Effect of muscular fatigue on the cumulative lumbar damage during repetitive lifting task: a comparative study of damage calculation methods.

Several methods have been put forward to quantify cumulative loads; however, limited evidence exists as to the subsequent damages and the role of muscular fatigue. The present study assessed whether muscular fatigue could affect cumulative damage imposed on the L5-S1 joint. Trunk muscle electromyographic (EMG) activities and kinematics/kinetics of 18 healthy male individuals were evaluated during a simulated repetitive lifting task. A traditional EMG-assisted model of the lumbar spine was modified to account for the effect of erector spinae fatigue. L5-S1 compressive loads for each lifting cycle were estimated based on varying (i.e. actual), fatigue-modified, and constant Gain factors. The corresponding damages were integrated to calculate the cumulative damage. Moreover, the damage calculated for one lifting cycle was multiplied by the lifting frequency, as the traditional approach. Compressive loads and the damages obtained through the fatigue-modified model were predicted in close agreement with the actual values. Similarly, the difference between actual damages and those driven by the traditional approach was not statistically significant (p = 0.219). However, damages based on a constant Gain factor were significantly greater than those based on the actual (p = 0.012), fatigue-modified (p = 0.017), and traditional (p = 0.007) approaches.Practitioner summary: In this study, we managed to include the effect of muscular fatigue on cumulative lumbar damage calculations. Including the effect of muscular fatigue leads to an accurate estimation of cumulative damages while eliminating computational complexity. However, using the traditional approach also appears to provide acceptable estimates for ergonomic assessments.

Changes in Neck and Shoulder Muscles Fatigue Threshold When Using a Passive Head/Neck Supporting Exoskeleton During Repetitive Overhead Tasks.

OBJECTIVE: This study aimed to investigate the effects of a head/neck supporting exoskeleton (HNSE) on the electromyographic fatigue threshold (EMGFT) of the neck and shoulder muscles during a simulated overhead work task. BACKGROUND: Overhead work is a well-known risk factor for neck and shoulder musculoskeletal disorders due to the excessive strain imposed on the muscles and joints in these regions. METHOD: Fourteen healthy males performed a repetitive overhead nut fastening/unfastening task to exhaustion while wearing and not wearing the HNSE at two neck extension angles (40% and 80% of neck maximum range of motion). Electromyographic signals were continuously recorded from the right and left sternocleidomastoid (SCMR, SCML), splenius capitis (SCR, SCL), upper trapezius (UTR, UTL), and anterior deltoid (ADR, ADL) muscles. The normalized electromyographic amplitude (nEMG) data was time normalized, and a bisegmental linear regression was applied to determine the muscle fatigue break point. RESULTS: The results showed a significant increase in fatigue threshold time in the SCMR (p < .001), SCML (p = .002), and UTR (p = .037) muscles when the HNSE was used. However, the EMGFT times for the right and left deltoid and left trapezius muscles showed a nonsignificant reduction due to the head/neck support exoskeleton use. In addition, the neck extension angle did not reveal a significant effect on muscles' EMGFT time. CONCLUSION: Overall, the findings confirmed a significant delay in fatigue onset in sternocleidomastoid muscles, as measured by the electromyographic fatigue threshold. This finding suggests that the HNSE can be an effective ergonomic intervention for reducing the risk of musculoskeletal disorders in overhead workers. However, further studies are needed to investigate the effect of the HNSE at other neck extension angles and more realistic tasks to ensure the generalizability of our results. APPLICATION: The present findings emphasize the application of the fatigue onset time to evaluate the effectiveness of ergonomic interventions, including exoskeletons, which can subsequently be utilized to alleviate postural demands and reduce the risk of musculoskeletal disorders.

Nonlinear analysis of postural changes related to the movement interventions during prolonged standing task.

This study assessed the effects of movement-based interventions on the complexity of postural changes during prolonged standing. Twenty participants, equally distributed in gender and standing work experience (SWE), completed three simulated prolonged standing sessions: without movement (control), leg exercise and footrest. The amount and complexity of variability in the centre of pressure (COP) and lumbar curvature angle were quantified using linear and nonlinear tools. Lower leg swelling and back/leg discomfort were also monitored. Participants in the SWE group showed significantly greater postural complexity during the standing. Regular leg exercise resulted in significantly higher postural complexity and lower leg discomfort and swelling. The footrest led to significant changes in amount of COP variability. Both interventions significantly reduced back discomfort. Overall, the nonlinear analysis of postural changes provided different findings compared to linear ones, considering the standing time, interventions and standing job experience. Nonlinear results were consistent with leg discomfort and swelling.Practitioner summary: The effect of movement-based interventions on dynamics of postural alterations over prolonged standing were characterised using nonlinear techniques. The effect of standing work experience was also considered. Previous experience of standing jobs and leg movements increase the complexity of postural behaviour over standing period.

