Paralumbar compartment syndrome, a rare sequela of deadlifting: a case report and review of current literature.

BACKGROUND: Compartment syndrome is a well-known phenomenon that is most commonly reported in the extremities. However, paralumbar compartment syndrome is rarely described in available literature. The authors present a case of paralumbar compartment syndrome after high intensity deadlifting. CASE PRESENTATION: 53-year-old male who presented with progressively worsening low back pain and paresthesias one day after high-intensity deadlifting. Laboratory testing found the patient to be in rhabdomyolysis; he was admitted for intravenous fluid resuscitation and pain control. Orthopedics was consulted, and Magnetic Resonance Imaging revealed significant paravertebral edema and loss of muscle striation. Given the patient's lack of improvement with intravenous and oral pain control, clinical and radiographic findings, there was significant concern for acute paralumbar compartment syndrome. The patient subsequently underwent urgent fasciotomy of bilateral paralumbar musculature with delayed closure. CONCLUSION: Given the paucity of literature on paralumbar compartment syndrome, the authors' goal is to promote awareness of the diagnosis, as it should be included in the differential diagnosis of intractable back pain after high exertional exercise. The current literature suggests that operative cases of paralumbar compartment syndromes have a higher rate of return to pre-operative function compared to those treated non-operatively. This case report further supports this notion. The authors recommend further study into this phenomenon, given its potential to result in persistent chronic exertional pain and irreversible tissue damage.

Work-related musculoskeletal disorders among desludging operators in Uganda.

BACKGROUND: Despite the limited evidence, desludging operators remain at a heightened risk of work-related musculoskeletal disorders (WMSDs). This study established the prevalence and predictors of WMSDs among desludging operators in Uganda. METHODS: A digitalized structured questionnaire was used to collect cross-sectional data on musculoskeletal disorders and routine workplace activities from 303 desludging operators in 11 cities in Uganda. These cities were purposively selected based on the presence of a fecal sludge treatment plant or wastewater treatment plant. The Nordic Musculoskeletal Questionnaire (NMQ) was used to assess WMSDs. Simple random sampling with replacements was used to select respondents. Data were analyzed using STATA version 15.0. Modified Poisson Regression was used to measure the strength of association between the independent variables and WMSDs. RESULTS: A total of 303 study participants were interviewed (97.7% response rate). The average age of the respondents was 34.0 years (SD ± 9.8). The prevalence of WMSDs among desludging operators was 29.7%. The body parts affected by MSDs were; the elbow for 4.6% (14/303), shoulder for 5.0% (15/303), and wrist/hand for 6.3% (19/303) of the respondents. At multivariable analysis, after controlling for age, desludging operators' ability to influence the availability of equipment needed to do their work (APR = 0.45, 95% CI: 0.20-0.99), and feeling that everything done was an effort (APR = 1.70, 95% CI: 1.01-2.87) were significantly associated with WMSDs. CONCLUSION: The prevalence of WMSDs was high among desludging operators in Uganda. Desludging operators' ability to influence the availability of equipment needed to do their work and frequency of feeling that everything done was an effort were significantly associated with WMSDs. Interventions should focus on ensuring adequate provision of ergonomic equipment and promoting practices that reduce the physical strain associated with desludging tasks. Additionally, comprehensive training programs addressing proper lifting techniques and posture awareness could significantly mitigate the risk of WMSDs among desludging-operators.

A tensor decomposition reveals ageing-induced differences in muscle and grip-load force couplings during object lifting.

Do motor patterns of object lifting movements change as a result of ageing? Here we propose a methodology for the characterization of these motor patterns across individuals of different age groups. Specifically, we employ a bimanual grasp-lift-replace protocol with younger and older adults and combine measurements of muscle activity with grip and load forces to provide a window into the motor strategies supporting effective object lifts. We introduce a tensor decomposition to identify patterns of muscle activity and grip-load force ratios while also characterizing their temporal profiles and relative activation across object weights and participants of different age groups. We then probe age-induced changes in these components. A classification analysis reveals three motor components that are differentially recruited between the two age groups. Linear regression analyses further show that advanced age and poorer manual dexterity can be predicted by the coupled activation of forearm and hand muscles which is associated with high levels of grip force. Our findings suggest that ageing may induce stronger muscle couplings in distal aspects of the upper limbs, and a less economic grasping strategy to overcome age-related decline in manual dexterity.

Effects of abdominal hollowing and bracing on each intervertebral angle during quadruped upper and lower extremity lift: Three-dimensional motion analysis of the spine.

