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).
fragments of sections
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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