Development and Validation of a Wearable Inertial Sensors-Based Automated System for Assessing Work-Related Musculoskeletal Disorders in the Workspace

Ergonomic Analysis of Dental Work in Different Oral Quadrants: A Motion Capture Preliminary Study among Endodontists

BACKGROUND

Dentists, including endodontists, frequently experience musculoskeletal disorders due to unfavourable working postures. Several measures are known to reduce the ergonomic risk; however, there are still gaps in the research, particularly in relation to dental work in the different oral regions (Quadrants 1-4).

METHODS

In this study (of a pilot character), a total of 15 dentists (8 male and 7 female) specialising in endodontics were measured while performing root canal treatments on a phantom head. These measurements took place in a laboratory setting using an inertial motion capture system. A slightly modified Rapid Upper Limb Assessment (RULA) coding system was employed for the analysis of kinematic data. The significance level was set at p = 0.05.

RESULTS

The ergonomic risk for the entire body was higher in the fourth quadrant than in the first quadrant for 80% of the endodontists and higher than in the second quadrant for 87%. For 87% of the endodontists, the ergonomic risk for the right side of the body was significantly higher in the fourth quadrant compared to the first and second quadrant. The right arm was stressed more in the lower jaw than in the upper jaw, and the neck also showed a greater ergonomic risk in the fourth quadrant compared to the first quadrant.

CONCLUSION

In summary, both the total RULA score and scores for the right- and lefthand sides of the body ranged between 5 and 6 out of a possible 7 points. Considering this considerable burden, heightened attention, especially to the fourth quadrant with a significantly higher ergonomic risk compared to Quadrants 1 and 2, may be warranted.

Transparency as a Means to Analyse the Impact of Inertial Sensors on Users during the Occupational Ergonomic Assessment: A Systematic Review

The literature has yielded promising data over the past decade regarding the use of inertial sensors for the analysis of occupational ergonomics. However, despite their significant advantages (e.g., portability, lightness, low cost, etc.), their widespread implementation in the actual workplace has not yet been realized, possibly due to their discomfort or potential alteration of the worker's behaviour. This systematic review has two main objectives: (i) to synthesize and evaluate studies that have employed inertial sensors in ergonomic analysis based on the RULA method; and (ii) to propose an evaluation system for the transparency of this technology to the user as a potential factor that could influence the behaviour and/or movements of the worker. A search was conducted on the Web of Science and Scopus databases. The studies were summarized and categorized based on the type of industry, objective, type and number of sensors used, body parts analysed, combination (or not) with other technologies, real or controlled environment, and transparency. A total of 17 studies were included in this review. The Xsens MVN system was the most widely used in this review, and the majority of studies were classified with a moderate level of transparency. It is noteworthy, however, that there is a limited and worrisome number of studies conducted in uncontrolled real environments.

Musculoskeletal disorders risk assessment methods: a scoping review from a sex perspective

The evidence points to differences in the impact of musculoskeletal disorders (MSD) in males and females due to different exposure to risk factors and inherent characteristics. To identify risks associated with MSDs, ergonomic assessment is carried out by applying various methods. The aim of this scoping review was to determine to what extent ergonomic assessment methods consider sex-related factors and if they were found to do so, to determine the extent of this consideration. A total of 31 papers on 32 ergonomic assessment methods were analysed in the review. Of these 32 methods, only 6 considered sex as an assessment parameter or when interpreting the results. The results revealed that the limited consideration given to the sex factor in ergonomic methods, together with the different impacts of MSDs and their consequences according to a person's sex, supports the importance of including sex factors in ergonomic assessment methods. Practitioner summary: This scoping review determined to what extent ergonomic assessment methods consider sex-related factors and if they do so, to establish the extent of such consideration. Of the 32 methods analysed, only 6 considered a person's sex. The results revealed that only a limited consideration is given to the sex factor in ergonomic methods.