Perceived Discomfort, Neck Kinematics, and Muscular Activity During Smartphone Usage: A Comparative Study.

OBJECTIVE: The present study aims to evaluate the effects of posture, task, and handgrip style on discomfort, neck kinematics, and concomitant muscular activity when using a smartphone (SP). BACKGROUND: Along with the popularity of smartphones, musculoskeletal disorders have become prevalent among smartphone users. However, comprehensive aspects of discomfort, kinematics, and electromyographic responses across various conditions remain to be investigated. METHOD: Twenty-four young smartphone users performed typing, video watching, and reading tasks while holding the smartphone both with one hand and with two hands while either sitting or standing. Neck kinematics and muscular activities were simultaneously recorded. RESULTS: Working with SPs led to higher discomfort in the neck (p = 0.01), lower back (p = 0.01), and shoulder (p = 0.04) while sitting as compared to standing. Sitting was associated with greater neck flexion and more minor lateral bending for all tasks and grip styles (p < 0.05). Electromyographic analysis indicated significant differences between sitting and standing, with alterations being dependent on the test condition. Moreover, neck kinematics and muscular activities significantly differed based on the task nature, handgrip, and interactions. CONCLUSION: This study highlights the risk of using smartphones in increased neck angle flexion and muscular activities fatigue. Thus, posture and handgrip should be considered while using SPs. As each test condition affects a specific dependent variable, a holistic approach is required to evaluate the responses of SP users' musculoskeletal systems. APPLICATION: Results can be applied to develop guidelines for musculoskeletal disorders/discomfort prevention among SP users, especially with the rise of smartphone use during the COVID-19 pandemic.

A Comprehensive Evaluation of Spine Kinematics, Kinetics, and Trunk Muscle Activities During Fatigue-Induced Repetitive Lifting.

OBJECTIVE: Spine kinematics, kinetics, and trunk muscle activities were evaluated during different stages of a fatigue-induced symmetric lifting task over time. BACKGROUND: Due to neuromuscular adaptations, postural behaviors of workers during lifting tasks are affected by fatigue. Comprehensive aspects of these adaptations remain to be investigated. METHOD: Eighteen volunteers repeatedly lifted a box until perceived exhaustion. Body center of mass (CoM), trunk and box kinematics, and feet center of pressure (CoP) were estimated by a motion capture system and force-plate. Electromyographic (EMG) signals of trunk/abdominal muscles were assessed using linear and nonlinear approaches. The L5-S1 compressive force (Fc) was predicted via a biomechanical model. A two-way multivariate analysis of variance (MANOVA) was performed to examine the effects of five blocks of lifting cycle (C1 to C5) and lifting trial (T1 to T5), as independent variables, on kinematic, kinetic, and EMG-related measures. RESULTS: Significant effects of lifting trial blocks were found for CoM and CoP shift in the anterior-posterior direction (respectively p < .001 and p = .014), trunk angle (p = .004), vertical box displacement (p < .001), and Fc (p = .005). EMG parameters indicated muscular fatigue with the extent of changes being muscle-specific. CONCLUSION: Results emphasized variations in most kinematics/kinetics, and EMG-based indices, which further provided insight into the lifting behavior adaptations under dynamic fatiguing conditions. APPLICATION: Movement and muscle-related variables, to a large extent, determine the magnitude of spinal loading, which is associated with low back pain.

Driver drowsiness is associated with altered facial thermal patterns: Machine learning insights from a thermal imaging approach.

Driver drowsiness is a significant factor in road accidents. Thermal imaging has emerged as an effective tool for detecting drowsiness by enabling the analysis of facial thermal patterns. However, it is not clear which facial areas are most affected and correlate most strongly with drowsiness. This study examines the variations and importance of various facial areas and proposes an approach for detecting driver drowsiness. Twenty participants underwent tests in a driving simulator, and temperature changes in various facial regions were measured. The random forest method was employed to evaluate the importance of each facial region. The results revealed that temperature changes in the nasal area exhibited the highest value, while the eyes had the most correlated changes with drowsiness. Furthermore, drowsiness was classified with an accuracy of 88 % utilizing thermal variations in the facial region identified as the most important regions by the random forest feature importance model. These findings provide a comprehensive overview of facial thermal imaging for detecting driver drowsiness and introduce eye temperature as a novel and effective measure for investigating cognitive activities.

