Manual Lifting Tasks Research Articles

Development of a wireless smart sensor system and case study on lifting risk assessment

With the widespread adoption of Industry 4.0 and smart manufacturing concepts across industries, sensor development, system integration, and data analysis have become important aspects of efficient manufacturing operations. In addition to monitoring the performance of machines, significant importance is given to human condition monitoring in factories, using body-worn sensors to ensure the well-being of workers and for injury prevention. This research presents the development of a body-worn sensor system capable of sampling acceleration and rotation data up to 400 Hz and wirelessly transmitting the data over Bluetooth Low Energy (BLE). Further, the communication protocols for data acquisition, data communication within the device, Real Time Operating System (RTOS) programming, and multi-threading are described. This system is designed in such a way that multiple devices can be connected to the Data acquisition (DAQ) system simultaneously, and data is collected from the sensors in a synchronized manner. This information is valuable for the wider adoption of sensor systems for human condition monitoring in industry. Lastly, to test the system’s capabilities, a case study of lifting risk assessment is presented, where data collected from the accelerometer and gyroscope are used to determine a relative estimate of the physical stress associated with a manual lifting task by using different machine learning (ML) algorithms. The case study highlights how sensor placement, feature extraction, and sensor types influence machine learning models. As the sensor system can perform computations on the edge, a framework to carry out real-time lifting risk assessment using lightweight algorithms and the most important data features is proposed.

Assessing the accuracy of a wireless sensor system for estimating lumbar moments during manual lifting tasks considering the effects of load weight, asymmetry, and height

This study assessed the accuracy of L5/S1 moment estimates calculated with an Inertial Motion Capture (IMC) system during an asymmetrical and variable height lifting task. The effects of load weight, asymmetry, and lifting height on estimates of lumbar moment have not been comprehensively considered in studies using IMC systems. Thirty-six participants engaged in tasks involving three loads, lifting heights, and trunk rotation angles. Lumbar moments were calculated using bottom-up and top-down biomechanical models. Gold-standard Optical Motion Capture (OMC) and Force Plates (FP) were used as the reference. A randomized block partially confounded design was used to compare the root mean square errors (RMSE) between the IMC and OMC-based reference estimates. The IMC system's estimated peak moments were 12%–13% lower than those estimated using the gold standard OMC-BU inverse dynamics, while the RMSE varied between 19 and 21 Nm. A Load*Height interaction was found; a trend was identified where the RMSE values increased as both the load and height levels increased. The angle did not show a significant effect on any of the tested scenarios. A close correspondence between the IMC and OMC-based moment estimates was established, with the load being the main factor affecting the differences between systems. The IMC system shows potential for use in occupational settings to capture data on the lumbar moments of workers, which could be utilized to assess ergonomic risk.

Analysis and study on biomarkers of local muscle fatigue caused by repetitive lifting task

BackgroundWork-related musculoskeletal disorders (WMSDs) show a rapid growth trend. It has brought a huge economic burden to the society and become a serious occupational health problem that needs to be solved urgently. This study aimed to analyze the local muscle response under continuous ergonomic load, screen sensitive fatigue-related biomarkers and provide data support for the early prevention of local muscle damage and the exploration of early warning indicators.MethodsThirteen male college student volunteers were recruited to perform simulated repetitive manual lifting tasks in the laboratory. The lifting task was designed for 4 periods which lasted for 12 min in each, and then paused for 3 min for sampling. Local muscle fatigue is assesed by the Rating of perceived exertion (RPE) and the Joint analysis of sEMG spectrum and amplitude (JASA). Elbow venous blood was collected and 14 kinds of biomarkers were analyzed, which included Metabolic markers Ammonia (AMM), Lactic acid (LAC), Creatine kinase (CK), Lactate dehydrogenase (LDH), Cartilage oligomeric matrix protein (COMP), C-telopeptide of collagen I and II (CTX-I, CTX-II) and Calcium ion (Ca2+); Oxidative stress marker Glutathione (GSH); Inflammatory markers C-reaction protein (CRP), Prostaglandin E2 (PG-E2), Interleukin-6 (IL-6) and Tumor necrosis factor α (TNF-α); Pain marker Neuropeptide Y (NPY). Repeated measures analysis of variance (Repeated ANOVA), linear regression analysis, t-test and spearman correlation analysis were used to analyze the data.ResultsBoth subjective and objective fatigue appeared at the same period. Serum AMM, LAC, CK, LDH, COMP, CTX-II, Ca2+ and NPY after fatigue were significantly higher than those before fatigue (p < 0.05). There was a certain degree of correlation between the markers with statistical differences before and after fatigue.ConclusionsMetabolic markers (serum AMM, LAC, CK, LDH, COMP, CTX-II, Ca2+) and pain markers (serum NPY) can reflect local muscle fatigue to a certain extent in repetitive manual lifting tasks. It is necessary to further expand the research on fatigue-related biomarkers in different types of subjects and jobs in the future.