The Three-Dimensional Body Center of Mass at the Workplace under Hypogravity

The center of mass dynamics of the seated posture of humans in a work environment under hypogravity (0 < g < 1) have rarely been investigated, and such research is yet to be carried out. The present study determined the difference in the body system of 32 participants working under simulated 1/6 g (Moon) and 1 g (Earth) for comparison using static and dynamic task measurements. This was based on a markerless motion capture method that analyzed participants' center of mass at the start, middle and end of the task when they began to get fatigued. According to this analysis, there is a positive relationship (p < 0.01) with a positive coefficient of correlation between the downward center of mass body shift along the proximodistal axis and gravity level for males and females. At the same time, the same positive relationship (p < 0.01) between the tilt of the body backward along the anterior-posterior axis and the level of gravity was found only in females. This offers fresh perspectives for comprehending hypogravity in a broader framework regarding its impact on musculoskeletal disorders. It can also improve workplace ergonomics, body stability, equipment design, and biomechanics.

Prevalence of low back pain and its associated factors among traditional cloth weavers in Gulele sub-city, Addis Ababa, Ethiopia

The prevalence of work-related musculoskeletal disorders particularly low back pain is significantly high among common informal or small-scale enterprises within developing countries like weaving. However, there is little information on risk factors for low back pain in the informal sector such as the weaving sector in the areas of Addis Ababa as well as in Ethiopia. Therefore this study was aimed to assess the magnitude of low back pain and its associated factors among traditional cloth weavers in the Gulele sub-city, Addis Ababa, Ethiopia. A cross-sectional study with internal comparison was conducted from June 1, 2022, and August 30, 2022. A total of 660 traditional cloth weavers were included in the study by using a systematic random sampling method to select participants in each of cooperatives as well as individual households in 5 woredas in Gulele sub-city. The data was analyzed and managed using SPSS version 20. A multivariate logistic regression analysis was used to control potential confounding factors and to determine the association. Among 660 (100%) respondents, 330 (50%) of them experienced low back pain after starting weaving. Out of the respondents with low back pain through their job career, 291 (44.1%) of them experienced low back pain during the last 12 months. Working greater than 8 h per day (AOR = 4.60, 95%CI: 2.35, 8.87), working with frequent bending (AOR = 3.32, 95%CI: 1.49, 7.40), job stress (AOR = 1.68, 95%CI: 1.18, 2.40) were among factors significantly associated with the occurrence of low back pain. This study has shown a high prevalence of low back pain among traditional cloth weavers which indicates the need for immediate public health action. However, very small improvements in the working condition, weaving tools design, working methods can potentially lead to large benefits.

Development of a Platform to Assess the Risk of Musculoskeletal Disorders in Manual Load Handling Activities - Preliminary Results

Risk identification on workstations is a crucial step to prevent the occurrence of musculoskeletal disorders (MSD) in workers. The available methods and tools used by ergonomists to assess and estimate the risk related to manual handling of loads under repetitive work cycles are usually biased by the inter-evaluator error that can lead to a subjective determination of work-related risks due to the application of, mainly, observational methods. This paper shows the preliminary results of a platform to assess the risk of musculoskeletal disorders during manual load-handling tasks using an instrumented system and using the National Institute for Occupational Safety & Health (NIOSH) method. Eight healthy subjects were measured during lifting activities using an optical-based and inertial-based motion capture systems. The developed software implements a semi-automated instrumented version of the NIOSH method, helping the evaluator with automated calculations of body segment locations, displacements and joint angles making it possible to obtain a objective risk classification. Also, we achieved a reduction of 85% in the time for the estimation of the necessary factors for the digital evaluation methodology, making the proposed platform a promising and attractive alternative for its application in real environments for risk assessments.Occupational health relevance- This work proposes an assistance tool for the detection of musculoskeletal disorders in activities related to manual handling of loads, essential to initiate modification strategies in the workplace, reduce the occurrence of occupational diseases and reduce the time of risk classification.

The Use of Wearable Inertial Sensors and Workplace-Based Exercises to Reduce Lateral Epicondylitis in the Workstation of a Textile Logistics Center

People whose jobs involve repetitive motions of the wrist and forearm can suffer from lateral epicondylitis, which is a significant burden on both the individual and the employer due to treatment costs, reduced productivity, and work absenteeism. This paper describes an ergonomic intervention to reduce lateral epicondylitis in the workstation of a textile logistics center. The intervention includes workplace-based exercise programs, evaluation of risk factors, and movement correction. An injury- and subject-specific score was calculated from the motion captured with wearable inertial sensors at the workplace to evaluate the risk factors of 93 workers. Then, a new working movement was adapted to the workplace, which limited the observed risk factors and took into account the subject-specific physical abilities. The movement was taught to the workers during personalized sessions. The risk factors of 27 workers were evaluated again after the intervention to validate the effectiveness of the movement correction. In addition, active warm-up and stretching programs were introduced as part of the workday to promote muscle endurance and improve resistance to repetitive stress. The present strategy offered good results at low cost, without any physical modification of the workplace and without any detriment to productivity.