Evaluation of driver drowsiness based on respiratory metrics.

BACKGROUND: The transition from alertness to drowsiness can cause considerable changes in the respiratory system, providing an opportunity to detect driver drowsiness. OBJECTIVE: The aim of this study was to determine which respiratory features indicate driver drowsiness and then use these features to classify the level of drowsiness and alertness. METHODS: Twenty male students (mean age 25.6±2.41 years) participated in the study using a driving simulator, and eight features, including expiration duration (ED), inspiration duration (ID), peak-to-peak amplitude (PA), inspiration-to-expiration time ratio (I/E ratio), driving, timing, respiration rate (RR), and yawning, were extracted from the respiratory signal generated by abdominal motions using a belt equipped with a force sensor. RESULTS: All eight features were statistically significant at the significance level of 0.05. Drowsiness can be detected using respiratory features with 88% accuracy, 82% precision, 86% recall, and an 90% F1 score. CONCLUSION: The findings of this study may be useful in the development of driver drowsiness monitoring systems based on less intrusive respiratory signal analysis, particularly for specific process automation applications when vehicle control is not in the hands of the driver.

A hybrid approach for driver drowsiness detection utilizing practical data to improve performance system and applicability.

BACKGROUND: Numerous systems for detecting driver drowsiness have been developed; however, these systems have not yet been widely used in real-time. OBJECTIVE: The purpose of this study was to investigate at the feasibility of detecting alert and drowsy states in drivers using an integration of features from respiratory signals, vehicle lateral position, and reaction time and out-of-vehicle ways of data collection in order to improve the system's performance and applicability in the real world. METHODS: Data was collected from 25 healthy volunteers in a driving simulator-based study. Their respiratory activity was recorded using a wearable belt and their reaction time and vehicle lateral position were measured using tests developed on the driving simulator. To induce drowsiness, a monotonous driving environment was used. Different time domain features have been extracted from respiratory signals and combined with the reaction time and lateral position of the vehicle for modeling. The observer of rating drowsiness (ORD) scale was used to label the driver's actual states. The t-tests and Man-Whitney test was used to select only statistically significant features (p < 0.05), that can differentiate between the alert and drowsy states effectively. Significant features then combined to investigate the improvement in performance using the Multilayer Perceptron (MLP), the Support Vector Machines (SVMs), the Decision Trees (DTs), and the Long Short Term Memory (LSTM) classifiers. The models were implemented in Python library 3.6. RESULTS: The experimental results illustrate that the support vector machine classifier achieved accuracy of 88%, precision of 85%, recall of 83%, and F1 score of 84% using selected features. CONCLUSION: These results indicate the possibility of very accurate detection of driver drowsiness and a viable solution for a practical driver drowsiness system based on combined measurement using less-intrusive and out-of-vehicle recording methods.

Fatigue in transportation operations: A contextual factors survey among Iranian suburban drivers.

BACKGROUND: Fatigue, as a persistent and serious occupational hazard, plays an important role in traffic accidents by reducing the driver's ability to maneuver with the vehicle and increasing the likelihood of falling asleep at the wheel. OBJECTIVE: The purpose of this study was to identify the individual contextual factors, sleep condition, lifestyle, job characteristics, environmental, and economic conditions that affect the fatigue and alertness of Iranian suburban bus drivers. METHODS: A questionnaire-based cross-sectional survey was used for this study. Non-probability sampling was used to study 401 suburban bus drivers from Tehran province, Iran, ranging in age from 24 to 67 years. The SPSS22 statistical software V27 was used for the analysis. RESULTS: Approximately half of the participants (50.5%) had experienced fatigue while driving in the previous six months. According to a logistic regression analysis, the contextual factors were all independently related to falling asleep and fatigue while driving. CONCLUSION: This study provides a thorough understanding of the contextual factors related to drowsy driving and emphasizes the importance of taking these things into consideration when developing interventions aimed at improving the driver's wellbeing and health and lowering the risk of errors and accidents.

Translation, cross-cultural adaptation and validation of the Persian version of selected PROMIS measures for use in lumbar canal stenosis patients.

