Back Support Research Articles

Prevalence of low back pain and associated factors among medical students in Wachemo University Southern Ethiopia

Low back pain(LBP) is the most common musculoskeletal disorder in adults. According to previous studies medical students were found vulnerable for the development of LBP. We assessed the prevalence of LBP and associated factors among Medical students in Wachemo University, Southern Ethiopia. An institution-based cross-sectional study design and simple random sampling technique was employed to select 370 medical students. A structured pretested interviewer administered questionnaire was used to collect the data. The data were entered into Epi-info version 3.1 and analysed by SPSS version 25. Analytical and descriptive statistics were conducted. Simple and multiple logistic regression analyses were employed to assess factors associated with LBP. Variables at p-value ≤ 0.25 in simple logistic regression analysis were entered into multiple logistic regression. Statistical significance was declared at P-value, < 0.05 in multiple logistic analysis. The prevalence of low back pain among medical students was found to be 40.1%with 95% CI (38.5–41.8). Being male students [AOR (95% CI): 1.83 (1.09–3.08)], design of study sitting chairs without back support [adjusted odds ratio(AOR) (95% C.I): 2.81 (1.74–4.55)], stress during class [AOR (95% C.I): 2.60 (1.56–4.35)], and daily study hours greater than 6 h and above [AOR: 4.33, 95% CI (2.30–8.12)] had a significant association with LBP. The prevalence of LBP in this study is high. Better ergonomic facilities and psychosocial supports to medical students are recommended to reduce the effects of predisposing factors on LBP.

The effect of a soft active back support exosuit on trunk motion and thoracolumbar spine loading during squat and stoop lifts

Back support exosuits aim to reduce tissue demands and thereby risk of injury and pain. However, biomechanical analyses of soft active exosuit designs have been limited. The objective of this study was to evaluate the effect of a soft active back support exosuit on trunk motion and thoracolumbar spine loading in participants performing stoop and squat lifts of 6 and 10 kg crates, using participant-specific musculoskeletal models. The exosuit did not change overall trunk motion but affected lumbo-pelvic motion slightly, and reduced peak compressive and shear vertebral loads at some levels, although shear increased slightly at others. This study indicates that soft active exosuits have limited kinematic effects during lifting, and can reduce spinal loading depending on the vertebral level. These results support the hypothesis that a soft exosuit can assist without limiting trunk movement or negatively impacting skeletal loading and have implications for future design and ergonomic intervention efforts.

Lightweight structure and unequal length flexible support design of a 1.3×1.2 m rectangular, horizontally supported mirror

A lightweight rectangular mirror designed for a space telescope features a lightweight structure and an innovative unequal length flexible support design. This design incorporates a three-point back support structure, which maintains the surface accuracy of the mirror assembly in a horizontal optical testing layout. The topology optimization design method is applied for the lightweight design of a SiC mirror. According to the principle that optimal gravity surface accuracy of the mirror is achieved when the pivot center of the flexible support coincides with the neutral plane of the mirror, an unequal length flexible support scheme is proposed. Furthermore, a “neck-shrinking” flexible support structure is designed to enhance the comprehensive surface quality of the mirror assembly, achieving better than λ/140 (RMS = 4.5 nm, λ=632.8nm). Following the completion of mirror polishing, an optical test system is established. The test results confirm that the surface shape accuracy satisfies the requirements of the design index. In addition, the mechanical design has been corroborated through dynamic testing.

