The assessment of material handling strategies in dealing with sudden loading: the effects of load handling position on trunk biomechanics

Real-time lumbosacral joint loading estimation in exoskeleton-assisted lifting conditions via electromyography-driven musculoskeletal models

Lumbar joint compression forces have been linked to the development of chronic low back pain, which is specially present in occupational environments. Offline methodologies for lumbosacral joint compression force estimation are not commonly integrated in occupational or medical applications due to the highly time-consuming and complex post-processing procedures. Hence, applications such as real-time adjustment of assistive devices (i.e., back-support exoskeletons) for optimal modulation of compression forces remains unfeasible. Here, we present a real-time electromyography (EMG)-driven musculoskeletal model, capable of estimating accurate lumbosacral joint moments and plausible compression forces. Ten participants performed box-lifting tasks (5 and 15 kg) with and without the Laevo Flex back-support exoskeleton using squat and stoop lifting techniques. Lumbosacral kinematics and EMGs from abdominal and thoracolumbar muscles were used to drive, in real-time, subject-specific EMG-driven models, and estimate lumbosacral joint moments and compression forces. Real-time EMG-model derived moments showed high correlations (R2 = 0.76 - 0.83) and estimation errors below 30% with respect to reference inverse dynamic moments. Compared to unassisted lifting conditions, exoskeleton liftings showed mean lumbosacral joint moments and compression forces reductions of 11.9 - 18.7 Nm (6 - 12% of peak moment) and 300 - 450 N (5 - 10%), respectively. Our modelling framework was capable of estimating in real-time, valid lumbosacral joint moments and compression forces in line with in vivo experimental data, as well as detecting the biomechanical effects of a passive back-support exoskeleton. Our presented technology may lead to a new class of bio-protective robots in which personalized assistance profiles are provided based on subject-specific musculoskeletal variables.

Inertial Motion Capture-Based Estimation of L5/S1 Moments during Manual Materials Handling

Inertial motion capture (IMC) has gained popularity in conducting ergonomic studies in the workplace. Because of the need to measure contact forces, most of these in situ studies are limited to a kinematic analysis, such as posture or working technique analysis. This paper aims to develop and evaluate an IMC-based approach to estimate back loading during manual material handling (MMH) tasks. During various representative workplace MMH tasks performed by nine participants, this approach was evaluated by comparing the results with the ones computed from optical motion capture and a large force platform. Root mean square errors of 21 Nm and 15 Nm were obtained for flexion and asymmetric L5/S1 moments, respectively. Excellent correlations were found between both computations on indicators based on L5/S1 peak and cumulative flexion moments, while lower correlations were found on indicators based on asymmetric moments. Since no force measurement or load kinematics measurement is needed, this study shows the potential of using only the handler's kinematics measured by IMC to estimate kinetics variables. The assessment of workplace physical exposure, including L5/S1 moments, will allow more complete ergonomics evaluation and will improve the ecological validity compared to laboratory studies, where the situations are often simplified and standardized.

Multi-Output Sequential Deep Learning Model for Athlete Force Prediction on a Treadmill Using 3D Markers

Reliable and innovative methods for estimating forces are critical aspects of biomechanical sports research. Using them, athletes can improve their performance and technique and reduce the possibility of fractures and other injuries. For this purpose, throughout this project, we proceeded to research the use of video in biomechanics. To refine this method, we propose an RNN trained on a biomechanical dataset of regular runners that measures both kinematics and kinetics. The model will allow analyzing, extracting, and drawing conclusions about continuous variable predictions through the body. It marks different anatomical and reflective points (96 in total, 32 per dimension) that will allow the prediction of forces (N) in three dimensions (Fx, Fy, Fz), measured on a treadmill with a force plate at different velocities (2.5 m/s, 3.5 m/s, 4.5 m/s). In order to obtain the best model, a grid search of different parameters that combined various types of layers (Simple, GRU, LSTM), loss functions (MAE, MSE, MSLE), and sampling techniques (down-sampling, up-sampling) helped obtain the best performing model (LSTM, MSE, down-sampling) achieved an average coefficient of determination of 0.68, although when excluding Fz it reached 0.92.