Estimating Compressive and Shear Forces at L5-S1: Exploring the Effects of Load Weight, Asymmetry, and Height Using Optical and Inertial Motion Capture Systems.

This study assesses the agreement of compressive and shear force estimates at the L5-S1 joint using inertial motion capture (IMC) within a musculoskeletal simulation model during manual lifting tasks, compared against a top-down optical motion capture (OMC)-based model. Thirty-six participants completed lifting and lowering tasks while wearing a modified Plug-in Gait marker set for the OMC and a full-body IMC set-up consisting of 17 sensors. The study focused on tasks with variable load weights, lifting heights, and trunk rotation angles. It was found that the IMC system consistently underestimated the compressive forces by an average of 34% (975.16 N) and the shear forces by 30% (291.77 N) compared with the OMC system. A critical observation was the discrepancy in joint angle measurements, particularly in trunk flexion, where the IMC-based model underestimated the angles by 10.92-11.19 degrees on average, with the extremes reaching up to 28 degrees. This underestimation was more pronounced in tasks involving greater flexion, notably impacting the force estimates. Additionally, this study highlights significant differences in the distance from the spine to the box during these tasks. On average, the IMC system showed an 8 cm shorter distance on the X axis and a 12-13 cm shorter distance on the Z axis during lifting and lowering, respectively, indicating a consistent underestimation of the segment length compared with the OMC system. These discrepancies in the joint angles and distances suggest potential limitations of the IMC system's sensor placement and model scaling. The load weight emerged as the most significant factor affecting force estimates, particularly at lower lifting heights, which involved more pronounced flexion movements. This study concludes that while the IMC system offers utility in ergonomic assessments, sensor placement and anthropometric modeling accuracy enhancements are imperative for more reliable force and kinematic estimations in occupational settings.

Ergonomic Risk Assessment and Fatigue Analysis During Manual Lifting Tasks in Farming Activities

Introduction: Farming is a physically demanding occupation that puts farmers at risk of musculoskeletal disorders, particularly when frequently performing activities like heavy lifting, which strains the lower back muscles. The present study aimed to assess the ergonomic risk and fatigue during manual lifting tasks pertaining to farming activities. Methods: A study was performed on 20 farmers to analyze the ergonomic risks associated with load lifting through the estimation of the Recommended Weight Limit and Lifting Index using the revised NIOSH lifting equation. The low back compression forces of the participants were estimated using the 3DSSPP software. Surface electromyography was employed to analyze the onset of muscle fatigue during the lifting activity. Results: The results of the study showed a 111.12% increase in the recommended weight limit, a 52.77% reduction in lifting index, and a 28.15% reduction in the low back compression forces for the redesigned lifting technique. The average low-back compression force for the redesigned technique was observed to be well below the back compression design limit of 770 lb. A reduction in the slope of the RMS voltage regression line by 60% and a reduction of 50.23% in the peak spectral power of the sEMG signal, accompanied by a shift in the peak spectral power towards higher frequency region indicated delayed onset of fatigue for the redesigned technique. Conclusion: The outcomes of the study indicated that the ergonomic redesign of the lifting task could significantly reduce the lifting index and alleviate the spinal compression forces well within the back-compression design limit. The redesign was also found to delay the onset of fatigue in the erector spinae muscles.

