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. Author manuscript; available in PMC: 2023 Apr 1.
Published in final edited form as: J Biomech. 2022 Mar 12;135:111048. doi: 10.1016/j.jbiomech.2022.111048

Effect of Simulated Changes in Pelvic Tilt on Hip Joint Forces

Karim K Ismail 1, Cara L Lewis 2
PMCID: PMC9255277  NIHMSID: NIHMS1791436  PMID: 35325751

Abstract

Musculoskeletal modeling is commonly used to simulate and compare various movements between individuals. For conditions such as femoroacetabular impingement syndrome (FAIS), individuals tend to walk with more anterior pelvic tilt than those without FAIS. However, it is unknown whether accounting for pelvic tilt in musculoskeletal modeling would lead to a change in muscle forces and in turn, joint forces. Gait data of six individuals were collected and processed using Vicon and Visual3D. Each participant’s pelvic tilt was adjusted by ±10° at all time points during gait. Three analyses were performed per individual: no adjustment in tilt, one posterior (positive) tilt, and one anterior (negative) tilt. The resulting data were imported into OpenSim to determine muscle forces and the resulting femur-on-acetabulum (hip joint) forces in the pelvic and femoral reference frames. Data for each participant were normalized for gait cycle and body weight in MATLAB, and statistical parametric mapping was used to determine if the differences in joint and muscle forces were significant across different pelvic orientations. Shifting from posterior to anterior pelvic tilt reduced resultant forces. In the pelvic reference frame, anteriorly-directed joint forces decreased, while medially-directed forces increased. In the femoral reference frame, anteriorly- and medially-directed joint forces increased, while superiorly-directed forces decreased. Anterior gluteus medius and iliacus muscle forces decreased, while quadratus femoris, piriformis, and gemellus muscle forces increased. Given these results, future studies using musculoskeletal modeling should account for pelvic tilt in musculoskeletal models to obtain more realistic comparisons between healthy and pathological conditions.

Keywords: Opensim, musculoskeletal modeling, pelvic tilt, hip pain, walking

1. Introduction

Musculoskeletal modeling is increasingly used to predict kinematics, kinetics, muscle forces, and joint forces of various movements. Previous modeling approaches, however, may assume that a person stands in an entirely neutral position. In turn, information on parameters that potentially affect muscle and joint forces (such as pelvic tilt) is lost in kinematic data, which may affect simulations of people with conditions such as femoroacetabular impingement syndrome (FAIS), who walk with more anterior pelvic tilt (Brown-Taylor et al., 2020; Lewis et al., 2018) than those without FAIS. The goal of this study was to observe the effect of computationally-altered pelvic tilt on hip joint and muscle forces during gait.

2. Materials and Methods

2.1. Participants

Gait data of six individuals from a previous study (Lewis et al., 2021) were used (Table 1). All participants were between ages 14 and 50 and walked without assistive devices. Individuals with a history of back or hip surgery, neurological disorder, and/or current back or lower extremity pain/injury were excluded. All individuals participated in the study voluntarily and provided written informed consent, as approved by the Boston University Institutional Review Board.

Table 1:

Demographic data of all participants in the study.

Number of participants 6
Height (m) ± SD 1.71 ± 0.1
Mass (kg) ± SD 69.3 ± 6.9
BMI (kg/m 2 ) ± SD 23.6 ± 4.0
Walking speed 1.25 m/s
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2.2. Instrumentation

Whole-body kinematic data were recorded from markers placed over bony landmarks on the trunk, pelvis, and lower extremities and from marker clusters on the thighs and shanks (Lewis et al., 2015), using a 10-camera motion capture system (Vicon Motion Systems Ltd. Centennial, CO, USA) sampling at 100Hz. Participants walked on a split-belt treadmill (Bertec Corp, Columbus, OH) which recorded ground reaction force (GRF) data at 1000Hz. Motion and GRF data were filtered through a low-pass, fourth-order Butterworth filter with 6Hz and 10Hz cutoff frequencies, respectively (Lewis et al., 2018).

2.3. Conditions

Participants walked at the average pedestrian speed of 1.25m/s (Silva et al., 2014). Virtual markers for the pelvis were created in Visual3D (C-Motion, Inc., Rockville, MD) above the right and left greater trochanters. A marker pair was placed 0.1m directly superior to the greater trochanters to define the baseline pelvic orientation (0° tilt), representing the model before adjustment and assuming a neutral standing position. Marker pairs were created posterior and anterior to the virtual markers to define the +10° and −10° adjustments (Figure 1), respectively. The virtual marker coordinates were defined as the sine of the desired angle in the anterior-posterior direction and the cosine of the angle in the superior-inferior direction (Table 2) (Pelvis Overview-Visual3D Wiki Documentation, 2014). Anatomical segments were scaled based on marker locations, and joint motion tracked with Inverse Kinematics (Inverse Kinematics-Visual3D Wiki Documentation, 2016; Lu & O’Connor, 1999). The 10° changes were ~1.5 times the observed pelvic angle standard deviation (6.3°) in the larger dataset (Lewis et al., 2021). Such changes are commonly observed and large enough to represent clinically appreciable differences.