Survey on Video-Based Biomechanics and Biometry Tools for Fracture and Injury Assessment in Sports

This work presents a survey literature review on biomechanics, specifically aimed at the study of existent biomechanical tools through video analysis, in order to identify opportunities for researchers in the field, and discuss future proposals and perspectives. Scientific literature (journal papers and conference proceedings) in the field of video-based biomechanics published after 2010 were selected and discussed. The most common application of the study of biomechanics using this technique is sports, where the most reported applications are american football, soccer, basketball, baseball, jumping, among others. These techniques have also been studied in a less proportion, in ergonomy, and injury prevention. From the revised literature, it is clear that biomechanics studies mainly focus on the analysis of angles, speed or acceleration, however, not many studies explore the dynamical forces in the joints. The development of video-based biomechanic tools for force analysis could provide methods for assessment and prediction of biomechanical force associated risks such as injuries and fractures. Therefore, it is convenient to start exploring this field. A few case studies are reported, where force estimation is performed via manual tracking in different scenarios. This demonstration is carried out using conventional manual tracking, however, the inclusion of similar methods in an automated manner could help in the development of intelligent healthcare, force prediction tools for athletes and/or elderly population. Future trends and challenges in this field are also discussed, where data availability and artificial intelligence models will be key to proposing new and more reliable methods for biomechanical analysis.

Foot Position Measurement during Assistive Motion for Sit-to-Stand Using a Single Inertial Sensor and Shoe-Type Force Sensors

Assistive motion for sit-to-stand causes lower back pain (LBP) among caregivers. Considering previous studies that showed that foot position adjustment could reduce lumbar load during assistive motion for sit-to-stand, quantitative monitoring of and instructions on foot position could contribute toward reducing LBP among caregivers. The present study proposes and evaluates a new method for the quantitative measurement of foot position during assistive motion for sit-to-stand using a few wearable sensors that are not limited to the measurement area. The proposed method measures quantitative foot position (anteroposterior and mediolateral distance between both feet) through a machine learning technique using features obtained from only a single inertial sensor on the trunk and shoe-type force sensors. During the experiment, the accuracy of the proposed method was investigated by comparing the obtained values with those from an optical motion capture system. The results showed that the proposed method produced only minor errors (less than 6.5% of body height) when measuring foot position during assistive motion for sit-to-stand. Furthermore, Bland–Altman plots suggested no fixed errors between the proposed method and the optical motion capture system. These results suggest that the proposed method could be utilized for measuring foot position during assistive motion for sit-to-stand.

Biomechanical assessment while using production tables on mast climbing work platforms

The objective of this study was to assess the impact of using alternative mast climbing work platform (MCWP) designs on trunk motion and postural stability with masonry workers while performing bricklaying and stepping down tasks using a conventional MCWP setting (i.e. with a step deck) as well as two types of production tables (straight- and L-shaped). The trunk angles and postural sway parameters of twenty-five masonry workers were recorded for the following tasks: (1) standing on a simulated MCWP and laying bricks on an adjacent wall, and (2) stepping down onto the step deck to get into position for doing the bricklaying task. Results indicated that the use of the L-shaped production table resulted in the lowest trunk ranges of motion and significantly reduced the workers' trunk angles in all three planes when compared to both the straight-shaped production table and the conventional approach of not using a production table. Data showed that both body sway velocity and area were significantly reduced when using either one of the production tables. The use of production tables significantly reduced impact sway forces when workers stepped from the main platform to the step deck. The use of production tables on MCWPs improved workers' postures and overall stability, which could reduce the risk of injury.

The effects of hospital bed features on physical stresses on caregivers when repositioning patients in bed

Repositioning patients in bed is the most common patient handling activity and is associated with musculoskeletal disorders in caregivers. Hospital bed features may mitigate the risk of injury. The current study investigated the effect of bed features on the physical stress on caregivers. Ten nurses were recruited to perform three repositioning activities. Hand forces were recorded, and spine loading was estimated using a dynamic biomechanical model. Results demonstrated that except for the peak L5/S1 compressive load in the turning task, the use of assistive features significantly reduced the physical stresses for all repositioning activities. However, recommended thresholds for injury were still exceeded in many conditions. Compared with spinal load, hand force was much higher relative to the injury thresholds, suggesting a greater risk of shoulder and upper extremity injuries than low back injury. Mechanical lift equipment remains the safest and most robust way to reposition a patient.