To investigate the effects of intentionally minimizing spinal motion and abdominal muscle contractions on intervertebral angles during quadruped upper and lower extremity lift (QULEL). Fifteen healthy men performed the QULEL under four conditions: without any special instructions (basic), with the intention to minimize spinal motion (intentional), with abdominal bracing (bracing), and with abdominal hollowing (hollowing). Each intervertebral angle was calculated from the local coordinate system using the marker data obtained from a motion capture system. Shear moduli, as indicators of the activities of the right transversus abdominis (TrA), internal and external oblique, and rectus abdominis muscles, were assessed using shear wave elastography during QULEL. One-way repeated-measures analysis of variance and multiple comparisons among conditions were used to compare each shear modulus of the abdominal muscle and the changes in thoracic kyphosis (Th1-12), lumbar lordosis (L1-5), and lumbar intervertebral angles from the quadruped position to QULEL. The significance level was set at P < 0.05. Changes in lumbar lordosis and L2/L3 and L3/L4 extension angles were significantly lower under hollowing than under other conditions (effect size ηG2: lumbar lordosis, 0.068; L2/L3, 0.072; L3/L4, 0.043). The change in the L1/L2 extension angle significantly decreased in bracing and hollowing compared with the basic (ηG2 = 0.070). Only the TrA shear modulus significantly increased in bracing and hollowing compared with the basic (ηG2 = 0.146). Abdominal hollowing during the QULEL increased TrA activity and suppressed lumbar extension, except at L4/L5, and may be more effective as a rehabilitation exercise for controlling spinal motion.

Use of a wearable electromyography armband to detect lift-lower tasks and classify hand loads.

We used an armband with embedded surface electromyography (sEMG) electrodes, together with machine-learning (ML) models, to automatically detect lifting-lowering activities and classify hand loads. Nine healthy participants (4 male and 5 female) completed simulated lifting-lowering tasks in various conditions and with two different hand loads (2.3 and 6.8 kg). We compared three sEMG signal feature sets (i.e., time, frequency, and a combination of both domains) and three ML classifiers (i.e., Random Forest, Support Vector Machine, and Logistic Regression). Both Random Forest and Support Vector Machine models, using either time-domain or time- and frequency-domain features, yielded the best performance in detecting lifts, with respective accuracies of 79.2% (start) and 86.7% (end). Similarly, both ML models yielded the highest accuracy (80.9%) in classifying the two hand loads, regardless of the sEMG features used, emphasizing the potential of sEMG armbands for assessing exposure and risks in occupational lifting tasks.

Incidence of knee and hip joint replacement associated with cumulative exposure to physical factors at work.

BACKGROUND: Knee osteoarthritis (OA) has been quite consistently associated with high physical workload and specific physical factors at work, while for hip OA, fewer studies are available, which still indicate possible associations with heavy lifting and physical workload. The objective of the study was to assess the association between exposure to workplace physical factors and incidence of knee and hip arthroplasty, as markers of severe OA in these joints. METHODS: The study population was composed of employees 25-60 years who participated in the Turin 2011 census. For each job held since 1995, exposure to physical factors was assigned to individuals in the cohort through a Job-Exposure Matrix constructed from the Italian O*NET database. Using Poisson regression models, the incidence of knee and hip arthroplasty for OA, identified through hospitalizations from 2012 to 2018, was examined in relation to cumulative exposure to 7 different physical hazards and a composite indicator of physical workload constructed from 17 physical factors (Ergo-Index). RESULTS: The risk of knee OA was significantly increased in the highest cumulative exposure quartile of physical workload (incidence rate ratio = 1.98, 95% confidence interval: 1.24-3.16) and of all single hazards examined, compared to the lowest quartile, with significant trends in risk with increasing exposure. In contrast, no association was found with hip OA, whose relative risks were close to or below one in all higher-exposure quartiles of physical workload and of each single hazard. CONCLUSIONS: Our results indicate that exposure to physical hazards at work increases the likelihood of developing knee OA, but not hip OA.

Comparison of multi-task ergonomic assessment methods for risk of upper extremity and low back musculoskeletal disorders.

Work-related musculoskeletal disorder of upper extremity multi-task assessment methods (Revised Strain Index [RSI], Distal Upper Extremity Tool [DUET]) and manual handling multi-task assessment methods (Revised NIOSH Lifting Equation [RNLE], Lifting Fatigue Failure Tool [LiFFT]) were compared. RSI and DUET showed a strong correlation (rs = 0.933, p < 0.001) where increasing risk factor exposure resulted in increasing outputs for both methods. RSI and DUET demonstrated fair agreement (κ = 0.299) in how the two methods classified outputs into risk categories (high, moderate or low) when assessing the same tasks. The RNLE and LiFFT showed a strong correlation (rs = 0.903, p = 0.001) where increasing risk factor exposure resulted in increasing outputs, and moderate agreement (κ = 0.574) in classifying the outputs into risk categories (high, moderate or low) when assessing the same tasks. The multi-task assessment methods provide consistent output magnitude rankings in terms of increasing exposure, however some differences exist between how different methods classify the outputs into risk categories.