Impact of work and working conditions on chronic low back pain among fisher women: a cross sectional study in Trivandrum

Background: This study aimed to estimate the prevalence of chronic low back pain, its severity and associated factors among fisherwomen. Methods: Cross-sectional survey conducted among 336 fisherwomen aged 18-49 years from 7 fishing villages in Trivandrum. The prevalence of chronic low back pain estimated using Nordic body map. Pain severity was assessed using the pain numeric rating scale. Results: Prevalence of chronic low back pain was 45%. High BMI, UTI history, stress-induced headaches, falls, physical abuse, water-collection frequency, work-experience, and standing duration were associated with chronic low back pain. The pain severity prevalence was 23.8% mild, 51.65% moderate and 24.5% severe. Income, continuous-standing, improper-seating, and stipulated rest-time were associated with seventy of chronic low back pain. Standing continuously and improper seating were predictors of pain severity. Conclusions: Low back pain is common among fisherwomen contributed by work-related behavior. Posture correction measures such as educating the fisherwomen on appropriate posture and need for relaxation will improve their health conditions. Improved working environments which include proper resting place, designated space for vending with proper seating arrangement with chairs and with back support will improve the LBP status of fisherwomen.

Confinement strength prediction of corroded rectangular concrete columns using BP neural networks and support vector regression

The application of machine learning in predicting the mechanical performance of reinforced concrete columns subjected to reinforcement corrosion was investigated in this study. Traditional models, often relying on empirical formulas or simplified assumptions, are known to struggle in capturing all variables and relationships in complex problems, leading to inadequate prediction accuracy. Through theoretical analysis, the confinement effect of stirrups on core concrete and its performance deterioration caused by reinforcement corrosion were determined. To improve the prediction accuracy and generalization ability, the error Back Propagation Neural Network (BPNN) and Support Vector Regression (SVR) models were employed. Parameter effects in the BPNN model were interpreted using the SHapley Additive exPlanations (SHAP) and compared with traditional parameter sensitivity analyses. The investigation indicates that the machine learning models have a high degree of fit and low error levels, particularly within the training set. After analyzing using the SHAP approach, it is found that the corrosion ratio of the stirrup and longitudinal reinforcement have a significant effect on the confinement strength of the concrete, whereas the effects of the stirrup configuration and size effect are negligible, which is different from conventional parametric sensitivity analysis. As to the stability analysis of model predictions, the SVR model shows lower volatility and higher prediction stability compared with the BPNN model, despite the latter occasionally providing superior generalization ability. This research underscores the significant advantages offered by machine learning models in addressing longstanding challenges associated with strength prediction, and thus presents new perspectives for future study.

Predicting Perceived Back Fatigue During Exoskeleton Supported Trunk Bending Tasks using Machine Learning

Repetitive trunk flexion tasks performed over long durations can increase low-back injury risk, where Back Support Industrial Exoskeletons (BSIEs) can be beneficial. While BSIEs have shown effectiveness in lab assessments, real-world outcomes have shown variation based on task complexity, necessitating monitoring of physical demands. Fourteen participants performed repetitive trunk BSIE-assisted forward bending and return, without fatigue and then at medium-high fatigue. We recorded muscle activity in low-back and thigh muscles using Electromyography (EMG) and whole-body stability using force plates. Classification algorithms, namely, Support Vector Machine (SVM), Random Forest (RF), and XGBoost (XGB) were utilized to predict perceived medium-high back fatigue using sensor data. Highest performance was observed with XGB algorithm using data from a single low-back EMG sensor (Accuracy: 86.1%, Recall: 86%), and force plate (93.5, 94.1%). Outcomes of our study can be helpful in developing novel fatigue detection products, benefiting ergonomists in properly implementing BSIEs in industrial scenarios.

Pressed Solid Target Production of 89Zr and its Application for Antibody Labelling.