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

The industrial societies face difficulty applying traditional work-related musculoskeletal disorder (WMSD) risk assessment methods in practical applications due to in-situ task dynamics, complex data processing, and the need of ergonomics professionals. This study aims to develop and validate a wearable inertial sensors-based automated system for assessing WMSD risks in the workspace conveniently, in order to enhance workspace safety and improve workers’ health. Both postural ergonomic analysis (RULA/REBA) and two-dimensional static biomechanical analysis were automatized as two toolboxes in the proposed system to provide comprehensive WMSD risk assessment based on the kinematic data acquired from wearable inertial sensors. The effectiveness of the developed system was validated through a follow-up experiment among 20 young subjects when performing representative tasks in the heavy industry. The RULA/REBA scores derived from our system achieved high consistency with experts’ ratings (intraclass correlation coefficient ≥0.83, classification accuracy >88%), and good agreement was also found between low-back compression force from the developed system and the reference system (mean intersystem coefficient of multiple correlation >0.89 and relative error <9.5%). These findings suggested that the wearable inertial sensors-based automated system could be effectively used for WMSD risk assessment of workers when performing tasks in the workspace.

Measuring Biomechanical Risk in Lifting Load Tasks Through Wearable System and Machine-Learning Approach

Ergonomics evaluation through measurements of biomechanical parameters in real time has a great potential in reducing non-fatal occupational injuries, such as work-related musculoskeletal disorders. Assuming a correct posture guarantees the avoidance of high stress on the back and on the lower extremities, while an incorrect posture increases spinal stress. Here, we propose a solution for the recognition of postural patterns through wearable sensors and machine-learning algorithms fed with kinematic data. Twenty-six healthy subjects equipped with eight wireless inertial measurement units (IMUs) performed manual material handling tasks, such as lifting and releasing small loads, with two postural patterns: correctly and incorrectly. Measurements of kinematic parameters, such as the range of motion of lower limb and lumbosacral joints, along with the displacement of the trunk with respect to the pelvis, were estimated from IMU measurements through a biomechanical model. Statistical differences were found for all kinematic parameters between the correct and the incorrect postures (p < 0.01). Moreover, with the weight increase of load in the lifting task, changes in hip and trunk kinematics were observed (p < 0.01). To automatically identify the two postures, a supervised machine-learning algorithm, a support vector machine, was trained, and an accuracy of 99.4% (specificity of 100%) was reached by using the measurements of all kinematic parameters as features. Meanwhile, an accuracy of 76.9% (specificity of 76.9%) was reached by using the measurements of kinematic parameters related to the trunk body segment.

Motion-based prediction of external forces and moments and back loading during manual material handling tasks

This paper evaluates a method for motion-based prediction of external forces and moments on manual material handling (MMH) tasks. From a set of hypothesized contact points between the subject and the environment (ground and load), external forces were calculated as the minimal forces at each contact point while ensuring the dynamics equilibrium. Ground reaction forces and moments (GRF&M) and load contact forces and moments (LCF&M) were computed from motion data alone. With an inverse dynamics method, the predicted data were then used to compute kinetic variables such as back loading. On a cohort of 65 subjects performing MMH tasks, the mean correlation coefficients between predicted and experimentally measured GRF for the vertical, antero-posterior and medio-lateral components were 0.91 (0.08), 0.95 (0.03) and 0.94 (0.08), respectively. The associated RMSE were 0.51 N/kg, 0.22 N/kg and 0.19 N/kg. The correlation coefficient between L5/S1 joint moments computed from predicted and measured data was 0.95 with a RMSE of 14 Nm for the flexion/extension component. In conclusion, this method allows the assessment of MMH tasks without force platforms, which increases the ecological aspect of the tasks studied and enables performance of dynamic analyses in real settings outside the laboratory.

The effect of diaphragm training on lumbar stabilizer muscles: a new concept for improving segmental stability in the case of low back pain

PURPOSE

The aim of this study was to assess the effects of diaphragm training on low back pain and thickness of stabilizer muscles of the lumbar spine.

PATIENTS AND METHODS

Fifty-two individuals were recruited with a history of chronic low back pain in our randomized controlled trial. The participants were divided randomly into two groups. One of the groups took part in a complex training program and completed with diaphragm training (DT group, n=26). The control (C) group took part only in the complex training (n=21). The thickness of transversus abdominis, diaphragm, and lumbar multifidus muscle was measured with ultrasonography in two positions: lying and sitting. All muscles were assessed in relaxed and in contracted state in the lying position and in a relatively relaxed (calm sitting) and relatively contracted state (during weightlifting) in the sitting position.

