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Register a new userThe Stoop-Squat-Index: a simple but powerful measure for quantifying lifting behavior
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Stefan Schmid
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The widely held belief that squat lifting should be preferred over stoop lifting to prevent back injury is increasingly being challenged by recent biomechanical evidence. However, most of these studies only focus on very localized parameters such as lumbar spine flexion, while evaluations of whole-body lifting strategies are largely lacking. For this reason, a novel index, the Stoop-Squat-Index, was developed, which describes the proportion between trunk forward lean and lower extremity joint flexion, with possible values ranging from 0 (full squat lifting) to 100 (full stoop lifting). To enable the interpretation of the index in a real-life setting, normative values were established using motion capture data from 30 healthy pain-free individuals that were collected in the context of a previous study. The results showed mean index values of lower than 30 and higher than 90 for the most relevant phases of the squat and stoop movements, respectively, with mean index values differing significantly from each other for the full duration of the lifting phases. The main advantages of the index are that it is simple to calculate and can not only be derived from motion capture data but also from conventional video recordings, which enables large-scale in-field measurements with relatively low expenditure. When used in combination with lumbar spine flexion measurements, the index can contribute important information, which is necessary for comprehensively evaluating whole-body lifting strategies and to shed more light on the debate over the connection between lifting posture and back complaints.
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Lifting up objects from the floor has been identified as a risk factor for low back pain, whereby a flexed spine during lifting is often associated with producing higher loads in the lumbar spine. Even though recent biomechanical studies challenge these assumptions, conclusive evidence is still lacking. This study therefore aimed at comparing lumbar loads among different lifting styles using a comprehensive state-of-the-art motion capture-driven musculoskeletal modeling approach. Thirty healthy pain-free individuals were enrolled in this study and asked to repetitively lift a 15 kg-box by applying 1) a freestyle, 2) a squat and 3) a stoop lifting technique. Whole-body kinematics were recorded using an optical motion capture system and used to drive a full-body musculoskeletal model including a detailed thoracolumbar spine. Compressive, shear and total loads were calculated based on a static optimization approach and expressed as factor body weight (BW). In addition, lumbar lordosis angles and total lifting time were calculated. All parameters were compared among the lifting styles using a repeated measures design. For all lumbar segments, stoop lifting showed significantly lower compressive and total loads (-0.3 to -1.0BW) when compared to freestyle and squat lifting. Stoop lifting produced higher shear loads (+0.1 to +0.8BW) in the segments T12/L1 to L4/L5, but lower loads in L5/S1 (-0.2 to -0.4BW). Peak compressive and total loads during squat lifting occurred approximately 30% earlier in the lifting cycle compared to stoop lifting. Stoop lifting showed larger lumbar lordosis range of motion (35.9+/-10.1{deg}) than freestyle (24.2+/-7.3{deg}) and squat (25.1+/-8.2{deg}) lifting. Lifting time differed significantly with freestyle being executed the fastest (4.6+/-0.7s), followed by squat (4.9+/-0.7s) and stoop (5.9+/-1.1s).
To simplify the quantification of time irreversibility, we employ order patterns instead of the raw multi-dimension vectors in time series, and considering the existence of forbidden permutation, we propose a subtraction-based parameter, Ys, to measure the probabilistic differences between symmetric permutations for time irreversibility. Two chaotic models, the logistic and Henon systems, and reversible Gaussian process and their surrogate data are used to validate the time-irreversible measure, and time irreversibility of epileptic EEGs from Nanjing General Hospital is detected by the parameter. Test results prove that it is promising to quantify time irreversibility by measuring the subtraction-based probabilistic differences between symmetric order patterns, and our findings highlight the manifestation of nonlinearity of whether healthy or diseased EEGs and suggest that the epilepsy leads to a decline in the nonlinearity of brain electrical activities during seize-free intervals.