A Wearable Multi-Modal Digital Upper Limb Assessment System for Automatic Musculoskeletal Risk Evaluation

Continuous ergonomic risk assessment of the human body is critical to avoid various musculoskeletal disorders (MSDs) for people involved in physical jobs. This paper presents a digital upper limb assessment (DULA) system that automatically performs rapid upper limb assessment (RULA) in real-time for the timely intervention and prevention of MSDs. While existing approaches require human resources for computing the RULA score, which is highly subjective and untimely, the proposed DULA achieves automatic and objective assessment of musculoskeletal risks using a wireless sensor band embedded with multi-modal sensors. The system continuously tracks and records upper limb movements and muscle activation levels and automatically generates musculoskeletal risk levels. Moreover, it stores the data in a cloud database for in-depth analysis by a healthcare expert. Limb movements and muscle fatigue levels can also be visually seen using any tablet/computer in real-time. In the paper, algorithms of robust limb motion detection are developed, and an explanation of the system is provided along with the presentation of preliminary results, which validate the effectiveness of the new technology.

Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics-An Overview of Current Applications, Challenges, and Future Opportunities

Work-related musculoskeletal disorders (WMSDs) are a major contributor to disability worldwide and substantial societal costs. The use of wearable motion capture instruments has a role in preventing WMSDs by contributing to improvements in exposure and risk assessment and potentially improved effectiveness in work technique training. Given the versatile potential for wearables, this article aims to provide an overview of their application related to the prevention of WMSDs of the trunk and upper limbs and discusses challenges for the technology to support prevention measures and future opportunities, including future research needs. The relevant literature was identified from a screening of recent systematic literature reviews and overviews, and more recent studies were identified by a literature search using the Web of Science platform. Wearable technology enables continuous measurements of multiple body segments of superior accuracy and precision compared to observational tools. The technology also enables real-time visualization of exposures, automatic analyses, and real-time feedback to the user. While miniaturization and improved usability and wearability can expand the use also to more occupational settings and increase use among occupational safety and health practitioners, several fundamental challenges remain to be resolved. The future opportunities of increased usage of wearable motion capture devices for the prevention of work-related musculoskeletal disorders may require more international collaborations for creating common standards for measurements, analyses, and exposure metrics, which can be related to epidemiologically based risk categories for work-related musculoskeletal disorders.

Evaluation of In-Cloth versus On-Skin Sensors for Measuring Trunk and Upper Arm Postures and Movements

Smart workwear systems with embedded inertial measurement unit sensors are developed for convenient ergonomic risk assessment of occupational activities. However, its measurement accuracy can be affected by potential cloth artifacts, which have not been previously assessed. Therefore, it is crucial to evaluate the accuracy of sensors placed in the workwear systems for research and practice purposes. This study aimed to compare in-cloth and on-skin sensors for assessing upper arms and trunk postures and movements, with the on-skin sensors as the reference. Five simulated work tasks were performed by twelve subjects (seven women and five men). Results showed that the mean (±SD) absolute cloth-skin sensor differences of the median dominant arm elevation angle ranged between 1.2° (±1.4) and 4.1° (±3.5). For the median trunk flexion angle, the mean absolute cloth-skin sensor differences ranged between 2.7° (±1.7) and 3.7° (±3.9). Larger errors were observed for the 90th and 95th percentiles of inclination angles and inclination velocities. The performance depended on the tasks and was affected by individual factors, such as the fit of the clothes. Potential error compensation algorithms need to be investigated in future work. In conclusion, in-cloth sensors showed acceptable accuracy for measuring upper arm and trunk postures and movements on a group level. Considering the balance of accuracy, comfort, and usability, such a system can potentially be a practical tool for ergonomic assessment for researchers and practitioners.