Zirconium-89 ( 89Zr, t1/2=3.27d) is an important + emitting radionuclide used in Positron Emission Tomography (PET) immuno studies due to its unique characteristics and increased demand due to simple and cost-effective production capacity. Production of 89Zr is achieved primarily through solid natural yttrium targets via different target preparation methodologies, such as electrodeposition, pressed foils, and spark plasma sintering. In this study, we have investigated the pressed solid target methodology. The Yttrium Oxide (Y2O3) powder was pressed to pellet form and stacked over a different back support plate, such as platinum (Pt), niobium (Nb), and tantalum (Ta). The target was irradiated with approximately 12 MeV proton beam for 10-60 minutes at 20µA current. The irradiated target was purified through a solid phase extraction method via hydroxamate-based resin by manual or automatic approach. The purified 89Zr was analyzed using gamma scintigraphy, and specific activity was calculated through Deferoxamine (DFO) chelation. 89Zr radionuclide via pressed target was effectively produced with a production yield of 20-30 MBq/µA.h, and the purification was achieved in 35 minutes with (87.46)% average recovery and >98% purity while using automated purification, but manual purification took 2 hours with (91 ± 2)% recovery and >98% purity. The production yield was comparable to the reported pressed target approach. Deferoxamine (DFO) chelation with 89Zr-oxalate was performed with purity >98% and specific activity of 25-30 µCi/mmol. In this study, we explored the production of 89Zr by pressed targets and purification via manual or automated methods with good radionuclide purity. The chelation with DFO or its analog was performed with good labeling efficiency and stability</p>.

Framework for the adoption, evaluation and impact of occupational Exoskeletons at different technology readiness levels: A systematic review

Work-related Musculoskeletal Disorders (WMSDs) are the most common occupational diseases caused by the prolonged performance of strenuous work, such as manual handling of loads or long-term maintenance of incongruous postures. Different safety protocols are implemented to reduce WMSDs and optimize the working environment, but one of the most promising solutions is using occupational exoskeletons (OEs). However, to truly acknowledge the benefits of OEs and be able to introduce them into daily business use, devices must pass several development and testing stages that determine the Technology Readiness Level (TRL). This review study aims to present an up-to-date collection of the most advanced assessments of exoskeletons for upper and back support, ranging from laboratory real-task simulations to operational scenarios in industrial sites. To identify relevant studies, we conducted comprehensive searches across different electronic databases, i.e., PubMed, Scopus, and Web of Science. Different keywords were used for the literature search, e.g., occupational exoskeleton, industrial exoskeleton, etc. Studies were included if they investigated the assessment of exoskeletons in the laboratory with real tasks or an industrial environment. We identified 45 research articles that fulfilled this selection criterion. Several features are compared and discussed in detail, such as industrial environment, experimental protocol, task performed, and exoskeleton typology. These data allowed us to formulate results that report the correspondence or discrepancy between the number of papers testing exoskeletons and WMSDs in different industrial sectors, the type of assessment performed, and the impact of exoskeletons on workers and industries at different TRLs. Among the results, the incidence of WMSDs in the manufacturing industry is 21.13%, while the adoption of exoskeletons in the same field is the highest with respect to the other industrial fields, at 44.45%. Electromyography (EMG) and Questionnaires were the most evaluated typologies across all development and testing stages (with an incidence of 64% across the selected articles). Additionally, an average reduction of EMG activity was reported, with 24% for Upper Limb and 20% for Back Support. Regarding the subjective assessment reported in the questionnaires, 68% of the studies reported a positive evaluation. Based on these outcomes, this work provides a framework for an effective evaluation process for the OEs to raise TRL with recommendations for future research activities.

The effect on back pain, anxiety, and comfort levels of an elevated supine position and back support applied to patients undergoing coronary angiography: A randomized controlled experimental study.

To determine the effect of elevated supine position with back support on back pain, anxiety and comfort in patients undergoing coronary angiography. This randomized-controlled, experimental study was conducted in the Coronary Intensive Care Unit between September 2021 and January 2022, with an intervention group of 51 patients and a control group of 53 patients. Data were collected using a patient information form, a visual analog scale, the anxiety state inventory and the immobilization comfort questionnaire. Following angiography, the intervention group received pillow support to the back and the bedhead was elevated to 30 degrees. Routine nursing care was applied to the control group. In both groups, the severity of back pain was measured at 0, 2, and 4 hours, and anxiety and comfort at 0 and 4 hours. The pain severity at 2 and 4 hours after the procedure was determined to be significantly lower in the intervention group than in the control group (p<0.001, p<0.001). At 4 hours, the anxiety levels were similar in both groups (p<0.05), and the comfort level was higher in the intervention group (p<0.001). The mean pain value was 6.003 points lower and the comfort level was 20.499 points higher in the intervention group than in the control group. The elevated supine position with back support was seen to reduce back pain, increase comfort, and did not change anxiety levels.Clinical Trials No: NCT05546216.