BACKGROUND: The National Institutes of Health (NIH) developed a new measurement system called the Patient-Reported Outcomes Measurement Information System (PROMIS) which can be used for multiple health conditions. The 29-item short form (PROMIS-29) with seven domains was more often used by clinical researchers to measure the physical function, mood and sleeping status of patients with low back pain (LBP). Translation of the PROMIS into multiple languages and adaptation of its application in different cultural diversities can help to further standardize clinical research studies and make them comparable to each other. This study aimed to cross-culturally adapt the PROMIS-29 into Persian (P-PROMIS-29) and evaluate the construct validity and reliability of the translated questionnaire among patients with lumbar canal stenosis. MATERIALS AND METHODS: The translation was conducted by using the multilingual translation methodology guideline. Construct validity, internal consistency, and test-retest reliability at a two-week interval for the P-PROMIS-29 were calculated. Construct validity was assessed by calculating correlations between the P-PROMIS-29 with Oswestry Disability Index (ODI) and Roland-Morris results. RESULTS: The study sample included 70 participants with lumbar canal stenosis. Internal consistencies were moderate to good with Cronbach's alpha ranging from 0.2 to 0.94. The test-retest reliability evaluation was excellent with intraclass correlation coefficients (ICCs) ranging from 0.885 to 0.986. Construct validity of different domains of P-PROMIS-29 were moderate to good, with Pearson's correlation coefficient results ranging from 0.223 to 0.749. CONCLUSION: Our results showed that P-PROMIS-29 is a valid and reliable measurement tool for evaluation of patients with lumbar canal stenosis.

Drivers' subjective perceptions of the contextual factors influencing fatigue: A qualitative study of suburban bus drivers in Iran.

BACKGROUND: Drivers' drowsiness is a significant issue globally known as a contributing factor to crashes in various transportation operations. Although there is evidence that suburban bus drivers experience drowsy driving, most previous studies are quantitative, which means that drivers experiencing drowsiness have not had the opportunity to explain their direct views and thoughts. OBJECTIVES: This qualitative exploratory study subjectively investigates the contextual factors influencing fatigue among suburban bus drivers. METHODS: Collecting data was conducted through 14 in-depth interviews with suburban bus drivers working in Tehran province's transportation system, Iran. The interview recording was transcribed by the research team and entered into the qualitative data analysis software. Two independent coders with qualitative content analysis and thematic analysis approach analyzed transcripts. RESULTS: Four themes emerged, including human factors (with categories of individual characteristic and lifestyle), vehicle factors (with categories of design and performance), job factors (with categories of task requirement, quantity and quality of sleep, and circadian rhythm,) and environmental factors (with categories of the physical and economic environment). We found a more significant number of codes and categories and thus more contextual factors associated with job factors. The participants emphasized the importance of sleep deprivation, long driving hours, and even time of the day as factors influencing fatigue. CONCLUSIONS: The study results can provide beneficial information for both ergonomists and car manufacturers in developing more accurate fatigue detection models and effective educational and technical interventions to maintain road user's health and reduce road accidents and mortality rates due to drowsiness.

Exploring individual factors influencing human reliability among control room operators: a qualitative study.

Identifying the individual factors is a major issue in determining the likelihood of human error and ultimately human reliability. In current human reliability assessment methods, this is determined based on a list of performance shaping factors and experts' judgment. This was a qualitative content analysis study, in which the participants were selected using purposive sampling from combined cycle power plant control rooms. Semi-structured interviews were performed and collected data were analyzed. A total of 32 operators (20 module controllers, eight head operators and four managers) were interviewed. Five categories were extracted, namely 'mental condition', 'consciousness at work', 'professional competence', 'communication skills' and 'quick reactions and decision-making capabilities'. Accordingly, it is suggested to taken into account such factors as professional competence and speed of reactions and to pay more attention to their important factors in the reliability of operators in combined cycle power plant control rooms.

Design and ergonomic assessment of a passive head/neck supporting exoskeleton for overhead work use.

Overhead work is an important risk factor associated with musculoskeletal disorders of the neck and shoulder region. This study aimed to propose and evaluate a passive head/neck supporting exoskeleton (HNSE) as a potential ergonomic intervention for overhead work applications. Fourteen male participants were asked to perform a simulated overhead task of fastening/unfastening nut in 4 randomized sessions, characterized by two variables: neck extension angle (40% and 80% of neck maximum range of motion) and exoskeleton condition (wearing and not wearing the HNSE). Using the HNSE, significantly alleviated perceived discomfort in the neck (p-value = 0.009), right shoulder (p-value = 0.05) and left shoulder (p-value = 0.02) and reduced electromyographic activity of the right (p-value = 0.005) and left (p-value = 0.01) sternocleidomastoid muscles. However, utilizing the exoskeleton caused a remarkable increase in right (p-value = 0.04) and left (p-value = 0.05) trapezius electromyographic activities. Performance was not significantly affected by the HNSE. Although the HNSE had promising effects with respect to discomfort and muscular activity in the static overhead task, future work is still needed to investigate its effect on performance and to provide support for the generalizability of study results.

