement. This systematic review adds to current evidence for the expanded and improved use of early training and testing of postural competence to reduce MSD risk among dental professionals. Further studies using technologies to assess the impacts of ergonomic training and testing among dental professionals are warranted.

Deformation of palmar hand measurements in a power grip by wrist ulnar/radial deviation

ObjectivesThe present study analyzed changes in palmar hand measurements during power grip by wrist radial/ulnar deviation for an ergonomic grip design. MethodTwelve palmar dimensions (Tip-to-PTC/DTC distances, Tip-to-MMC distances, and Tip-to-MMC surface lengths) of digits 2 to 5 were measured for 30 Koreans with various hand sizes (15 males and 15 females; hand length = 177.9 ± 12.3 mm) at three wrist postures (neutral, 20° of radial deviation, and 30° of ulnar deviation) using 3D scanning and casting methods. ResultsAs the hand changed from the straight neutral posture to the power grip posture, the Tip-to-PTC/DTC distances (related to grip widths), Tip-to-MMC distances (related to grip heights), and Tip-to-MMC surface lengths (related to grip circumferences) decreased to 30%–65% compared to corresponding original lengths. Wrist posture also had significant effects on the Tip-to-PTC/DTC and Tip-to-MMC distances by 6.5%–9.0%, while finger position significantly affected all the measurements by 8.2%–22.3%. Practitioner summaryThe measurement protocol of palmar hand dimensions and the changes in palmar hand measurements by wrist posture are of use to develop an ergonomic handle design for comfort and prevention of musculoskeletal disorders.

텍스트마이닝을 활용한 작업관련성 근골격계질환 연구동향 분석

Domestic musculoskeletal disorders have been on the rise since the 1997 IMF crisis, as rapid changes in work environments and practices, such as mechanization, automation, and specialization, have been implemented by various companies to enhance productivity. Furthermore, with increasing awareness and concern among workers, the government has been conducting harmful factor and causal investigations related to musculoskeletal disorders caused by burdensome work tasks through the amendment of Article 39 of the Industrial Safety and Health Act since 2003.&#x0D; To ensure the proactive prevention of work-related musculoskeletal disorders and minimize work-related losses for workers' safety, there is a continuous need for systematic and comprehensive research. To address this, the present study conducted a trend analysis to explore new perspectives for preventing industrial accidents.&#x0D; The literature collection comprised a total of 653 domestic theses and academic papers from 2003 to 2022 that included the keyword 'musculoskeletal disorder,' gathered through search engines such as the Korean Citation Index (KCI) and the Research Information Sharing Service (RISS). The data were categorized into two periods: the first period from 2003 to 2012 and the second period from 2013 to 2022. Text mining was employed to analyze the frequency (TF) and network connections, which were subsequently visualized.&#x0D; The results revealed that the top keywords in work-related musculoskeletal disorder research throughout the entire period (2003 to 2022) were 'work,' 'musculoskeletal disorder,' and 'symptoms,' consistently recognized as essential research topics in both the first and second periods. In the first period, the most frequently discussed factors influencing workers' musculoskeletal disorders included 'posture,' 'physical condition,' 'environment,' 'job stress,' 'time,' 'age,' and the term 'survey' was prominent among the top keywords. In the second period, keywords like 'comparison,' 'development,' 'measurement,' 'method,' and 'investigation' emerged.&#x0D; N-Gram analysis indicated that the simultaneous occurrence of the 'musculoskeletal disorder-symptoms' keyword was the most frequent throughout the entire period, followed by high frequencies of 'musculoskeletal disorder,' 'pain,' 'awareness,' and 'burden.' In the first period, body part-related keywords like 'hand-wrist,' 'shoulder-back,' 'wrist-finger,' and 'back-leg' were prominent. In the second period, keywords such as 'workload,' 'safety-health,' 'factor-investigation,' 'risk-assessment,' and 'occupational accident-insurance' were observed.&#x0D; This study attempted the first analysis of theses and academic papers on work-related musculoskeletal disorders using text mining, a big data analysis method. The findings contribute to suggesting future research directions on work-related musculoskeletal disorders, holding significant implications for the field.