Experimental and data-driven prediction for the impact of free/bond lengths of element specimen on interface characterization of ground anchors

The performance of ground anchor often employed in retaining the stability of onshore structures depends largely on its interface shear behavior. Interface characterization using pullout tests on element specimens of ground anchor is a versatile approach for determining its interface shear behavior. This research combines laboratory experiments and data-driven modeling to investigate the effect of free/bond lengths as a critical configuration condition of element specimen on the interface characterization results of ground anchors. Machine Learning models such as back propagation neural network (BPNN), random forest (RF), and support vector regression (SVR) were employed. Moreover, the particle swarm optimization (PSO) algorithm was used to improve the process. The results indicate that variations in free/bond lengths have a negligible effect on the trends of interface bond curves when bond lengths reach 90–100 mm. Moreover, when the bond and free lengths are set to 80 mm and 20 mm, respectively, the configuration conditions of the element specimen have a limited effect on the average interface shear strength. The PSO-BPNN model provided the most accurate predictions, which closely followed the experimental results compared to RF and SVR models. Compared to the other models, it reached a greater correlation coefficient (0.9975) and a lower root-mean-square error (14.89 kPa). Moreover, Partial dependence plot (PDP) is introduced to visualize the established machine learning model.

Design and evaluation of the OmniSuit: A passive occupational exoskeleton for back and shoulder support

Many physically straining occupations involve lifting movements over the full-vertical range of motion, which over time may lead to the development of musculoskeletal injuries. To address this, occupational exoskeletons can be designed to provide meaningful support to the back and shoulders during lifting movements.This paper introduces the main functional design features of the OmniSuit, a novel passive occupational exoskeleton. We present the technical and biomechanical considerations for the expected support level, as well as an evaluation of the physiological benefit and usability of the exoskeleton in a sample of 31 healthy volunteers performing physically demanding tasks in a laboratory setting.The OmniSuit exoskeleton significantly reduced Deltoid, Trapezius and Erector Spinae muscle activity between 4.1%MVC and 15.7%MVC when lifting a 2.5kg weight above shoulder level (p<0.001), corresponding to a reduction of up to 49.1% compared to without exoskeleton. A position-dependent reduction of Erector Spinae muscle activity was observed (p<0.001), with reductions ranging between 4.6%MVC and 14.0%MVC during leaning and squatting, corresponding to a reduction up to 41.5% compared to without exoskeleton. The measured muscular support and the predicted support torque based on the biomechanical model were found to show a similar profile for those phases of the movement which are most straining to the shoulder and back muscles. Participants reported experiencing good device usability and minimal discomfort (<1/10) in the shoulder and back during task execution with exoskeleton support.These first results validate that the considered biomechanical model helped design an ergonomic and efficient exoskeleton, and confirm the potential of such wearable assistive devices to provide support over multiple joints during physically demanding tasks.