Dynamic assessment for low back-support exoskeletons during manual handling tasks.

Exoskeletons can protect users' lumbar spine and reduce the risk of low back injury during manual lifting tasks. Although many exoskeletons have been developed, their adoptability is limited by their task- and movement-specific effects on reducing burden. Many studies have evaluated the safety and effectiveness of an exoskeleton using the peak/mean values of biomechanical variables, whereas the performance of the exoskeleton at other time points of the movement has not been investigated in detail. A functional analysis, which presents discrete time-series data as continuous functions, makes it possible to highlight the features of the movement waveform and determine the difference in each variable at each time point. This study investigated an assessment method for exoskeletons based on functional ANOVA, which made it possible to quantify the differences in the biomechanical variables throughout the movement when using an exoskeleton. Additionally, we developed a method based on the interpolation technique to estimate the assistive torque of an exoskeleton. Ten men lifted a 10-kg box under symmetric and asymmetric conditions five times each. Lumbar load was significantly reduced during all phases (flexion, lifting, and laying) under both conditions. Additionally, reductions in kinematic variables were observed, indicating the exoskeleton's impact on motion restrictions. Moreover, the overlap F-ratio curves of the lumbar load and kinematic variables imply that exoskeletons reduce the lumbar load by restricting the kinematic variables. The results suggested that at smaller trunk angles (<25°), an exoskeleton neither significantly reduces the lumbar load nor restricts trunk movement. Our findings will help increasing exoskeleton safety and designing effective products for reducing lumbar injury risks.

The effect of back muscle fatigue on EMG and kinematics based estimation of low-back loads and active moments during manual lifting tasks

This study investigated the effects of back muscle fatigue on the estimation of low-back loads and active low-back moments during lifting, using an EMG and kinematics based model calibrated with data from an unfatigued state. Fourteen participants performed lifting tasks in unfatigued and fatigued states. Fatigue was induced through semi-static forward bending. EMG, kinematics, and ground reaction forces were measured, and low-back loads were estimated using inverse dynamics and EMG-driven muscle model. A regression model was developed using data from a set of calibration lifts, and its accuracy was evaluated for unfatigued and fatigued lifts. During the fatigue-inducing task, the EMG amplitude increased by 2.8 %MVC, representing a 38% increase relative to the initial value. However, during the fatigued lifts, the peak EMG amplitude was found to be 1.6 %MVC higher than that observed during the unfatigued lifts, representing a mere 4% increase relative to the baseline unfatigued peak EMG amplitude. Kinematics and low-back load estimates remained unaffected. Regression model estimation errors remained unaffected for 5 kg lifts, but increased by no more than 5% of the peak active low-back moment for 15 kg lifts. We conclude that the regression-based estimation quality of active low-back moments can be maintained during periods of muscle fatigue, although errors may slightly increase for heavier loads.

The effect of clinically elevated body mass index on physiological stress during manual lifting activities.

