From Stoop to Squat: A Comprehensive Analysis of Lumbar Loading Among Different Lifting Styles

Abstract

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 a 16-camera optical motion capture system and used to drive a full-body musculoskeletal model including a detailed thoracolumbar spine. Continuous as well as peak compressive, anterior-posterior shear and total loads (resultant load vector of the compressive and shear load vectors) 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 each lifting style, loads increased towards the caudal end of the lumbar spine. 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°) than freestyle (24.2 ± 7.3°) and squat (25.1 ± 8.2°) lifting. Lifting time differed significantly with freestyle being executed the fastest (4.6 ± 0.7 s), followed by squat (4.9 ± 0.7 s) and stoop (5.9 ± 1.1 s). Stoop lifting produced lower total and compressive lumbar loads than squat lifting. Shear loads were generally higher during stoop lifting, except for the L5/S1 segment, where anterior shear loads were higher during squat lifting. Lifting time was identified as another important factor, considering that slower speeds seem to result in lower loads.

Benchmarking commercially available soft and rigid passive back exoskeletons for an industrial workplace

“…Muscle activity reductions were on average 19.0 and 17.7% for the Asymmetric and Stoop tasks, respectively, which were comparable to findings in literature (Schmalz et al, 2022 ). Paexo is effective for stooping, although this movement results in higher low-back shear loads (von Arx et al, 2021 ).…”

The Stoop-Squat-Index: a simple but powerful measure for quantifying whole-body lifting behavior

“…To enable the interpretation of the Stoop-Squat-Index in a real-life setting, normative values were established using pre-processed motion capture data (i.e., labeled and filtered three-dimensional trajectories of 58 retroreflective skin markers recorded with a 16-camera Vicon motion capture system) from a sample of 30 healthy pain-free individuals that underwent motion analysis during lifting a moderately-weighted object (15-kg-box) with a full squat and a full stoop lifting technique in the context of a previously conducted and published study [8]. This sample consisted of 20 males and 10 females with a mean age of 31.8 ± 8.5 years and a mean BMI of 23.3 ± 2.4 kg/m 2 , which were recruited by flyer from the personal and workplace environment of the investigators of this previous study.…”

Lower Limb Muscle Co-Activation Maps in Single and Team Lifting at Different Risk Levels

“…For all these reasons, there is a need to better study the behavior of the lower limbs during the execution of heavy lifting activities in an occupational context. Indeed, a correct motor execution of the lower limbs during lifting allows for less overload of the spine [44][45][46]. Furthermore, global co-activation of lower limb muscles could be used as an index in instrumental risk assessment methods and to train machine learning algorithms for automated risk level estimation.…”