Work-related musculoskeletal disorders and associated factors among weavers working in Bahir Dar City, Northwest Ethiopia: cross-sectional study design

BackgroundWork-related musculoskeletal disorders are one of the most common public health problems throughout the world. It is a major cause of occupational injury, illness, and disability that leads to an increased rate of sick leave, financial costs for both individuals and society and the health care system. Weavers are among the populations exposed to musculoskeletal disorders due to a lack of occupational safety, health services, and poor working conditions. Yet, little is known about WMSD among weavers in Africa particularly in Ethiopia. Thus, this study aimed to assess the prevalence and associated factors of work-related musculoskeletal disorders among weavers.MethodA multi-centered institutional-based cross-sectional study was conducted in Bahir Dar City, Ethiopia among 424 weavers with a response rate of 97.7%. Participants were recruited randomly after proportional allocation was done for each institution and face-to-face interviews were employed to collect data using a well-structured questionnaire adopted from the Nordic musculoskeletal questionnaire and different literature. The data were entered into Epidata and analyzed using SPSS version (Choobineh A, Lahmi M, Shahnavaz H, Khani Jazani R, Hosseini M. Int J Occup Saf Ergon, 10:157–68, 2004). Variables with a P-value < 0.25 in the bivariate logistic regression were entered into a multivariable logistic regression model. Finally, variables with an AOR, a 95% confidence interval, and a P-value of < 0.05 were reported.ResultThe annual prevalence rate of work-related musculoskeletal disorders among weavers was 76.3% [CI = 72.2 to 80.2%]. Longer working hours [AOR = 3.48, CI = (1.96–6.21)] lack of back support during sitting [AOR = 2.50 (1.293–4.480)], having repetitive movement in weaving [AOR = 4.11(2.029–8.324)], attaining awkward posture [AOR = 3.37(1.875–6.059)] and job stress [AOR = 4.37(2.447–7.816)] was significantly associated with work-related musculoskeletal disorders.ConclusionsThis study revealed a high prevalence of WMSDs among weavers. Our study findings reported that longer working hours, lack of back support during sitting, having repetitive movement in weaving attaining awkward posture, and having job stress were significantly associated with work-related musculoskeletal disorders.

Lower back pain and associated factors among weavers working in Bahir Dar City, Northwest Ethiopia: A cross-sectional study.

Work-related musculoskeletal disorders are widespread among workers of informal small-scale enterprises. Specifically, lower back pain is a prevalent occupational health problem across various industries, including weaving factories. Lower back pain significantly impairs the functioning, performance, and productivity of weavers. However, information on the prevalence and associated factors of low back pain among weavers of Bahir Dar City and nationwide is scarce. Therefore, this study aimed to assess the prevalence and associated factors of lower back pain among weavers working in Bahir Dar City. A multicentered institutional-based cross-sectional study was conducted on 403 weavers in Bahir Dar City, Ethiopia, from April to May 2023 using a structured face-to-face interview questionnaire. Samples were proportionally allocated to each institution, and study participants were selected using a simple random sampling technique. Variables with a P-value < 0.25 in the bivariate logistic regression were adopted for the multivariate logistic regression analysis after verifying the model fitness. In the multivariate logistic regression analysis, the adjusted odds ratio (AOR) with a 95% confidence interval (CI) and a P-value < 0.05 were considered to identify the associated factors of lower back pain among weavers. The results revealed that the overall annual prevalence of lower back pain was 63.5% (95% CI = 58.8-68.5). Longer working hours [AOR = 2.580 (CI = 1.517-4.384)], lack of back support [AOR = 1.938 (CI = 2.089-3.449)], repetitive movement of the back during weaving [AOR = 5.940 (CI = 2.709-13.02)], awkward posture [AOR = 2.915 (CI = 1.677-5.065), static working posture [AOR = 4.505 (CI = 2.298-8.831)], and job stress [AOR = 3.306 (CI = 1.896-5.765)] were significantly associated with lower back pain among weavers. Lower back pain among weavers was found to be highly prevalent. Working longer hours, lack of back support, repetitive movement of the back, awkward posture, static posture, and job stress were significantly associated with lower back among weavers. The study recommends prompt interventions on weavers to ensure that they use sitting support, weave for <8 h per day, change positions every 2 h, reduce job-related stress, and minimize task repetition, thereby enhancing their working conditions and minimizing the occurrence of lower back pain.