Individuals with a body mass index (BMI) classified as obesity constitute 27.7% of U.S. workers. These individuals are more likely to experience work-related injuries. However, ergonomists still design work tasks based on the general population and normal body weight. This is particularly true for manual lifting tasks and the calculation of recommended weight limits (RWL) as per National Institute of Occupational Safety & Health (NIOSH) guidelines. This study investigates the effects of BMI on indicators of physiological stress. It was hypothesized that, for clinically elevated BMI individuals, repeated manual lifting at RWL would produce physiological stress above safety limits. A repetitive box lifting task was designed to measure metabolic parameters: volume of carbon dioxide (VCO2) and oxygen (VO2), respiratory exchange ratio (RER), heart rate (HR), and energy expenditure rate (EER). A two-way ANOVA compared metabolic variables with BMI classification and gender, and linear regressions investigated BMI correlations. Results showed that BMI classification represented a significant effect for four parameters: VCO2 (p < 0.001), VO2 (p < 0.001), HR (p = 0.012), and EER (p < 0.001). In contrast, gender only had a significant effect on VO2 (p = 0.014) and EER (p = 0.017). Furthermore, significant positive relationships were found between BMI and VCO2 (R2 = 59.65%, p < 0.001), VO2 (R2 = 45.01%, p < 0.001), HR (R2 = 21.86%, p = 0.009), and EER (R2 = 50.83%, p < 0.001). Importantly, 80% of obese subjects exceeded the EER safety limit of 4.7 kcal/min indicated by NIOSH. Indicators of physiological stress are increased in clinically elevated BMI groups and appear capable of putting these individuals at increased risk for workplace injury.

Machine Learning for Detection and Risk Assessment of Lifting Action

Repetitive occupational lifting has been shown to create an increased risk for incidence of back pain. Ergonomic workstations that promote proper lifting technique can reduce risk, but it is difficult to assess the workstations without constant risk monitoring. Machine learning systems using inertial measurement unit (IMU) data have been successful in various human activity recognition (HAR) applications, but limited work has been done regarding tasks for which it is difficult to collect significant amounts of data, such as manual lifting tasks. In this article, we discuss why traditional methods of data expansion may fail to improve performance on IMU data, and we present a machine learning system capable of detecting lifting action for assessing the risk for back pain using a relatively small amount of data. The proposed models outperform baseline HAR models and function on raw time-series data with minimal preprocessing for efficient real-time application.

Assessment of the adecuacy of KIM-LHC method in assessing the risk level based on biomechanical loads for manual lifting tasks: A laboratory study

Introduction: Manual Material handling includes activities in which pushing, pulling, lifting, lowering, carrying, and holding the load, the most common of which is lifting. This study aimed to evaluate the reliability of the KIM-LHC method to identify high-risk manual load lifting tasks.&#x0D; Material and Methods: This cross-sectional study was performed on healthy male workers with a history of manual material handling in a laboratory setting. The sample size was determined according to previous studies of 15 people. The participants were required to perform 25 tasks with four iterations randomly. An inclinometer device was used to determine the forward bending angle at the waist. Compression loads exerted on L5/S1 were estimated using 3DSSPP software using participants' postural and anthropometric information. Also, the tasks were evaluated using the KIM-LHC method, and their final scores and levels of MSD risks were determined. Data were analyzed using SPSS.20 software and the Chi-square test.&#x0D; Results: The results of compression load estimation for lifting tasks showed that 92% of the tasks had a low-risk level (less than 3400 N), and 8% of the tasks had a medium-risk level (3400 to 6800 N). While the results of the KIM-LHC method showed that 28% of tasks had a low-risk level, 64% had a medium level, and 8% had a high-risk level. &#x0D; Conclusion: The results of this study showed no correlation between the risk levels of the KIM-LHC method and the estimated compression load for some designed lifting tasks. Therefore, there is a possibility of error in estimating the risk level of some lifting tasks by the KIM-LHC method, and more biomechanical studies should be performed on kinetics and kinematics.

Analysis of the Manual Lifting of Loads in Operators: Evaluation of Efforts

This article presents the results of the evaluations of the mechanical stresses associated with the performance of manual lifting tasks of loads and those operators must endure in their workplaces, considering these the most recurrent cases and positions. This study is based on a static analysis of certainspecific positions of the human body, the transmission of forces through the musculoskeletal structure, and the generation of efforts at critical points of the body. In addition to this, it is considered a revision of the criteria of the Spanish Technical Standard NTP-477. There are critical points of the musculoskeletal structure that support considerable efforts, the recommendations and criteria provided by the NTP-477 are relevant and although limited, provide an adequate margin of safety to avoid injury to workers.