The effects of an upper limb exoskeleton on gait performance and stability.

Upper limb exoskeletons (ULEs) are emerging as workplace tools to alleviate workload and prevent work-related musculoskeletal disorders during lifting tasks. However, their introduction raises concerns about potential instability and increased fall risk for workers. This study investigates gait performance and stability parameters implications of ULE use. Fifteen participants performed a carrying task with different loads (0, 5, 10, 15 kg), both with and without the use of an ULE. Spatiotemporal gait parameters, Required Coefficient of Friction (RCoF), Minimum Foot Clearance (MFC), and Margin of Stability (MoS) were analysed. The findings indicate that while the ULE does not significantly alter most gait parameters or slip risk, it may negatively impact trip risk. Furthermore, while mediolateral stability remains unaffected, anteroposterior stability is compromised by ULE usage. These insights are critical for ensuring the safe implementation of ULEs in occupational settings.

Restricting lumbar spine flexion redistributes and changes total mechanical energy expenditure during lifting.

Minimizing lumbar spine flexion during lifting requires greater lower extremity joint motion. However, the effects of these kinematic changes on lumbar and lower extremity joint kinetics are unknown. Further, it is unclear whether the distribution of biomechanical demands throughout the lumbar spine and lower extremity during lumbar spine flexion restricted lifting are modulated by task factors like lift origin height and object mass. This study examined the influence of restricting lumbar spine flexion during lifting on the distribution of biomechanical demands, operationalized as mechanical energy expenditure (MEE), across the lumbar spine and lower extremity joints during lifting tasks. Twenty participants performed a series of lifting tasks that varied by lift origin height, object mass and presence or absence of lumbar spine motion restricting harness. MEE was quantified for the lumbar spine and lower extremity joints and summed across all joints to represent the total MEE. Distributions of MEE were compared across combinations of the three task factors. Total MEE was greater when lifting with restricted spine motion (p < 0.001). MEE was redistributed away from the lumbar spine and predominantly to the hips in the spine restricted conditions (p < 0.001). The nature and magnitude of this effect was modulated by lift origin height for the lumbar spine (p < 0.001) and hips (p < 0.001). Findings demonstrated that biomechanical demands can be shifted from the lumbar spine to the lower extremity when lifting with restricted spine flexion, which might help mitigate overuse injuries through coordinative variability.

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.

Estimation of lower back muscle force in a lifting task using wearable IMUs.

Low back pain is commonly reported in occupational settings due to factors such as heavy lifting and poor ergonomic practices, often resulting in significant healthcare expenses and lowered productivity. Assessment tools for human motion and ergonomic risk at the workplace are still limited. Therefore, this study aimed to assess lower back muscle and joint reaction forces in laboratory conditions using wearable inertial measurement units (IMUs) during weight lifting, a frequently high-risk workplace task. Ten able-bodied participants were instructed to lift a 28 lbs. box while surface electromyography sensors, IMUs, and a camera-based motion capture system recorded their muscle activity and body motion. The data recorded by IMUs and motion capture system were used to estimate lower back muscle and joint reaction forces via musculoskeletal modeling. Lower back muscle patterns matched well with electromyography recordings. The normalized mean absolute differences between muscle forces estimated based on measurements of IMUs and cameras were less than 25 %, and the statistical parametric mapping results indicated no significant difference between the forces estimated by both systems. However, abrupt changes in motion, such as lifting initiation, led to significant differences (p < 0.05) between the muscle forces. Furthermore, the maximum L5-S1 joint reaction force estimated using IMU data was significantly lower (p < 0.05) than those estimated by cameras during weight lifting and lowering. The study showed how kinematic errors from IMUs propagated through the musculoskeletal model and affected the estimations of muscle forces and joint reaction forces. Our findings showed the potential of IMUs for in-field ergonomic risk evaluations.

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.

Manual rolling load and low back pain among workers in Japan: a cross-sectional study.