Kinematic Analysis of the Forward Head Posture Associated with Smartphone Use

Background: Frequent use of mobile devices has a known association with musculoskeletal neck pain. This study sought out to localize the region with greatest flexion in the cervical spine and explored the role of symmetry in maintaining the pose during texting. Methods: Three inertial measuring units (IMUs) superficially attached along the cervical spine divided the cervical spine into two measurable segments. Twenty-five subjects participated in the study and performed three tasks when using smartphones: sitting, standing, and walking. Data from each IMU were used to calculate the flexion of cervical divided into two segments: craniocervical junction (C0–C1) and subaxial (C1–C7). Results: The greatest flexion by far occurred at C0–C1. While sitting, standing, and walking, the mean flexion angles were 33.33 ± 13.56°, 27.50 ± 14.05°, and 32.03 ± 10.03° for the C0–C1 joint and −3.30 ± 10.10°, 2.50 ± 9.99°, and −1.05 ± 11.88° for the C2–C7 segment, respectively. There is a noticeable pattern of yaw movement of the head, with a slow rotation toward symmetry and a fast corrective movement toward the smartphone held in one hand. Conclusions: This study identified the region of greatest contribution toward forward flexion along the cervical parameters during various tasks involving smartphone use. With each task, the greatest contributor to head flexion was the C0–C1 joint. There is involuntary rotation of the cervical spine toward symmetry when texting.

Effectiveness and usability of real-time vibrotactile feedback training to reduce postural exposure in real manual sorting work

Vibrotactile feedback training may be used as a complementary strategy to reduce time in demanding postures in manual handling. This study evaluated the short- and medium-term effects of concurrent posture-correction vibrotactile feedback training on trunk inclination exposure in real manual sorting work. Fifteen warehouse workers completed the training and the follow-up sessions. Trunk inclination angles were recorded using the ambulatory Smart Workwear System. Questionnaires were used for assessing system usability, perceived physical exertion, and work ability. The results showed reduced time in trunk inclination >30°, >45°, and >60°, and reductions in the 90th, 95th, and 99th percentile trunk inclination angles, when receiving feedback and immediately after feedback withdrawal. No significant reduction was retained after one and three weeks. The wearer's comfort was scored high, and the feedback did not increase the perceived cognitive demands. No significant effects attributed to changed trunk inclination exposure were observed for perceived physical exertion or work ability. The training program has the potential of contributing to reduced trunk inclination exposure in the short term. Future studies are needed to evaluate if improvements in the feedback training can transfer the short-term results to retained median- and long-term effects.Practitioner summary: A two-day training program with concurrent posture-correction vibrotactile feedback can contribute to reduced exposure of trunk inclination in real manual sorting work in the short term. More research is needed on how to design the feedback training programs in order to be effective in the long term.

A Narrative Review on Wearable Inertial Sensors for Human Motion Tracking in Industrial Scenarios

Industry 4.0 has promoted the concept of automation, supporting workers with robots while maintaining their central role in the factory. To guarantee the safety of operators and improve the effectiveness of the human-robot interaction, it is important to detect the movements of the workers. Wearable inertial sensors represent a suitable technology to pursue this goal because of their portability, low cost, and minimal invasiveness. The aim of this narrative review was to analyze the state-of-the-art literature exploiting inertial sensors to track the human motion in different industrial scenarios. The Scopus database was queried, and 54 articles were selected. Some important aspects were identified: (i) number of publications per year; (ii) aim of the studies; (iii) body district involved in the motion tracking; (iv) number of adopted inertial sensors; (v) presence/absence of a technology combined to the inertial sensors; (vi) a real-time analysis; (vii) the inclusion/exclusion of the magnetometer in the sensor fusion process. Moreover, an analysis and a discussion of these aspects was also developed.

