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Abstract

Spinal Force In biomechanics investigations, division normalization is frequently used to eliminate the impact of anthropometric variations (such as body weight) on kinetic variables, permitting comparison across a population. In spine biomechanics, the intervertebral load or body weight during a standing posture is frequently used to split the spinal forces. To normalize kinetic variables, such as ground reaction forces during walking and running, offset and power curve normalisation have been recommended to be more appropriate than division normalisation.

 The Spinal Force current study looked into four methods for normalizing spinal stresses to offset the impact of body weight for the first time. A thorough OpenSim musculoskeletal model of the spine was used to calculate the spinal forces at all lumbar levels for 11 scaled models (50–100 kg) and 13 trunk flexion activities. The effectiveness of each normalization procedure was evaluated using Pearson correlations of the raw and normalized forces versus body weight. Body weight normalization and standing division normalisation were only able to successfully normalize L4L5 spinal forces in three tasks and L5S1 loads in five and three tasks, respectively.

Spinal Force offset and power curve normalization techniques were effective for all lumbar spine levels and tasks. Offset normalisation effectively eliminates the impact of body weight while keeping the flexion angle's bearing on spinal forces. Thus, we advise offset normalization to take anthropometric variations into account in spinal force experiments.

Introduction

Anthropometric factors have a significant impact on ground reaction forces (GRF), intersegmental forces, and other kinetic variables in biomechanics investigations. To eliminate the impacts of participant anthropometric disparities acting as confounding factors, kinetic variables are frequently standardised by anthropometric characteristics such as body weight (BW) and height (Derrick et al., 2020). For instance, non-dimensional normalisation has been suggested for normalising data in clinical gait analysis, where each variable is divided by combinations of body mass, leg length, and gravitational acceleration Although normalisation appears to be a harmless data analysis technique, it is important to take into   account its impacts since normalisation might alter how results are viewed. For instance,

in studies on the risk of anterior cruciate ligament injury, adjusting the knee abduction moment might have a considerable impact on how group comparisons are interpreted (Norcross et al., 2017). Determining the best appropriate methodology for normalising each biomechanical variable is crucial since different normalisation methods may have varied effects on the outcomes and findings of a study.

Spinal Force joint forces are of interest in many studies of spine biomechanics because these loads significantly contribute to the aetiology of back, and height are the four individual variables that have been proven to have the largest impact on spinal burdens Therefore, previous studies have frequently simply divided the measured or estimated spinal forces by Spinal Force  Favier et al., 2021; or divided the spinal forces by the intervertebral load during a neutral, unloaded, standing posture to eliminate the influence In the current investigation, these two division normalisation methods—sometimes referred to as "ratio scaling" in the literature—will be abbreviated BW Division Normalization (BWDN) and Standing Division Normalization (SDN).

For GRF, the Spinal Force impacts of various normalisation methods have mostly been studied while walking and running (Wannop et al., 2012). (Stickley et al., 2018). These studies' findings indicated that BWDN was not the most effective method for normalising GRF because the normalised GRF values had a strong association with BW. In other words, even with BWDN, BW still accounted for a sizable percentage of the variance in the normalised data. Offset and power curve normalisation, which is also known as "allometric scaling" in the literature, have been shown to be more suitable for normalising GRF (Stickley et al., 2018, Wannop et al., 2012). To the best of the authors' knowledge, no studies have compared the effects of different normalisation methods on spinal forces. In this study, we investigate the suitability of BWDN, SDN, BW Offset Normalization (BWON), and BW Power Curve Normalization (BWPCN) for normalising spinal forces in flexed and upright postures.

Notwithstanding the similarities with GRFs during walking that were mentioned above, studying spinal forces can be more challenging due to a lack of experimental data. In particular, spinal force measurements utilising instrumented vertebral body implants are only accessible for a small number of individuals (L1 level: four patients, 66 4 kg; L3 level: one patient, 66 kg) due to their invasiveness and complexity (Rohlmann et al., 2014). Consequently, one may use musculoskeletal modelling, which is frequently used to predict spinal joint forces, to assess the performance of various normalising strategies over a large range of BW (Akhavanfar et al., 2019).

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Modeli the skeleton in humans

In various modelling systems, several intricate musculoskeletal models of the spine have been created and verified (et al., 2018, et al., 2018, et al., 2017, -Gauvreau et al., 2019, Bruno et al., 2015, et al., 2018). We chose the fully articulated thoracolumbar spine (FATLS) model (Bruno et al., 2015) to calculate spinal loads for this investigation for a number of different reasons. First off, this model was created in and is an open-access model.

Results

With BW ranging from 490 N to 980 N, Figure 1 compares the initial resulting L1L2 spinal forces from our model with the spinal forces following normalisation using each of the four strategies mentioned above. For all flexion tasks, there was a substantial positive correlation between raw resulting forces at all lumbar spinal levels and BW. The Supplemental Information contains the Pearson correlation coefficients between BW and resulting forces (raw and normalised) for all levels of the lumbar spine. once BWDN and

Discussion

Normalizing variables is vital in Spinal Force  to reduce the variance across individuals (Derrick et al., 2020), thereby presenting generalizable conclusions. In many spine biomechanics investigations, spinal stresses during actions requiring trunk flexion are of interest (e.g., squat and stoop lifting tasks). Hence, in order to normalise spinal stresses during static flexion exercises, we investigated four different methods. BW is recognised to have the highest impact on spinal forces of individualised parameters

Contribution statement for authors using credit

First-person writing, Software, Methodology, Validation, and Investigation. Thomas K. Uchida: Supervision, Writing, Review, and Editing. Ryan B. Graham: Editing, Supervision, and Writing.

Conflict of Interest Statement

The authors affirm that they have no known financial or interpersonal conflicts that would have appeared to have an impact on the research presented in this study.

Acknowledgments

The Natural Sciences and Engineering Research Council of Canada provided funding for this work (PGSD3-518358-2018 [Mohammadhossein Akhavanfar], RGPIN-2020-04748 [Ryan Graham]).

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