OBJECTIVES: Manual rolling of heavy objects remains in the workplace. The Health and Safety Executive (HSE) in the United Kingdom recommends load weights of <400 kg in the rolling task. However, the association of rolling weights <400 kg with work-related low back pain (LBP) has not been sufficiently investigated. This study examined the effect of rolling loads weighing <400 kg on LBP among Japanese workers. METHODS: A web-based survey gathered information from 15 158 workers in 2022. Among them, 15 035 did not handle loads, whereas 123 handled rolling weights <400 kg. Load weight was categorized into 4 groups: no-handling (0 kg) and rolling weights of ≤20, 20-40, and >40 kg. Multiple logistic regression analysis examined the association between the subdivided rolling weight and LBP. RESULTS: No significant differences in odds ratio (OR) of LBP were found for workers handling ≤40 kg rolling weights compared with that for no-handling workers. However, workers handling >40 kg rolling weights had a significantly greater OR of LBP than those not handling loads. CONCLUSIONS: Rolling weights between 40 and 400 kg could place a high stress on the lower back. Implementation in Japan of the HSE recommendations regarding rolling load should be carefully considered.

Tip of the iceberg: unveiling the impact on back disorders from cumulative physical job exposure and evaluating bias from the healthy worker effect using a nationwide longitudinal cohort study.

PURPOSE: Longitudinal studies across various sectors with physically demanding jobs are notably absent in back disorder risk research. This study aimed to investigate the relationship between cumulative physical job exposure (PJE) and hospital-diagnosed back disorders among individuals in Denmark. To assess the healthy worker effect, we compared the cumulative risk estimate with results from a naive cross-sectional model ignoring PJE history. METHODS: A nationwide longitudinal cohort study was conducted using Danish registers, encompassing individuals born between 1975 and 1978 and working in 1996. Cumulative PJE was measured with a 10-year look-back period for each year 2006-2017. PJE consisted of lower-body occupational exposures, including the total weight lifted, stand/sit ratio, and the frequency of lifting more than 20 kg per day from a job exposure matrix. Odds ratio for back disorders was estimated for each year and all years combined. RESULTS: The results unveiled a significant 31% increase in the risk of hospital-diagnosed back disorders after 4 years of cumulative PJE. The lowest risk (7%) was observed for incident back disorders with 1 year of exposure, suggesting a healthy worker effect. Nevertheless, this risk is still significantly elevated. This cumulative estimate is fourfold the estimate from the 2006 naive cross section model. CONCLUSION: Our study clearly demonstrates an 31% increase in the risk of hospital-diagnosed back disorders with just 4 years of PJE over a 10-year period. Further, we find that cross-sectional studies strongly underestimate the risk of back disorders due to the healthy worker effect.

Adaptive Lifting Index (aLI) for Real-Time Instrumental Biomechanical Risk Assessment: Concepts, Mathematics, and First Experimental Results.

When performing lifting tasks at work, the Lifting Index (LI) is widely used to prevent work-related low-back disorders, but it presents criticalities pertaining to measurement accuracy and precision. Wearable sensor networks, such as sensorized insoles and inertial measurement units, could improve biomechanical risk assessment by enabling the computation of an adaptive LI (aLI) that changes over time in relation to the actual method of carrying out lifting. This study aims to illustrate the concepts and mathematics underlying aLI computation and compare aLI calculations in real-time using wearable sensors and force platforms with the LI estimated with the standard method used by ergonomists and occupational health and safety technicians. To reach this aim, 10 participants performed six lifting tasks under two risk conditions. The results show us that the aLI value rapidly converges towards the reference value in all tasks, suggesting a promising use of adaptive algorithms and instrumental tools for biomechanical risk assessment.

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.

Hip osteoarthritis and occupational mechanical exposures: a systematic review and meta-analysis.

OBJECTIVES: The aim was to conduct a systematic review and meta-analysis investigating the association between occupational mechanical exposures and hip osteoarthritis. METHODS: The study was registered in PROSPERO. A systematic literature search was conducted in six databases to identify relevant articles. Two authors independently excluded articles, extracted data, assessed the risk of bias of each included article, and graded the level of evidence. We conducted a meta-analysis using random-effects model and performed a sensitivity analysis stratifying articles based on the risk of bias assessment, study design, and the outcome measurement. RESULTS: Twenty-four articles were eligible for inclusion. The highest pooled odds ratio (OR) was found for combined mechanical exposures [OR 1.7, 95% confidence interval (CI) 1.4-2.0], non-neutral postures (OR 1.7, 95% CI 1.4-2.1), lifting/carrying loads (OR 1.6, 95% CI 1.3-1.9), and climbing stairs (OR 1.6, 95% CI 1.1-2.2). The range of pooled OR for the remaining mechanical exposures (eg, standing, walking, kneeling, squatting, and sitting) was 0.6-1.6. Grading the quality of evidence, a moderate level of evidence was found for the combined mechanical exposures and for lifting/carrying loads. The remaining exposure categories were graded as having either low or very low levels of evidence. CONCLUSIONS: Considerable heterogeneity was observed across the included studies, and high-quality literature using objective exposure measurements is warranted. Despite various limitations affecting the comparability, occupational mechanical exposures seem to influence the likelihood of developing hip osteoarthritis.