Sensor-Based Motion Tracking System Evaluation for RULA in Assembly Task

Industries need a mechanism to monitor the workers' safety and to prevent Work-related Musculoskeletal Disorders (WMSDs). The development of ergonomics assessment tools helps the industry evaluate workplace design and worker posture. Many studies proposed the automated ergonomics assessment method to replace the manual; however, it only focused on calculating body angle and assessing the wrist section manually. This study aims to (a) propose a wrist kinematics measurement based on unobtrusive sensors, (b) detect potential WMSDs related to wrist posture, and (c) compare the wrist posture of subjects while performing assembly tasks to achieve a comprehensive and personalized ergonomic assessment. The wrist posture measurement is combined with the body posture measurement to provide a comprehensive ergonomics assessment based on RULA. Data were collected from subjects who performed the assembly process to evaluate our method. We compared the risk score assessed by the ergonomist and the risk score generated by our method. All body segments achieved more than an 80% similarity score, enhancing the scores for wrist position and wrist twist by 6.8% and 0.3%, respectively. A hypothesis analysis was conducted to evaluate the difference across the subjects. The results indicate that every subject performs tasks differently and has different potential risks regarding wrist posture.

Exploring the efficacy of a set of smart devices for postural awareness for workers in an industrial context – A protocol for a single-subject experimental design (Preprint)

BACKGROUND

In manufacturing industries, tasks requiring poor posture, high repetition, and long duration commonly induce fatigue and lead to an increased risk of work-related musculoskeletal disorders. Smart devices assessing biomechanics and providing feedback to the worker for correction may be a successful way to increase postural awareness, reducing fatigue, and work-related musculoskeletal disorders. However, evidence in industrial settings is lacking.

OBJECTIVE

This study protocol aims to explore the efficacy of a set of smart devices to detect malposture and increase postural awareness, reducing fatigue, and musculoskeletal disorders.

METHODS

A longitudinal single-subject experimental design following the ABAB sequence will be developed in a manufacturing industry real context with 5 workers. A repetitive task of screw tightening of 5 screws in a standing position into a piece placed horizontally was selected. Workers will be assessed in 4 moments per shift (10 minutes after the beginning of the shift, 10 minutes before and after the break, and 10 minutes before the end of the shift) in 5 nonconsecutive days. The primary outcomes are fatigue, assessed by electromyography, and musculoskeletal symptoms assessed by the Nordic Musculoskeletal Questionnaire. Secondary outcomes include perceived effort (Borg perceived exertion scale); range of motion of the main joints in the upper body, speed, acceleration, and deceleration assessed by motion analysis; risk stratification of range of motion; and cycle duration in minutes. Structured visual analysis techniques will be conducted to observe the effects of the intervention. Results for each variable of interest will be compared among the different time points of the work shift and longitudinally considering each assessment day as a time point.

RESULTS

Enrollment for the study will start in April 2023. Results are expected to be available still in the first semester of 2023. It is expected that the use of the smart system will reduce malposture, fatigue, and consequently, work-related musculoskeletal pain and disorders.

CONCLUSIONS

This proposed study will explore a strategy to increase postural awareness in industrial manufacturing workers who do repetitive tasks, using smart wearables that provide real-time feedback about biomechanics. Results would showcase a novel approach for improving self-awareness of risk for work-related musculoskeletal disorders for these workers providing an evidence base support for the use of such devices.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/43637.

A Work-Related Musculoskeletal Disorders (WMSDs) Risk-Assessment System Using a Single-View Pose Estimation Model

Musculoskeletal disorders are an unavoidable occupational health problem. In particular, workers who perform repetitive tasks onsite in the manufacturing industry suffer from musculoskeletal problems. In this paper, we propose a system that evaluates the posture of workers in the manufacturing industry with single-view 3D human pose-estimation that can estimate the posture in 3D using an RGB camera that can easily acquire the posture of a worker in a complex workplace. The proposed system builds a Duckyang-Auto Worker Health Safety Environment (DyWHSE), a manufacturing-industry-specific dataset, to estimate the wrist pose evaluated by the Rapid Limb Upper Assessment (RULA). Additionally, we evaluate the quality of the built DyWHSE dataset using the Human3.6M dataset, and the applicability of the proposed system is verified by comparing it with the evaluation results of the experts. The proposed system provides quantitative assessment guidance for working posture risk assessment, assisting the continuous posture assessment of workers.