Figure 1:

Figure 1:

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Simulated pelvic orientations in Visual3D. The blue sphere represents the virtual greater trochanter marker. The white spheres represent the ilium markers.

Table 2:

Coordinates (in meters) for creation of virtual markers above the greater trochanters for each pelvic orientation in Visual3D. While the angles above are expressed in degrees, the units in Visual3D are expressed in radians.

Desired Pelvic Orientation Coordinates in Visual3D
X (m) (Medial-Lateral) Y (m) (Anterior-Posterior) Z (m) (Superior-Inferior)
+10° tilt (Posterior) 0 −0.1 × sin(10°) 0.1 × cos(10°)
0° tilt (No
adjustment) 		0 0 0.1
−10° tilt (Anterior) 0 0.1 × sin(10°) 0.1 × cos(10°)
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Muscle and joint force calculations were performed for each participant for each pelvic orientation. While 10° pelvic shifts were achieved in Visual3D, the shift in the exported data was less precise due to the enforcement of the inverse kinematic chain.

2.4. Data Acquisition and Processing

Scaling, kinematic, and GRF data from Visual3D were imported into OpenSim 3.2. A 23 degree-of-freedom, 92-actuator musculoskeletal model (“Gait2392”) was scaled based on calculations from Visual3D. The Residual Reduction Algorithm (RRA) tool was used; the mass distribution was altered and RRA rerun until residual forces and moments were less than 10N and 50Nm, respectively (Hicks et al., 2014). To calculate muscle forces, the Computed Muscle Control (CMC) (Anderson & Thelen, 2006) tool was used. RRA and CMC results were used in the JointReaction Tool (Steele et al., 2012) to estimate femur-on-acetabulum forces in the anterior, superior, and medial directions in the pelvic and femoral reference frames. The resultant force was the vector sum of forces in the 3 directions, and thus independent of the reference frame.

2.5. Data Analysis

The resulting data were split into strides and normalized from heel-strike (0% gait cycle) to ipsilateral heel-strike (100% gait cycle). At least five strides from each leg were used for each participant. Data were averaged over all strides for each leg. The resulting forces of the right and left legs were averaged and adjusted for each participant’s body weight in MATLAB (The MathWorks Inc., Natick, MA, USA).

Statistical parametric mapping (SPM) (Pataky, 2010) was used to compare average joint and muscle forces between different pelvic orientations. An SPM repeated-measurement ANOVA test was used to compare differences across all three pelvic orientations, followed by paired t-tests to compare differences between the unaltered and altered pelvic orientations. SPM uses random field theory to make statistical inferences about the likelihood of observed differences between curves occurring by chance at each 1% of the gait cycle. A threshold is determined based on the smoothness of the curves, and is the value beyond which less than 5% of the data are expected to reach by chance (α=0.05). Regions where the difference between curves exceeds the threshold are statistically significant. SPM analyses were performed using the open-source spm1d code (M.0.4.7, www.spm1d.org) in MATLAB.

3. Results

All simulations of kinematic and kinetic data were similar to the experimental walking data. The average RMS residual forces and moments were less than 0.2% body weight (BW) and 0.6% BW×Height respectively; all residuals were below the suggested thresholds (Hicks et al., 2014) and consistent with prior studies (Samaan et al., 2019, Weinhandl et al., 2017). The resultant and pelvic reference frame joint force curves were similar to prior literature in shape and magnitude (Ng et al., 2018; Valente et al., 2013; Weinhandl et al., 2017). Peak anteriorly-directed forces were 2–4×BW, superiorly-directed forces (during late stance) were ~4×BW, medially-directed forces were 0–1×BW, and peak resultant forces were 4–5×BW, all consistent with prior literature (Ng et al., 2018; Valente et al., 2013; Weinhandl et al., 2017). The computed muscle force patterns were similar to both measured (Samaan et al., 2019, Semciw et al., 2013; Valente et al., 2013) and estimated (Samaan et al., 2019; Valente et al., 2013; Weinhandl et al., 2017) muscle activations in terms of timing and magnitude of peak muscle activity (Samaan et al., 2019).