RESULTS

After the training, severity of the pain was significantly reduced in both the groups. Regarding the thickness of the muscles, there were no changes in group C. The thickness of transversus abdominis increased significantly in relaxed and in relatively relaxed state, but there were no changes in contracted and relatively contracted state in group DT. As for the diaphragm muscle, there were significant increase in the state of supine position and in relatively contracted state, but there was no notable change in relatively relaxed state. With regard to the thickness of lumbar multifidus, a significant increase was only found in the left-sided muscle in relaxed, relatively relaxed, and relatively contracted state and in case of the right-sided one in relatively contracted state in group DT.

CONCLUSION

Our results suggest that diaphragm training has an effect also on the thickness of other active stabilizers of the lumbar spine, such as transversus abdominis and lumbar multifidus muscles.

The influence of external load configuration on trunk biomechanics and spinal loading during sudden loading

Sudden loading is a major risk factor for work-related lower back injuries among occupations involving manual material handling (MMH). The current study explored the effects of external weight configuration on trunk biomechanics and trunk rotational stiffness in the sagittal plane during sudden loading. Fifteen asymptomatic volunteers experienced sudden loadings using the same magnitude of weight (9 kg) with two different configurations (medially- or laterally-distributed) at three levels of height (low, middle and high). Results of this study showed that the medially distributed weight resulted in a significantly higher peak L5/S1 joint compression force (2861 N vs. 2694 N) and trunk rotational stiffness (2413 Nm/rad vs. 1785 Nm/rad) compared to the laterally distributed weight. It was concluded that when experiencing sudden loading, a more laterally distributed weight could increase the load's resistance to physical perturbations and alleviate spinal loading during sudden loading events. Practitioner summary: Increased trunk rotational stiffness and peak L5/S1 joint compression force were observed when undergoing a sudden load release of a medially distributed load compared to a laterally distributed load revealing a less stable hand load condition due to the reduced moment of inertia. The laterally distributed load could increase the load's resistance to physical perturbations and mitigate spinal loading during sudden loading events.

Effects of the weight configuration of hand load on trunk musculature during static weight holding

The performance of manual material handling tasks is one major cause of lower back injuries. In the current study, we investigated the influence of the weight configuration of hand loads on trunk muscle activities and the associated spinal stability. Thirteen volunteers each performed static weight-holding tasks using two different 9 kg weight bars (with medial and lateral weight configurations) at two levels of height (low and high) and one fixed horizontal distance (which resulted in constant spinal joint moment across conditions). Results of the current study demonstrated that holding the laterally distributed load significantly reduced activation levels of lumbar and abdominal muscles by 9-13% as compared with holding the medially distributed load. We believe such an effect is due to an elevated rotational moment of inertia when the weight of the load is laterally distributed. These findings suggest that during the design and assessment of manual material handling tasks, such as lifting and carrying, the weight configuration of the hand load should be considered. Practitioner summary: Elevated trunk muscle activities were found when holding a medially distributed load vs. a laterally distributed load (with an equivalent external moment to the spine), indicating a reduced spinal stability due to the reduced rotational moment of inertia. The configuration of the hand load should be considered when evaluating manual material handling tasks.

An EMG-assisted modeling approach to assess passive lumbar tissue loading in vivo during trunk bending

Lower back pain (LBP) is a condition with high prevalence and high cost both in the United States and around the world. The magnitude of mechanical loading on spine is strongly associated with the occurrence of LBP. Previously, to assess spinal loading, biologically assisted biomechanical models were developed to estimate trunk muscle contraction forces. Loadings on lumbar passive tissues are estimated using anatomical models. However, despite the substantial individual variability in lumbar ligament geometry and viscoelastic properties, the existing anatomical models do not account for these differences. As such, the accuracy of model prediction is compromised especially when mid to full range of trunk motions are involved. This paper describes a new modeling approach to assess lumbar passive tissue loading with the consideration of individual differences in lumbar passive tissue properties. A data set that has trunk bending data from 13 human participants was analyzed; on average, lumbar passive tissue contributes to ∼89% of the total spinal compression force at fully flexed trunk postures; the estimated spinal tissue loadings were in feasible ranges as reported from previous cadaver studies; the estimated spinal loadings were also mostly in agreement with results from previous in vivo studies.