A comparative study of biomechanical assessments in laboratory and field settings for manual material handling tasks using extractor tools and exoskeletons.

To enhance physical capabilities of workers who regularly perform physically demanding tasks involving heavy lifting and awkward postures, various tools and occupational exoskeletons can be used. Most of the studies aiming to explore the efficiency of these tools and exoskeletons have been performed in confined and controlled laboratory spaces, which do not represent the real-world work environment. This study aimed to compare the outcome of biomechanical assessment of using a back support exoskeleton and assistive tools (Lever and Jake) in the procedure of a high demanding manual material handling task versus the results found by performing the same task in a laboratory. Ten able-bodied participants and ten able-bodied utility workers performed the same manhole removal task in-lab and in-field, respectively, with the aid of an exoskeleton and Lever and Jake tools. Muscle activity and Rapid Entire Body Assessment (REBA) scores were recorded using surface electromyography and inertial measurement units, respectively and compared between in-lab and in-field trials. The field experiments indicated significant differences (p < 0.05) in normalized muscle activity across most muscles when compared to laboratory data. These results revealed how muscle activity is affected by the controlled lab setting compared to real-world field conditions. However, REBA scores indicate similar ergonomic implications regardless of the utilization of exoskeletons or tools. These findings underscore that real-world field assessments are crucial for evaluating ergonomic risks and effects of occupational exoskeletons and tools to account for environmental factors and workers' skills in ergonomic evaluations of this nature.

Enhanced relief of low back pain following surgical repair of a ventral hernia: A case report

The effectiveness of core muscle strengthening in treating Low Back Pain (LBP) is well-established. The laxity or defect of the important portion of core muscle groups, transverse abdominis muscle, as seen in ventral hernia could be a contributing factor for core weakness and instability and thereafter results in LBP. The contribution of ventral hernia to LBP is scantily documented. Ventral hernias can be easily missed if a thorough physical exam is not performed. A 50-year-old male patient presented to the clinic with a 10- year history of LBP; a physical exam revealed a previously undiscovered ventral hernia. He reported a reduction in LBP and improvement in back support after his ventral hernia repair surgery. This case report highlights the importance of a thorough assessment and treatment of the underlying connection between ventral hernia and chronic LBP.

Reconstruction of occluded pelvis markers during marker-based motion capture with industrial exoskeletons

Industrial back support exoskeletons are a promising solution to alleviate lumbar musculoskeletal strain. Due to the complexity of spinal loading, evaluation of EMG data alone has been considered insufficient to assess their support effects, and complementary kinematic and dynamic data are required. However, the acquisition of marker-based kinematics is challenging with exoskeletons, as anatomical reference points, particularly on the pelvis, are occluded by exoskeleton structures. The aim of this study was therefore to develop and validate a method to reliably reconstruct the occluded pelvic markers. The movement data of six subjects, for whom pelvic markers could be placed while wearing an exoskeleton, were used to test the reconstructions and compare them to anatomical landmarks during lifting, holding and walking. Two separate approaches were used for the reconstruction. One used a reference coordinate system based on only exoskeleton markers (EXO), as has been suggested in the literature, while our proposed method adds a technical marker in the lumbar region (LUMB) to compensate for any shifting between exoskeleton and pelvis. Reconstruction with EXO yielded on average an absolute linear deviation of 54 mm ± 16 mm (mean ± 1SD) compared to anatomical markers. The additional marker in LUMB reduced mean deviations to 14 mm ± 7 mm (mean ± 1SD). Both methods were compared to reference values from the literature for expected variances due to marker placement and soft tissue artifacts. For LUMB 99% of reconstructions were within the defined threshold of 24 mm ±9 mm while for EXO 91% were outside.