3.1. Resultant Force

Shifting from posterior to anterior pelvic tilt reduced resultant forces (Figure 2). The differences between all three curves exceeded the critical threshold during mid- to terminal stance (27.4%–31.9% gait cycle, p=.008), pre-swing (51.5%–57.2% gait cycle, p=.003), and initial swing (62.8%–63.2% and 64.4%–68.0% gait cycle, p=.049, and p=.016, respectively).

Figure 2:

Figure 2:

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Resultant hip joint forces (femur to acetabulum), averaged across all six participants. Shaded areas indicate regions of statistical significance (p<0.05) across all three pelvic orientations, determined by the repeated-measurements ANOVA test.

3.2. Pelvic Reference Frame Forces

In the pelvic reference frame, shifting from posterior to anterior tilt (which also shifts the reference frame) reduced anterior hip joint forces (Figure 3A) during all of gait (p<.001). No systematic shift was noticed in the superiorly-directed joint forces (Figure 3B), although the threshold was briefly exceeded during pre-swing (56.9%–57.2% gait cycle, p=.050). The medially-directed forces (Figure 3C) were increased from loading response to pre-swing (6.3%–59.8% gait cycle, p<.001), and between mid-swing and terminal swing (76.6%–91.8% gait cycle, p<.001).

Figure 3:

Figure 3:

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A) anterior, B) superior, and C) medial hip joint forces (femur to acetabulum), averaged across all six participants for each pelvic orientation in the pelvic reference frame. D) Location of the pelvic reference frame. Shaded areas indicate regions of statistical significance (p<0.05) across all three pelvic orientations, determined by the SPM repeated-measurements ANOVA test.

3.3. Femoral Reference Frame Forces

In the femoral reference frame, shifting from posterior to anterior tilt increased anterior joint forces (Figure 4A) during mid-stance (15.1%–20.0% gait cycle, p=.002), terminal stance (34.1%–53.5% gait cycle, p<.001), pre-swing (58.9%–59.1% gait cycle, p=.050), and terminal swing (80.2%–81.4% gait cycle, p=.041). The superiorly-directed forces (Figure 4B) decreased during mid- to terminal stance (29.4%–31.3% gait cycle, p=.037), pre-swing (49.6%–58.1% gait cycle, p<.001), and initial swing (62.4%–63.3% and 64.5%–68.5% gait cycle, p≤.047). The medial forces (Figure 4C) increased between loading response and mid-stance (6.0%–9.9% and 10.1%–21.0% gait cycle, p≤.016), between terminal stance and pre-swing (31.1%–59.3% gait cycle, p<.001), and between mid-swing and terminal swing (76.4%–91.1% gait cycle, p<.001).

Figure 4:

Figure 4:

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A) anterior, B) superior, and C) medial hip joint forces (femur to acetabulum), averaged across all six participants for each pelvic orientation in the femoral reference frame. D) Location of the femoral reference frame. Shaded areas indicate regions of statistical significance (p<0.05) across all three pelvic orientations, determined by the SPM repeated-measurements ANOVA test.

3.4. Muscle Forces

With different pelvic adjustments, muscles changed their activity levels, contributing to the observed changes in joint forces. Examples include the anterior gluteus medius, iliacus, and psoas, which were implicated in changes in peak anterior hip forces (Lewis et al., 2007, 2010). Shifting from posterior to anterior tilt reduced anterior gluteus medius forces (Figure 5A) during loading response and mid-stance (0%–13.2% gait cycle, p<.001), during initial swing (66.1%–68.3% gait cycle, p=.031), and between mid-swing and terminal swing (77.8%–100% gait cycle, p<.001). The iliacus forces (Figure 5B) decreased between mid-stance and terminal stance (20.7%–35.2% gait cycle, p<.001), during pre-swing (49.6%–57.6% and 59.2%–60.5% gait cycle, p≤.04), and briefly during terminal swing (80.9%–81.4% gait cycle, p=0.05). The psoas forces (Figure 5C) were comparable throughout gait.

Figure 5:

Figure 5:

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Forces of the A) anterior gluteus medius, B) iliacus, and C) psoas muscles. Shaded area indicate regions of statistical significance (p < 0.05) across all three pelvic orientations, determined by the repeated-measurements ANOVA test.