Setting research priorities to achieve long-term national road safety goals in Iran.

Background: Road traffic crashes (RTCs) and its associated injuries are one of the most important public health problems in the world. In Iran, RTCs rank second in terms of mortality. To address this issue, there is a need for research-based interventions. Prioritizing researches using a variety of approaches and frameworks to determine the most effective interventions is a key nodal point in the RTCs' research policy planning cycle. Thus, this study aims to generate and prioritize research questions in the field of RTCs in Iran. Methods: By adapting the Child Health and Nutrition Research Initiative (CHNRI) method, this study engaged 25 prominent Iranian academic leaders having role in setting Iran's long-term road safety goals, a group of research funders, and policymakers. The experts' proposed research questions were independently scored on a set of criteria: feasibility, impact on health, impact on the economy, capacity building, and equity. Following the prioritization of Research Questions (RQs), they were all classified using the 5 Pillar frameworks. Results: In total, 145 Research Questions were systematically scored by experts against five criteria. Iran's top 20 road traffic safety priorities were established. The RQs related to "road safety management" and "road and infrastructure" achieved a high frequency. Conclusions: The top 20 research questions in the area of RTCs in Iran were determined by experts. The majority of these RQs were related to "road safety management". The results of this study may contribute to the optimal use of resources in achieving long-term goals in the prevention and control of road traffic crashes and its related injuries. Considering these RQs as research investment options will improve the current status of Road Traffic Injuries (RTIs) at a national level and further advance toward compliance with international goals. If these research priorities are addressed, and their findings are implemented, we can anticipate a significant reduction in the number of crashes, injuries, and deaths.

Effect of neck posture on cervicothoracic loads in overhead crane operators.

Awkward neck postures are commonly documented to be associated with an increased risk of neck disorders. This study intended to continuously monitor and evaluate neck postures and to estimate the cervicothoracic loads among overhead crane operators during work time. Neck postures were measured among 40 randomly selected operators by an inclinometer during 2 h of work time. To determine the tasks and adapt the posture recordings to each of their corresponding tasks, direct observation was conducted concurrently. The median neck flexion and lateral bend angles were 28.23° and 11.30°, respectively. The mean compression and shear loads on the neck ranged from 75.22 to 113.14 N and from 9.50 to 41.11 N, respectively. The results indicated substantial levels of exposure to awkward and extreme neck postures among the operators. The nature of the operators' work and the visual requirements of some tasks will increase the mechanical loads on the neck.

Determining the interactions between postural variability structure and discomfort development using nonlinear analysis techniques during prolonged standing work.

PURPOSE: Nonlinear analysis techniques provide a powerful approach to explore dynamics of posture-related time-varying signals. The aim of this study was to investigate the fundamental interactions between postural variability structure and discomfort development during prolonged standing. METHODS: Twenty participants, with equal distribution for gender and standing work experience (SWE), completed a simulated long-term standing test. Low back and legs discomfort, center of pressure, lumbar curvature, and EMG activity of trunk and leg muscles were monitored. Nonlinear measures including largest lyapunov exponent, multi-scale entropy, and detrended fluctuation analysis were applied to characterize the variability structure (i.e., complexity) in each signal. The size (i.e., amount) of variability was also computed using traditional linear metrics. RESULTS: With progress of low back and legs discomfort over standing periods, significant lower levels were perceived by the participants having SWE. The amount of variability in all signals (except external oblique EMG activity) were significantly increased with the time progress for all participants. The structure of variability in most signals demonstrated a lower complexity (more regularity) with fractal properties that deviated from 1/f noise. The SWE group showed a higher complexity levels. CONCLUSIONS: Overall, the findings verified variations in structure and amount of the postural variability. However, nonlinear analysis identified postural strategies according to the perceived discomfort in a different way. These results provide supports for future application of nonlinear tools in evaluating standing tasks and related ergonomics interventions as it allows further insight into how discomfort development impact the structure of postural changes.

Head forward flexion, lateral bending and viewing distance in smartphone users: A comparison between sitting and standing postures.