Review of the Application of Wearable Devices in Construction Safety: A Bibliometric Analysis from 2005 to 2021

Wearable devices as an emerging technology to collect safety data on construction site is gaining increasing attention from researchers and practitioners. Given the rapid development of wearable devices research and the high application prospects of wearable devices in construction safety, a state-of-the-art review of research and implementations in this field is needed. The aim of this study is to provide an objective and extensive bibliometric analysis of the published articles on wearable applications in construction safety for the period of 2005–2021. CiteSpace software was used to conduct co-citation analysis, co-occurrence analysis, and cluster identification on 169 identified articles. The results show that 10 research clusters (e.g., attentional failure, brain-computer interface) were extremely important in the development of wearable devices for construction safety. The results highlight the evolution of wearable devices in construction-safety-related research, revealing the underlying structure of this cross-cutting research area. The analysis also summarizes the status quo of wearable devices in the construction safety field and provides a dynamic platform for integrating future applications.

Prevalence and factors associated with work-related musculoskeletal disorder among health care providers working in the operation room

Background

Work-related musculoskeletal disorder is a major and frequently underappreciated problem on people, countries, healthcare services, and society as a whole. Not only have detrimental health impacts, but it had considerable damage on healthcare services and costs.

Objective

The aim of this study was to determine the prevalence and factors associated with work-related musculoskeletal diseases among health care providers working in the operating room of University of Gondar comprehensive specialized hospital and Tibebe Ghion comprehensive specialized hospital, North West Ethiopia, 2021.

Method

Institution-based cross-sectional study was conducted on 394 healthcare providers. Purposive sampling was used to select the study participants. Data were collected through a self-administer questionnaire using the standard Nordic Musculoskeletal Questionnaire. Descriptive statistics and bivariate logistic regression were done to identify factors associated with work-related musculoskeletal disorders. Variables with P-value≤ 0.05 with 95% confidence interval in a multivariate model were taken as statistically significant. Finally, AOR with 95% confidence interval at a P-value<0.05 was reported.

Result

The prevalence of work-related musculoskeletal disorder among study participants was 64.2% with 95% CI: (59.4, 69.0). In multivariate logistic regression analysis; working overtime [AOR:1.74; 95% CI (1.05, 2.86)], previous history of MSD [AOR:6.85; 95%CI:(1.91, 22.7)], being diploma holder [AOR:5.27; 95% CI (1.12, 24.68)], being 1st degree holder [AOR:2.65; 95% CI (1.11, 6.28)], absence of assistance during procedures [AOR:1.73; 95% CI (1.02, 2.85)], and working in night shifts [AOR:1.72; 95% CI (1.08, 2.74)] were significantly associated with work related musculoskeletal disease among health care providers working in operation room.

Conclusion

A high proportion of hospital care providers working in the operation room reported MSD at different body parts. Lower back pain was the most often complained. Working overtime, not having assistance during procedures, educational status (diploma and 1st degree holder), and working at night shifts were statistically significant associated with musculoskeletal disorders.

Wearable inertial sensors for human movement analysis: a five-year update

INTRODUCTION

The aim of the present review is to track the evolution of wearable IMUs from their use in supervised laboratory- and ambulatory-based settings to their application for long-term monitoring of human movement in unsupervised naturalistic settings.

AREAS COVERED

Four main emerging areas of application were identified and synthesized, namely, mobile health solutions (specifically, for the assessment of frailty, risk of falls, chronic neurological diseases, and for the monitoring and promotion of active living), occupational ergonomics, rehabilitation and telerehabilitation, and cognitive assessment. Findings from recent scientific literature in each of these areas was synthesized from an applied and/or clinical perspective with the purpose of providing clinical researchers and practitioners with practical guidance on contemporary uses of inertial sensors in applied clinical settings.

EXPERT OPINION

IMU-based wearable devices have undergone a rapid transition from use in laboratory-based clinical practice to unsupervised, applied settings. Successful use of wearable inertial sensing for assessing mobility, motor performance and movement disorders in applied settings will rely also on machine learning algorithms for managing the vast amounts of data generated by these sensors for extracting information that is both clinically relevant and interpretable by practitioners.