Ergonomics Evaluation of Manual Lifting Task on Biomechanical Stress in Symmetric Posture

Introduction: Manual lifting operations continue to play a key role in the industrial and service sectors, inflicting physical strain on the musculoskeletal system, despite advances in automation. As a result, an experiment is carried out to assess the impact of two lifting task parameters; weight and height, based on the estimation of subjective responses and biomechanical loading, while lifting the weight symmetrically in the sagittal plane. Also to recommend the safe limit for manual lifting tasks. Methods: Twelve volunteer male students in the age group of 21 to 26 years performed lifting tasks from floor to 5 different heights (below the knee to ear level), with 5 different weights (10 to 20 kg) using free-style lifting techniques. The load pan with no handle was used for lifting weight, which is typically adopted in the Indian building construction field. The subjective estimate was obtained using workload assessment by body discomfort chart. The biomechanical loading (loading rate) for each lifted weight and height was collected using a force platform. Results: The results showed that heavier weights produced higher stresses than lower weights. The loading rate was found to be almost similar at waist or knee level. The loading rate was observed to be linearly increasing after waist level. The overall workload rating seems to be a good correlate with the mean loading rate to some extent. Conclusion: It is proposed to keep the maximum acceptable lifting weight from floor to knee, up to the ear level is 15 kg, to prevent any musculoskeletal or chronic injury.

Characterization of Occupational Lifting Patterns with Exposure Variation Analysis. Cross-sectional Workplace Study among Blue-Collar Workers.

To investigate and characterize the influence of sex, age, muscle strength, and cardiovascular fitness on manual lifting patterns using exposure variation analysis (EVA) during a full working day among blue-collar workers. Muscular activity (surface electromyography [sEMG]) of the thigh, low-back, and shoulder was measured throughout the working day in 173 employees with manual lifting tasks from 14 workplaces. Relative sEMG loading was expressed as % of maximal voluntary contraction (MVC). As an additional and more practically oriented analysis, calibration of load from standardized box lifts (5, 10, 20, and 30 kg) identified corresponding sEMG values in kg. Using an EVA 'lifting periods' of [1 to 5, >5 to 10, >10 to 20, >20 to 30, and >30] kg in time intervals [0 to 0.5, >0.5 to 1, >1 to 2, >2 to 5, >5 to 10, and >10] s were identified. Arm elevation and back inclination were measured using accelerometers. Females and older workers (≥50 years) primarily used the thighs for lifting and were exposed to more frequent thigh muscle 'lifting periods' of varying duration and load and performed more thigh lifts >30 kg and >60% of MVC compared with males and younger workers (P < 0.05). Females had less brief shoulder lifting periods and more work with bent back >30° than the males (P < 0.05), whereas stronger workers performed more work with elevated arm >60° and >90° than workers with low muscle strength (P < 0.05). However, besides a single difference where workers with lower cardiovascular fitness were exposed to more light (1-5 kg) and moderate duration (5-10 s) trapezius loading, the number of lifting periods was not affected by muscle strength nor cardiovascular fitness (P > 0.05). This EVA demonstrated sex- and age-related differences in exposure to lifting periods involving shoulder and thigh muscles.

A comparison of augmented feedback and didactic training approaches to reduce spine motion during occupational lifting tasks

Manual handling training may be improved if it relied on the provision of individualized, augmented feedback about key movement features. The purpose of this study was to compare the reduction in sagittal spine motion during manual lifting tasks following two training approaches: didactic (DID) and augmented feedback (AUG). Untrained participants (n = 26) completed lifting tests (box, medication bag, and paramedic backboard) and a randomly-assigned intervention involving 50 practice box lifts. Lifting tests were performed immediately before and after training, and one-week after interventions. Both groups exhibited reductions in spine motions immediately and one-week after the interventions. However, the AUG intervention group elicited significantly greater reductions in 5 of 12 between-group comparisons (3 tasks × 4 spine motion variables). The results of the current study support the use of augmented feedback-based approaches to manual handling training over education-based approaches.