Musculoskeletal models have the potential to improve diagnosis and optimize clinical treatment by predicting accurate outcomes on an individual basis. However, the subject-specific modeling of spinal alignment is often strongly simplified or is based on radiographic assessments, exposing subjects to unnecessary radiation. We therefore developed a novel skin marker-based approach for modeling subject-specific spinal alignment and evaluated its feasibility by comparing the predicted with the actual intervertebral joint (IVJ) locations/orientations (ground truth) using lateral-view radiographic images. Moreover, the predictive performance of the subject-specific models was evaluated by comparing the predicted L1/L2 spinal loads during various functional activities with in vivo measured data obtained from the OrthoLoad database. IVJ locations/orientations were predicted closer to ground truth as opposed to standard model scaling, with average location prediction errors of 0.99+/-0.68 cm on the frontal and 1.21+/-0.97 cm on the transverse axis as well as an average orientation prediction error of 4.74{deg}+/-2.80{deg}. Simulated spinal loads showed similar curve patterns but considerably larger values as compared to in vivo measured data. Differences in spinal loads between generic and subject-specific models become only apparent on an individual subject level. These results underline the feasibility of the proposed method and associated workflow for inter- and intra-subject investigations using musculoskeletal simulations. When implemented into standard model scaling workflows, it is expected to improve the accuracy of muscle activity and joint loading simulations, which is crucial for investigations of treatment effects or pathology-dependent deviations.
The pathogenesis of adolescent idiopathic scoliosis (AIS) remains poorly understood and biomechanical data are limited. A deeper insight into spinal loading could provide valuable information for the improvement of current treatment strategies. This work therefore aimed at using subject-specific musculoskeletal full-body models of patients with AIS to predict segmental compressive forces around the curve apex and to investigate how these forces are affected by simulated load carrying. Models were created based on spatially calibrated biplanar radiographic images from 24 patients with mild to moderate AIS and validated by comparing predictions of paravertebral muscle activity with reported values from in vivo studies. Spinal compressive forces were predicted during unloaded upright standing as well as upright standing with external loads of 10%, 15% and 20% of body weight (BW) applied to the scapulae to simulate carrying a backpack in the regular way, in front of the body and over both shoulders. The validation studies showed higher convex muscle activity, which was comparable to the literature. The implementation of spinal deformity resulted in a 10% increase of compressive force at the curve apex during unloaded upright standing. Apical compressive forces further increased by 50-62%, 77-94% and 103-128% for 10%, 15% and 20% BW loads, respectively. Moreover, load-dependent compressive force increases were the lowest in the regular backpack and the highest in the frontpack and convex conditions. The predictions indicated increased segmental compressive forces during unloaded standing, which could be ascribed to the scoliotic deformation. When carrying loads, compressive forces further increased depending on the carrying mode and the weight of the load. These results can be used as a basis for further studies investigating segmental loading in AIS patients during functional activities.
Non-specific chronic low back pain (NSCLBP) is a major health problem, affecting about one fifth of the population worldwide. To avoid further pain or injury, patients with NSCLBP seem to adopt a stiffer movement pattern during everyday living activities. However, it remains unknown how NSCLBP affects the lumbar lordosis angle (LLA) during repetitive activities such as walking or running. This pilot study therefore aimed at exploring possible NSCLBP-related alterations in LLAs during walking and running by focusing on discrete parameters as well as continuous data. Thirteen patients with NSCLBP and 20 healthy pain-free controls were enrolled and underwent a full-body movement analysis involving various everyday living activities such as standing, walking and running. LLAs were derived from markers placed on the spinous processes of the vertebrae L1-L5 and S1. Possible group differences in discrete (average and range of motion (ROM)) and continuous LLAs were analyzed descriptively using mean differences with confidence intervals ranging from 95% to 75%. Patients with NSCLBP indicated reduced average LLAs during standing, walking and running and a tendency for lower LLA-ROM during walking. Analyses of continuous data indicated the largest group differences occurring around 25% and 70% of the walking and 25% and 75% of the running cycle. Furthermore, patients indicated a reversed movement pattern during running, with increasing instead of a decreasing LLAs after foot strike. This study provides preliminary evidence that NSCLBP might affect LLAs during walking and running. These results can be used as a basis for future large-scale investigations involving hypothesis testing.
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