Implementation of Kinetic and Kinematic Variables in Ergonomic Risk Assessment Using Motion Capture Simulation: A Review

Work-related musculoskeletal disorders (WMSDs) are among the most common disorders in any work sector and industry. Ergonomic risk assessment can reduce the risk of WMSDs. Motion capture that can provide accurate and real-time quantitative data has been widely used as a tool for ergonomic risk assessment. However, most ergonomic risk assessments that use motion capture still depend on the traditional ergonomic risk assessment method, focusing on qualitative data. Therefore, this article aims to provide a view on the ergonomic risk assessment and apply current motion capture technology to understand classical mechanics of physics that include velocity, acceleration, force, and momentum in ergonomic risk assessment. This review suggests that using motion capture technologies with kinetic and kinematic variables, such as velocity, acceleration, and force, can help avoid inconsistency and develop more reliable results in ergonomic risk assessment. Most studies related to the physical measurement conducted with motion capture prefer to use non-optical motion capture because it is a low-cost system and simple experimental setup. However, the present review reveals that optical motion capture can provide more accurate data.

A Wearable Sensor-Based Platform for Surgeon Posture Monitoring: A Tool to Prevent Musculoskeletal Disorders

Surgeons are workers that are particularly prone to the development of musculoskeletal disorders. Recent advances in surgical interventions, such as laparoscopic procedures, have caused a worsening of the scenario, given the harmful static postures that have to be kept for long periods. In this paper, we present a sensor-based platform specifically aimed at monitoring the posture during actual surgical operations. The proposed system adopts a limited number of Inertial Measurement Units (IMUs) to obtain information about spine and neck angles across time. Such a system merges the reliability of sensor-based approaches and the validity of state-of-the-art scoring procedure, such as RULA. Specifically, three IMUs are used to estimate the flexion, lateral bending, and twisting angles of spine and neck. An ergonomic risk index is thus estimated in a time varying fashion borrowing relevant features from the RULA scoring system. The detailed functioning of the proposed systems is introduced, and the assessment results related to a real surgical procedure, consisting of a laparoscopy and mini-laparotomy sections, are shown and discussed. In the exemplary case study introduced, the surgeon kept a high score, indicating the need for an intervention on the working procedures, for a large time fraction. The system allows separately analyzing the contribution of spine and neck, also specifying the angle configuration. It is shown how the proposed approach can provide further information, as related to dynamical analysis, which could be used to enlarge the features taken into account by currently available approaches for ergonomic risk assessment. The proposed system could be adopted both for training purposes, as well as for alerting surgeons during actual surgical operations.

A Review of Relevant Regulations, Requirements and Assessment Methods Concerning Physical Load in Workplaces in the Slovak Republic

This review brings an overview of the Slovak regulations concerning occupational safety and health at work (OSH) primarily considering the parameter of physical load. In addition to regulations, this article focuses on particular requirements at workplaces with an increased physical load and describes the permissible values of the physical load (see tables). Attention is given to assessing the working posture and handling of loads. The main purpose of the evaluation is to determine the parameters of physical load, which is the first important step in the process of health risk assessment. Based on the physical load assessment and the categorization of tasks for the physical load factor in the Slovak Republic, further steps and measures should be taken to improve working conditions, to reduce the workload, number of health problems, fatigue, and ultimately to prevent accidents at work and work-related musculoskeletal diseases.

Estimation of Human Center of Mass Position through the Inertial Sensors-Based Methods in Postural Tasks: An Accuracy Evaluation

The estimation of the body’s center of mass (CoM) trajectory is typically obtained using force platforms, or optoelectronic systems (OS), bounding the assessment inside a laboratory setting. The use of magneto-inertial measurement units (MIMUs) allows for more ecological evaluations, and previous studies proposed methods based on either a single sensor or a sensors’ network. In this study, we compared the accuracy of two methods based on MIMUs. Body CoM was estimated during six postural tasks performed by 15 healthy subjects, using data collected by a single sensor on the pelvis (Strapdown Integration Method, SDI), and seven sensors on the pelvis and lower limbs (Biomechanical Model, BM). The accuracy of the two methods was compared in terms of RMSE and estimation of posturographic parameters, using an OS as reference. The RMSE of the SDI was lower in tasks with little or no oscillations, while the BM outperformed in tasks with greater CoM displacement. Moreover, higher correlation coefficients were obtained between the posturographic parameters obtained with the BM and the OS. Our findings showed that the estimation of CoM displacement based on MIMU was reasonably accurate, and the use of the inertial sensors network methods should be preferred to estimate the kinematic parameters.