Biomechanical analysis of different back-supporting exoskeletons regarding musculoskeletal loading during lifting and holding

Industrial back support exoskeletons (BSEs) are a promising approach to addressing low back pain (LBP) which still affect a significant proportion of the workforce. They aim to reduce lumbar loading, the main biomechanical risk factor for LBP, by providing external support to the lumbar spine. The aim of this study was to determine the supporting effect of one active (A1) and two passive (P1 and P2) BSEs during different manual material handling tasks. Kinematic data and back muscle activity were collected from 12 subjects during dynamic lifting and static holding of 10 kg. Mean and peak L5/S1 extension moments, L5/S1 compression forces and muscle activation were included in the analysis. During dynamic lifting all BSEs reduced peak (12–26 %) and mean (4–17 %) extension moments and peak (10–22 %) and mean (4–15 %) compression forces in the lumbar spine. The peak (13–28 %) and mean (4–32 %) activity of the back extensor muscles was reduced accordingly. In the static holding task, analogous mean reductions for P1 and P2 of L5/S1 extension moments (12–20 %), compression forces (13–23 %) and muscular activity (16–23 %) were found. A1 showed a greater reduction during static holding for extension moments (46 %), compression forces (41 %) and muscular activity (54 %). This pronounced difference in the performance of the BSEs between tasks was attributed to the actuators used by the different BSEs.

Safety Monitoring Method for the Uplift Pressure of Concrete Dams Based on Optimized Spatiotemporal Clustering and the Bayesian Panel Vector Autoregressive Model

To establish a safety monitoring method for the uplift pressure of concrete dams, spatiotemporal information from monitoring data is needed. In the present study, the method of ordering points to identify the clustering structure is employed to spatially cluster the uplift pressure measuring points at different locations on the dam; three distance indexes and two clustering evaluation indexes are used to realize clustering optimization and select the optimal clustering results. The Bayesian panel vector autoregressive model is used to establish the uplift stress safety monitoring model for each category of monitoring point. For a nonstationary sequence, the difference method is selected to ensure that the sequence is stable, and the prediction is carried out according to the presence or absence of exogenous variables. The result is that the addition of exogenous variables increases the accuracy of the model’s forecast. Engineering examples show that the uplift pressure measurement points on the dam are divided into seven categories, and classification is based mainly on location and influencing factors. The multiple correlation coefficients of the training set and test set data of the BPVAR model are more than 0.80, and the prediction error of the validation set is lower than that of the Back Propagation neural network, XGBoost algorithm, and Support Vector Machines. The research in this paper provides some reference for seepage monitoring of concrete dams.

Effect of Wearable Passive Back Support Exoskeleton on the Peak Muscle Activation of the Erector Spinae Muscles During Lifting

Effect of Wearable Passive Back Support Exoskeleton on the Peak Muscle Activation of the Erector Spinae Muscles During Lifting

Equivalent weight: Application of the assessment method on real task conducted by railway workers wearing a back support exoskeleton

Commonly used risk indexes, such as the NIOSH Lifting Index, do not capture the effect of exoskeletons. This makes it difficult for Health and Safety professionals to rigorously assess the benefit of such devices. The community requires a simple method to assess the effectiveness of back-support exoskeleton's (BSE) in possibly reducing ergonomic risk. The method introduced in this work is termed “Equivalent Weight” (EqW) and it proposes an interpretation of the effect built on the benefit delivered through reduced activation of the erector spinae (ES). This manifests itself as an apparent reduction of the lifted load perceived by the wearer. This work presents a pilot study where a practical application of the EqW method is used to assess the ergonomic risk in manual material handling (MMH) when using a back support exoskeleton (StreamEXO). The results are assessed by combining observational measurements from on-site testing with five different workers and quantitative measures of the muscle activity reduction achieved during laboratory evaluation with ten workers. These results will show that when lifting, lowering, and carrying a 19 kg load the StreamEXO can reduce risk by up to two levels (from “high” to “low”) in the target sub-tasks. The Lifting index (LI) was reduced up to 64% when examining specific sub-tasks and the worker's movement conduction.