PENGARUH OBESITAS TERHADAP KARAKTERISTIK POLA BERJALAN : LITERATURE REVIEW

Obesity is a global health problem with increasing prevalence worldwide. One aspect of concern is how obesity can affect an individual's gait characteristics, leading to musculoskeletal disorders. Numerous studies have explored the gait characteristics experienced by individuals with obesity. The objective of this literature review is to provide further information on the gait characteristics of individuals with obesity, which can be utilized for the prevention of obesity-related musculoskeletal disorders. The methodology employed in this study is a literature review, creating conclusions from selected data sources from various national and international journals published between 2011 and 2021. The findings reveal that obesity can lead to decreased balance, reduced walking speed, and influence several gait characteristic parameters, such as changes in step length and width, stride length, as well as various angles formed by the knee and ankle joints during walking, resulting in a distinct gait pattern compared to normal gait. Therefore, it can be concluded that individuals with obesity are prone to exhibit an altered gait pattern, which can potentially contribute to musculoskeletal problems such as osteoarthritis.

JS-16 Causes and prevention of musculoskeletal disorders in the work environment

JS-16 Causes and prevention of musculoskeletal disorders in the work environment

Development and evaluation of a mobile app-based musculoskeletal exercise program for operating room nurses

Purpose: The aim of this study was to develop a mobile app-based musculoskeletal exercise program (AMSEP) for operating room (OR) nurses and evaluate its effects on self-efficacy, the flexibility of the shoulders, lower back, and legs, and musculoskeletal symptoms and fatigue. Methods: The AMSEP was developed based on the information-motivation-behavioral skill model. In total, 48 OR nurses were recruited at a university hospital in Korea and divided into an experimental group (n=24) and a control group (n=24), matched for career experience in the OR. The experimental group participated in the AMSEP, while the control group received a booklet regarding musculoskeletal exercise. Results: The experimental group showed significant increases in self-efficacy (t = -2.77, p = .008) and flexibility of the right shoulder (t = -4.08, p &lt; .001), left shoulder (t = -3.28, p = .002), lower back (t = -3.75, p &lt; .001), and legs (t = -3.96, p &lt; .001) compared to the control group. Musculoskeletal symptoms (t = 2.75, p = .008), and fatigue (Z = -1.98, p = .048) significantly decreased in the experimental group compared to the control group. Conclusion: Our findings indicate that the AMSEP for OR nurses provided information on the prevention of musculoskeletal disorders and methods of exercise, as well as an opportunity for continued exercise performance through self-management. The AMSEP was easily accessible and effective in increasing self-efficacy and flexibility and reducing musculoskeletal symptoms and fatigue.

Smart vision-based analysis and error deduction of human pose to reduce musculoskeletal disorders in construction

PurposeThis 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.Design/methodology/approachUsing 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).FindingsResults 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.Research limitations/implicationsLiterature 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.Practical implicationsThe 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.Social implicationsBy 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.Originality/valueHuman 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.

High-Sensitive Double-Clad Fiber Bragg Grating Sensors for Real-Time Monitoring of Body Posture and Movement State

Musculoskeletal disorders (MSD) are prevalent in society and currently lack effective treatments. The incidence of MSD appears to be increasing as the worldwide population ages and sedentary lifestyles. Real-time monitoring of the body posture and movement state may be an effective strategy for the prevention and treatment of MSD. We proposed a real-time monitoring system based on a wearable high-sensitive double-clad fiber Bragg grating (FBG) sensors and an integrated demodulation device to recognize the body posture and movement state. The results demonstrate that the double-clad FBG sensors exhibit a high measurement sensitivity of approximately 36 pm/° in elbow joint static tests and 7.5 pm/° in knee joint static tests, which is almost 1.4 times higher than that of a single-mode FBG. Furthermore, a dataset of six gestures was created based on time and wavelength information obtained from six double-clad FBG sensors monitoring subtle deformations of muscles of the arm. The accuracy of recognizing simple and complex gestures was close to 100% and about 88%, respectively. The static and dynamic measurements demonstrate that the double-clad sensors have high accuracy, improved sensitivity, excellent flexibility and good repeatability, and this work is expected to a reliable assessment tool for clinical trials of MSD.