BACKGROUND: Smartphones (SPs) are widely used by people of all age groups and genders. Users spend many hours per day on the SPs for different purposes, which imposes significant stress on their musculoskeletal system. OBJECTIVES: This study explored head forward flexion, lateral bending angle, and viewing distance while working with a SP in sitting/standing postures and one-handed/two-handed grips. The users' performance as well as pain development were also investigated. METHODS: Participants answered a questionnaire on pain experience before and after SP usage. Neck kinematics of 20 SP users were monitored by a motion analysis system while doing three tasks (typing, video watching, and reading) in sitting and standing postures. Performance was evaluated by number of typed words, amount of errors in typing, and total read words. RESULTS: The results indicated a significant increase in pain complaints in neck and upper limbs after test completion. Working with SPs in sitting and standing postures were, respectively, associated with greater head forward flexion for watching and viewing distance for two-handed typing tasks. Higher left lateral bending values were measured for one-handed watching and reading tasks in standing posture. The performance measures were superior for two-handed grips in all conditions. CONCLUSIONS: Overall, using SPs in sitting posture creates greater head forward flexion and lower lateral bending angles in all tasks and grip types. The findings of this study can be used to provide recommendations for SP users.

Identifying factors influencing cardiac care nurses' work ability within the framework of the SEIPS model.

BACKGROUND: Due to their physically and mentally demanding job, nurses are exposed to high risk of fatigue and musculoskeletal disorders, through which their work ability could be adversely affected. OBJECTIVE: This study aims to identify factors influencing nurses' work ability by using a macroergonomic model. METHODS: Descriptive and qualitative analyses were carried out in two phases of the study. First, 41 nurses of the cardiac intensive care unit in a military hospital in Iran filled in the work ability questionnaire (WAI). In the second phase, in order to identify factors influencing work ability of the nurses, a semi-structural interview within the framework of the System Engineering Initiative for Patient Safety (SEIPS) model was conducted. Consequently, data were analysed and compared by multiple experts using directed content analysis method. RESULTS: The mean work ability of the nurses was 40.01±4.05 (good work ability). 22 themes were identified through the directed content analysis and they were classified in 5 categories of the SEIPS model including environment, tools and technology, task, person, and organization. CONCLUSIONS: Using a macroergonomic approach proved to be valuable in identifying factors influencing work ability of nurses. These factors should be considered by managers and HFE practitioners designing intervention programs to improve nurses' work ability.

Multi-dimensional model for determining the leading performance indicators of safety management systems.

BACKGROUND: Health and safety performance measurements aimed to provide information on the progress and current situation of organizational strategies and activities. OBJECTIVES: We developed a model to determine and select safety key performance indicators in order to assess safety management systems. METHODS: This study has been designed in six steps aiming at defining a model of leading performance indicators (LPIs) and selecting key performance indicators (KPIs) using the AHP method. RESULTS: According to the results analysis, 116 structural and operational indicators were defined based on the components of the OHSAS 18001 management system. For this purpose, 19 structural, 27 operational and 33 active KPIs were selected by AHP and BN techniques. CONCLUSION: Development of LPIs is influenced by various organizational, managerial, and operational factors. LPIs extracted from the components of the OHS-MS deployed in an organization are often passive and cannot show the changes in the safety status of a workplace in a short period. The model presented in this study was designed with an emphasis on extraction of active and operational indicators, as they were capable of detecting performance changes in construction industries.

Design and ergonomic assessment of an infusion set connector tool used in nursing work.

Nursing is a physically demanding job characterized by a high prevalence of fatigue and musculoskeletal disorders. One of the high-exertion and repetitive nursing tasks is the manual connection of an infusion set to a medical fluid bottle. Such physical work can be eased by the design of new hand tools. Correspondingly, this study designed and ergonomically assessed an infusion set connector tool (ISCT) and compared it with that of manual connection. First, a prototype of ISCT was designed to perform infusion set connecting task in the mechanical form. Subsequently, 12 nurses were asked to connect an infusion set to medical bottle in the form of manual and mechanical tasks and these tasks were evaluated using ergonomic indices including muscular activity level, force, posture, and subjective (Borg scale CR10) measures. Results showed that the activity levels (root mean square) of the extensor digitorum communis, flexor carpi radialis, biceps, triceps, and deltoid muscles remarkably decreased when the nurses used the ISCT. The postures of the wrist, arm, and shoulder regions were corrected from Rapid Upper Limb Assessment action level 3 to 2 when the designed tool was used. Additionally, the subjective perception of exertion was significantly lower with the use of the prototype.