Validation of a Wireless Sensor System for the Estimation of Cumulative Lumbar Loads in Occupational Settings

This study aimed to evaluate the accuracy of 3D L5/S1 moment estimates from a wearable inertial motioncapture system during manual lifting tasks. Reference L5/S1 moments were calculated using inversedynamics bottom-up and top-down laboratory models, based on the data from a measurement systemcomprising optical motion capture and force plates. Nine groups of four subjects performed tasks consistingof lifting and lowering 10 lbs. load with three different heights and asymmetry angles. As a measure ofsystem performance, the root means square errors and absolute peak errors between models werecompared. Also, repeated measures analyses of variance were calculated comparing the means and theabsolute peaks of the estimated moments. The results suggest that most of the estimates obtained from thewireless sensor system are in close correspondence when comparing the means, and more variability isobserved when comparing peak values to other models calculating estimates of L5/S1 moments.

척추부하 평가를 위한 L4-L5 요추의 유한요소모델 개발

Low back injury (LBI) often occurs during manual materials handling (MMH). Intradiscal pressure (IDP) is used to assess the risk of the LBI and is measured in vivo or by computer simulation. As for computer simulation, motion analysis and finite element (FE) analysis are usually employed. In this study, a FE model has been developed for L4-L5 segment with high risk of injury to predict LBI during manual lifting tasks. The FE model was composed of lumbar vertebrae, discs, and ligaments and a calibration process was performed to set the nonlinear material properties of the intervertebral disc. To validate the developed FE model, IDP and range of motion (ROM) under in vitro loading conditions were compared to the experiments and other FE studies in literature. Within in vitro range, IDP and ROM from the FE model were in agreement with results from previous studies. The FE model developed in this study can be scaled according to the subject used in the analysis integrating FE analysis to motion analysis, and is expected to be used in future work to estimate IDP and stress/strain in joint structures during occupational activities.

A Study on Factors Affecting the Manual Material Handling Capacity of Indian Male Construction Workers

Construction is one of the most hazardous industries involving high manual labour where health and safety risks are plentiful. This study focuses on evaluating the factors affecting the material lifting capacity of Indian male construction workers. A statistical experiment was conducted on selected male construction workers, and ANOVA technique was used to analyse the influence of parameters (like age, body mass index (BMI), material lifting height and lifting frequency) on maximum allowable weight limit (MAWL). From the analysis, maximum allowable weight limit (MAWL) and minimum lifting weight were determined for every worker based on his age and BMI corresponding to three different lift frequencies and lifting heights. The results indicate that for all BMI categories, the MAWL increases with the increase in the age of workers to a certain extent, but it decreases as the age increases. Using the maximum and minimum lifting weight values obtained, it will be easy to assign manual lifting tasks for workers without compromising their health at the same time ensuring optimum utilization of their efficiency.

Psychophysiological responses to manual lifting of unknown loads.

BackgroundThe handling of unknown weights, which is common in daily routines either at work or during leisure time, is suspected to be highly associated with the incidence of low back pain (LBP).ObjectivesTo investigate the effects of knowledge and magnitude of a load (to be lifted) on brain responses, autonomic nervous activity, and trapezius and erector spinae muscle activity.MethodsA randomized, within-subjects experiment involving manual lifting was conducted, wherein 10 participants lifted three different weights (1.1, 5, and 15 kg) under two conditions: either having or not having prior knowledge of the weight to be lifted.ResultsThe results revealed that the lifting of unknown weights caused increased average heart rate and percentage of maximum voluntary contraction (%MVC) but decreased average inter-beat interval, very-low-frequency power, low-frequency power, and low-frequency/high-frequency ratio. Regardless of the weight magnitude, lifting of unknown weights was associated with smaller theta activities in the power spectrum density (PSD) of the central region, smaller alpha activities in the PSD of the frontal region, and smaller beta activities in the PSDs of both the frontal and central regions. Moreover, smaller alpha and beta activities in the PSD of the parietal region were associated only with lifting of unknown lightweights.ConclusionsUncertainty regarding the weight to be lifted could be considered as a stress-adding variable that may increase the required physical demand to be sustained during manual lifting tasks. The findings of this study stress the importance of eliminating uncertainty associated with handling unknown weights, such as in the cases of handling patients and dispatching luggage. This can be achieved through preliminary self-sensing of the load to be lifted, or the cautious disclosure of the actual weight of manually lifted objects, for example, through clear labeling and/or a coding system.