Electromyography-driven musculoskeletal models with time-varying fatigue dynamics improve lumbosacral joint moments during lifting.

Muscle fatigue is prevalent across different aspects of daily life. Tracking muscle fatigue is useful to understand muscle overuse and possible risk of injury leading to musculoskeletal disorders. Current fatigue models are not suitable for real-world settings as they are either validated using simulations or non-functional tasks. Moreover, models that capture the changes to muscle activity due to fatigue either assume a linear relationship between muscle activity and muscle force or utilize a simple muscle model. Personalised electromygraphy (EMG)-driven musculoskeletal models (pEMS) offer person-specific approaches to model muscle and joint kinetics during a wide repertoire of daily life tasks. These models utilize EMG, thus capturing central fatigue-dependent changes in multi-muscle bio-electrical activity. However, the peripheral muscle force decay is missing in these models. Thus, we studied the influence of fatigue on a large scale pEMS of the trunk. Eleven healthy participants performed functional asymmetric lifting task. Average peak body-weight normalized lumbosacral moments (BW-LM) were estimated to be 2.55 ± 0.26 Nm/kg by reference inverse dynamics. After complete exhaustion of the lower back, the pEMS overestimated the peak BW-LM by 0.64 ± 0.37 Nm/kg. Then, we developed a time-varying muscle force decay model resulting in a time-varying pEMS (t-pEMS). This reduced the difference between BW-LM estimated by the t-pEMS and reference to 0.49 ± 0.14 Nm/kg. We also showed that five fatiguing contractions are sufficient to calibrate the t-pEMS. Thus, this study presents a person and muscle specific model to track fatigue during functional tasks.

Regression-Based Machine Learning for Predicting Lifting Movement Pattern Change in People with Low Back Pain.

Machine learning (ML) algorithms are crucial within the realm of healthcare applications. However, a comprehensive assessment of the effectiveness of regression algorithms in predicting alterations in lifting movement patterns has not been conducted. This research represents a pilot investigation using regression-based machine learning techniques to forecast alterations in trunk, hip, and knee movements subsequent to a 12-week strength training for people who have low back pain (LBP). The system uses a feature extraction algorithm to calculate the range of motion in the sagittal plane for the knee, trunk, and hip and 12 different regression machine learning algorithms. The results show that Ensemble Tree with LSBoost demonstrated the utmost accuracy in prognosticating trunk movement. Meanwhile, the Ensemble Tree approach, specifically LSBoost, exhibited the highest predictive precision for hip movement. The Gaussian regression with the kernel chosen as exponential returned the highest prediction accuracy for knee movement. These regression models hold the potential to significantly enhance the precision of visualisation of the treatment output for individuals afflicted with LBP.

Effect of low back pain on the kinetics and kinematics of the lumbar spine - a combined in vivo and in silico investigation.

Lifting is a significant risk factor for low back pain (LBP). Different biomechanical factors including spinal loads, kinematics, and muscle electromyography (EMG) activities have previously been investigated during lifting activities in LBP patients and asymptomatic individuals to identify their association with LBP. However, the findings were contradictory and inconclusive. Accurate and subject-specific prediction of spinal loads is crucial for understanding, diagnosing, planning tailored treatments, and preventing recurrent pain in LBP patients. Therefore, the present study aimed to estimate the L5-S1 compressive and resultant shear loads in 19 healthy and 17 non-specific chronic LBP individuals during various static load-holding tasks (holding a 10 kg box at hip, chest, and head height) using full-body and personalized musculoskeletal models driven by subject-specific in vivo kinematic/kinetic, EMG, and physiological cross-sectional areas (PCSAs) data. These biomechanical characteristics were concurrently analyzed to identify potential differences between the two groups. Statistical analyses showed that LBP had almost no significant effect on the range of motion (trunk, lumbar, pelvis), PCSA, and EMG. There were no significant differences (p > 0.05) in the predicted L5-S1 loads. However, as the task became more demanding, by elevating the hand-load from hip to head, LBP patients experienced significant increases in both compressive (33 %, p = 0.00) and shear (25 %, p = 0.02) loads, while asymptomatic individuals showed significant increases only in compressive loads (30 %, p = 0.01). This suggests that engaging in more challenging activities could potentially magnify the effect of LBP on the biomechanical factors and increase their discrimination capacity between LBP and asymptomatic individuals.