Muscles that may explain the increased medially-directed joint forces include the quadratus femoris, piriformis, and gemellus; these muscles impart some of their force in the medial-lateral direction (Neumann, 2010). Shifting from posterior to anterior tilt increased quadratus femoris force (Figure 6A) during loading response (2.1%–3.3%, 6.6%–8.2% gait cycle, p≤.04) and most of swing (63.5%–91.7%, 95.7%–100% gait cycle, p≤0.001). There was a brief decrease during mid-stance (26.7%–29.0% gait cycle, p=.014). The piriformis force (Figure 6B) increased during all phases of gait (p<.001), except initial swing (59.9%–69.3% gait cycle). The gemellus force (Figure 6C) increased during loading response (2.7%–3.2%, 4.5%–8.8% gait cycle, p≤.049), during mid-stance stance (9.3%–27.3% gait cycle, p<.001), during mid- to terminal swing (74.7%–90.9% gait cycle, p<.001), and near heel-strike (99.4%–100% gait cycle, p=.048).

Figure 6:

Figure 6:

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Forces of the A) quadratus femoris, B) piriformis, and C) gemellus muscles. Shaded area indicate regions of statistical significance (p < 0.05) across all three pelvic orientations, determined by the repeated-measurements ANOVA test.

4. Discussion

Our results demonstrate that computationally changing pelvic orientation affects joint forces. In the pelvic reference frame, a more anterior pelvic tilt reduced anteriorly-directed joint forces during all of gait, and increased medially-directed forces in specific phases. Thus, changing pelvic tilt is a possible intervention to address pathological conditions and reduce hip pain. Pain may result from excessive anteriorly-directed joint forces onto the acetabulum (Lewis et al., 2010); increasing anterior tilt may reduce those forces. One can also increase posterior tilt to reduce medially-directed forces, although the therapeutic indications are unexplored. It is unclear what adjustment is most effective at addressing pathological conditions, and different individuals may benefit from different interventions. Moreover, intentionally changing pelvic tilt (rather than simulating the change) may result in different findings; further research is needed to assess these possibilities.

Our findings can be compared to other interventions that affect joint forces. For example, reducing walking speed by 10% reduced peak anterior joint forces by 8.2% (Weinhandl et al., 2017) whereas shifting the pelvis from neutral to 10°an anterior tilt reduced the peak anterior force by 29.3%. Shifting from posterior to anterior pelvic tilt had a similar reduction on the peak resultant force as changing from fast walking to slow walking (8.9% and 9.6%, respectively) (Weinhandl et al., 2017).

Altering pelvic tilt affected forces in the pelvic reference frame differently than in the femoral reference frame. In the pelvic reference frame, the observed change in forces was due to both the shift in the reference frame and the change in muscle orientation. In the femoral reference frame, the change was only due to muscle orientation. Observing forces from both reference frame perspectives also elucidates how the forces relate to areas of cartilage damage. Cartilage damage has been reported in the anterosuperior region of the acetabulum (Beaulé et al., 2012; Beck et al., 2005) and the femur (Jannelli et al., 2019; Kapron et al., 2019) in people with FAIS. While the anterosuperior regions of the acetabulum and femur are likely adjacent in standing, their relative position will change throughout the gait cycle, underscoring the need to observe loads from different perspectives.

Changes in joint forces were due to changes in estimated muscle forces, not changes in joint moments. Joint moments were unchanged between different pelvic orientations, as the joint center and GRFs were unchanged with each adjustment. Therefore, increases in some muscle forces with anterior pelvic adjustment coincide with decreases in muscle moment arms to maintain the same moment. For instance, when shifting from posterior to anterior tilt, the magnitude of the piriformis hip rotation moment arm decreased as muscle force increased, and likely contributed to increased medial forces. Further study is necessary to determine which muscles are most affected by modification in pelvic position.

One limitation is the use of the same generic musculoskeletal model for all participants, despite potential differences in lower-limb neuromuscular anatomy (Alexander, 1997; Fox, 1991; Lewis et al., 2017) between sexes. Person-specific musculoskeletal models could be created from computed tomography scans, but these are typically unavailable. While more recent models (Rajagopal et al., 2016) exist, the commonly-used Gait2392 model allows for comparison with and interpretation of muscle/joint forces from prior literature (Valente et al., 2018; Ng et al., 2018). Also, adjusting for body weight does not account for differences in fat and muscle distribution in lower limbs, which may lead to different gait patterns between participants.

5. Conclusions

Pelvic tilt affects joint and muscle forces in different manners and should be considered in future analyses to better understand the role of body orientation when analyzing musculoskeletal conditions. Our findings can be applied in the comparison of muscle/joint forces of people with and without FAIS, the study of gait alteration strategies, and the use of finite-element simulations to model hip morphologies.

Acknowledgments

Research reported in this paper was supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under Award Numbers R21AR061690 and K23AR063235. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

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