The Risk Assessment of Low Back Pain Based on Allowable Weight Limits for Manual Lifting in Iranian Women Workers

Background: Manual load lifting is one of the most important risk factors for musculoskeletal disorders, including occupational low back pain. These disorders are common in women workers who perform manual load lifting and displacement tasks at the workplace. Objectives: To determine the level of musculoskeletal disorders and to evaluate the recommended limits of manual load lifting in women workers using WISHA checklist and ACGIH TLV, the recommended limits of Iran, and compare the results of two methods. Methods: This cross-sectional study was conducted on 100 women workers who performed manual loading tasks in 2018. Nordic questionnaire was used to determine the prevalence of musculoskeletal disorders, and two methods, WISHA checklist and ACGIH TLV, were used to determine the recommended allowable limits for manual load lifting. Results: The results of the prevalence assessment of musculoskeletal disorders showed that most of the musculoskeletal disorders were in the low back (55%) in the past 12 months. The results of the assessment of the allowable lifting limits also showed that 8% of women in the WISHA checklist method and 31% in the ACGIH TLV method were at risk for low back injuries. The kappa coefficient test (0.031) also showed that there is a poor and insignificant agreement between the two methods of WISHA checklist and ACGIH TLV in determining the allowable limits for manual lifting. Conclusions: The results of this study showed a poor agreement between the WISHA checklist and ACGIH TLV in determining the allowable limits for manual lifting, which suggest that the two methods are not mutually exclusive. Hence, owing to the increasing presence of women in various occupations and raising the hand load-lifting and, naturally increasing occupational low back pain among them, it is necessary that in a comprehensive study, the allowable limits of lifting loads according to anthropometric and physiological characteristics of Iranian women, prepare and compile according to a comprehensive instruction.

A safe human–robot interactive control structure with human arm movement detection for an upper-limb wearable robot used during lifting tasks

Manual lifting tasks involve repetitive raising, holding and stacking movements with heavy objects. These arm movements are notable risk factors for muscle pain, fatigue, and musculoskeletal disorders in workers. An upper-limb wearable robot, as a 6-DOF dual-arm exoskeleton, which was designed to augment workers’ strength and minimize muscular activation in the arm during repetitive lifting tasks. To adjust the robot joint trajectory, the user needs to apply an interactive torque to operate the robot during lifting tasks when a standard virtual mechanical impedance control structure is used. To reduce overshooting of the interactive torque on the user’s joint, a three-tier hierarchical control structure was developed for the robot in this study. At the highest level, a human arm movement detection module is used to detect the user’s arm motion according to the surface electromyography signals. Then, a Hammerstein adaptive virtual mechanical impedance controller is used at the middle level to reduce overshooting and yield an acceptable value of torque for the user’s elbow joint in actual lifting tasks. At the lowest level, the actuator controller on each joint of the robot controls the robot to complete lifting tasks. Several experiments were conducted, and the results showed that the interactive torque on the user’s elbow was limited and the muscular activations of erector spinae and biceps brachii muscles were effectively decreased. The proposed scheme prevents potential harm to the user due to excessive interactive torque on the human elbow joint, such as related muscle fatigue and joint injuries.