Ergonomic evaluation of brake pedal and push handle locations on hospital beds

Transporting patients in hospital beds is a physically demanding activity performed by healthcare workers and bed design may moderate the risk of injury. Nine healthcare workers participated in a study to investigate how brake pedal location affected maximal voluntary exertion (MVE) force and the level of acceptable force for engagement. Preferred and acceptable push heights when maneuvering a bed were also evaluated. The method of limits was used to determine acceptable forces and push heights. Results demonstrated that pedal depth, clearance above, and clearance behind the pedal significantly affected MVE force and acceptable force. Preferred push height was approximately at elbow level and a single height would not accommodate the user population. These findings provide important considerations for hospital bed design. The method of limits was a valid and reliable approach for evaluating user acceptance of design inputs characterized by continuous variables and may be useful in other design evaluations.

Differences in lumbopelvic rhythm between trunk flexion and extension

BACKGROUND

Trunk flexion and extension have already been found to have different characteristics, such as those in lumbopelvic rhythm. Although a more advanced method of quantifying such rhythm, lumbopelvic continuous relative phase and phase variability have not been used to explore the differences between trunk flexion and extension motions. This information is important since abnormal lumbopelvic coordination patterns increase the risk of low back pain. The current study investigated the differences in lumbopelvic rhythm between trunk flexion and extension, and how the rhythm changed within each of the two motions.

METHODS

Thirteen subjects performed pace-controlled trunk flexion/extension motions in the sagittal plane while lumbar and pelvis kinematics data were recorded, such that the lumbopelvic continuous relative phase and phase variability could be calculated to quantify lumbopelvic rhythm.

FINDINGS

Trunk extension motion had significantly smaller lumbopelvic continuous relative phase and phase variability than flexion motion, which indicated a more in-phase and stable rhythm. Additionally, the lumbopelvic rhythm within trunk extension motion changed from a more in-phase and stable pattern to a more out-of-phase and unstable pattern; by contrast, the opposite change (from out-of-phase and unstable to in-phase and stable) was observed in trunk flexion.

INTERPRETATION

Findings of the current study provided important information about the differences in lumbopelvic rhythm between trunk flexion and extension motions. Quantifying these patterns provides the means for identifying abnormal patterns in a clinical setting, and could serve as normative benchmarks during low back pain rehabilitation plans.

The effect of time-of-day on static and dynamic balance in recreational athletes

The purpose of this study was to investigate the effect of time-of-day (morning vs. afternoon) on static and dynamic balance in recreational athletes. A total of 34 recreational athletes completed the single-leg stance test with or without eyes open, lower quarter Y-balance test, upper quarter Y-balance test, and single-leg landing balance test in a random order in the morning (7:00-10:00 am) and afternoon (3:00-6:00 pm) for two consecutive days. Compared with the morning, participants demonstrated decreased centre of pressure (COP) sway areas (p = 0.002; Cohen's d (d) = 0.28) and sway speeds (p = 0.002; d = 0.17) during the eyes-open single-leg stance test, increased stance time (p = 0.031; d = 0.16) and decreased COP sway areas (p = 0.029; d = 0.22) during the eyes-closed single-leg stance test, and increased reaching distances (p = 0.024; d = 0.10) during the upper quarter Y-balance test in the afternoon. The between-day effect (day 1 vs. day 2) was observed for several parameters. Time-of-day had a minimal effect on dynamic balance and a noticeable effect on static balance. Time-of-day may be considered as a factor in designing balance training programmes and intervention studies for recreational athletes.

The influence of lumbar extensor muscle fatigue on lumbar-pelvic coordination during weightlifting

Lumbar muscle fatigue is a potential risk factor for the development of low back pain. In this study, we investigated the influence of lumbar extensor muscle fatigue on lumbar-pelvic coordination patterns during weightlifting. Each of the 15 male subjects performed five repetitions of weightlifting tasks both before and after a lumbar extensor muscle fatiguing protocol. Lumbar muscle electromyography was collected to assess fatigue. Trunk kinematics was recorded to calculate lumbar-pelvic continuous relative phase (CRP) and CRP variability. Results showed that fatigue significantly reduced the average lumbar-pelvic CRP value (from 0.33 to 0.29 rad) during weightlifting. The average CRP variability reduced from 0.17 to 0.15 rad, yet this change ws statistically not significant. Further analyses also discovered elevated spinal loading during weightlifting after the development of lumbar extensor muscle fatigue. Our results suggest that frequently experienced lumbar extensor muscle fatigue should be avoided in an occupational environment.

PRACTITIONER SUMMARY

Lumbar extensor muscle fatigue generates more in-phase lumbar-pelvic coordination patterns and elevated spinal loading during lifting. Such increase in spinal loading may indicate higher risk of back injury. Our results suggest that frequently experienced lumbar muscle fatigue should be avoided to reduce the risk of LBP.