Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Jul 19.
Published in final edited form as: J Biomech. 2021 Jun 11;124:110565. doi: 10.1016/j.jbiomech.2021.110565

Frontal Plane Ankle Stiffness Increases with Weight-Bearing

Marie Matos 1,2,3, Eric J Perreault 1,2,4, Daniel Ludvig 1,2,*
PMCID: PMC8569913  NIHMSID: NIHMS1717571  PMID: 34167018

Abstract

Ankle sprains are among the most common musculoskeletal injuries. They are not isolated innocuous injuries as 30–40% of people who sprain their ankles develop chronic ankle instability. Ankle instability is typically assessed under passive unloaded conditions, ignoring any potential contribution of joint loading or muscle activation to the maintenance of ankle stability. Thus, the relevance of unloaded ankle stability assessments to the evaluation of impairments in chronic ankle instability or the prediction of future ankle sprains is questionable. Ankle impedance, which quantifies the resistance to an imposed rotation, has often been used to quantify ankle stability. However, few studies have investigated impedance in the frontal plane where sprains occur, and none have systematically investigated the effect of weight-bearing on ankle impedance. The objective of this study was to determine whether weight-bearing affects frontal plane ankle impedance. We had subjects systematically alter the weight on the tested ankle, while imposed frontal plane rotations were applied to estimate the impedance. We found that ankle stiffness, the static component of impedance, increased proportionally with the weight on the ankle. This increase in stiffness was due to a combination of the increase loading on the joint and the increase in muscle activation that occurs during weight-bearing. Finally, we found that men had a greater stiffness than women over the majority of the weight-bearing range. These results highlight the importance of clinically assessing ankle stability during weight-bearing conditions to better determine the impairments in chronic ankle instability and identify those at risk for ankle sprains.

Keywords: Ankle Stiffness, Weight-Bearing, Ankle Instability, Ankle Sprains

Introduction

Ankle sprains are one of the most common musculoskeletal injuries, with approximately 2000 people treated per day in U.S. emergency rooms (Waterman et al., 2010). The prevalence of ankle sprains is likely even higher, as about 55% of those who sustain a sprain do not seek medical treatment (McKay et al., 2001). Not all ankle sprains are isolated innocuous injuries. Instead 30–40% of people who sprain their ankles suffer from chronic ankle instability (CAI) (Anandacoomarasamy and Barnsley, 2005; Freeman, 1965; Gerber et al., 1998; Korkala et al., 1987; Verhagen et al., 1995). People with CAI may live with daily pain (Arnold et al., 2011), suffer frequent recurrent sprains (Anandacoomarasamy and Barnsley, 2005; Beynnon et al., 2002; Korkala et al., 1987), and are at greater risk of developing ankle osteoarthritis (Valderrabano et al., 2006).

While a number of mechanisms have been suggested as the underlying impairment contributing to CAI, the extent to which impairments in these mechanisms destabilizes the ankle remains unknown. The ankle is stabilized by passive structures including ligaments, the geometry of the articular surfaces (Watanabe et al., 2012), tendons and passive muscles as well as through active stabilization generated by active muscle contractions (Konradsen, 2002). Chronic ankle instability has been associated with damage to ligaments (Hubbard and Hertel, 2006), altered articular surface geometry (Magerkurth et al., 2010), weakened muscles (Arnold et al., 2009) and altered patterns of muscle contractions (Hertel, 2008). However, it remains unknown whether and to what extent damage to passive structure and improper muscle activation affect ankle stability. A major reason for this uncertainty is in the challenge of quantifying ankle stability during the conditions in which sprains occur. Typical clinical assessments for ankle instability, quantify ankle laxity under relaxed, non-weight-bearing conditions (Docherty and Rybak-Webb, 2009; Hubbard et al., 2004; Kovaleski et al., 1999; Liu et al., 2001). Since these assessments are done under relaxed non-weight-bearing conditions, these measures will miss any contributions to stability from passive weight-bearing or active components that are present during the conditions in which sprains occur.

One approach that has been used to quantify ankle stability during weight-bearing and active muscle conditions is to estimate the impedance of the ankle. These studies measured the resistive torque the ankle produced in response to imposed rotations, and quantified this relationship as the impedance (Kearney and Hunter, 1990). While ankle impedance has been extensively studied (Gottlieb and Agarwal, 1978; Hunter and Kearney, 1982; Lee et al., 2014a; Mirbagheri et al., 2000; Sinkjaer et al., 1988), only a few studies have quantified ankle impedance during the weight-bearing conditions in which sprains typically occur. Ankle impedance has been found to be greater during these weight-bearing conditions than during passive unloaded conditions (Amiri and Kearney, 2019; Casadio et al., 2005; Lee and Hogan, 2015; Loram and Lakie, 2002; Rouse et al., 2014; Sakanaka et al., 2018; Shorter and Rouse, 2018). However, these studies included multiple covariates (e.g. ankle posture, movement speed, muscle activation), all of which are known to affect ankle impedance (Ficanha et al., 2017; Mirbagheri et al., 2000; Weiss et al., 1988; Weiss et al., 1986a, b). Since none of these studies varied weight-bearing in a systematic matter, it is impossible to discern the effect of weight-bearing from these co-variates. Furthermore, all but one of these weight-bearing studies were performed in the sagittal plane, and 85% of ankle sprains occur with excessive rotation in the frontal plane (i.e. excessive inversion) (Ferran and Maffulli, 2006). Thus, it remains unknown how weight-bearing affects frontal plane ankle impedance, and hence whether passive unloaded measures of ankle impedance are relevant to the stability of the ankle during the functional conditions in which sprains occur.

The objective of this study was to determine whether weight-bearing affects frontal-plane ankle impedance. Our primary hypothesis was that impedance would increase with increasing weight placed on the ankle. We tested our hypothesis by having subjects place a percentage of their bodyweight on their right foot while frontal-plane ankle impedance was estimated. Frontal-plane impedance was estimated by applying small random rotations in the frontal plane via a robotic platform and measuring the resultant torque. Our results will demonstrate whether frontal-plane ankle impedance estimates generated during relaxed unloaded condition, are relevant to the ankle’s stability during the weight-bearing conditions in which sprains occur.

Methods

1. Subjects

Sixteen subjects (8 men and 8 women) participated and gave informed consent to the experimental protocol, which was approved by Northwestern University’s Institutional Review Board.

2. Apparatus

Subjects’ right feet were rigidly attached to a brushless AC rotary servomotor (BSM90N – 3150AF, Baldor. Fort Smith, AR, USA) using a subject-specific cast (Fig. 1). The axis of rotation of the motor was aligned with the frontal plane axis of rotation of the ankle (Brockett and Chapman, 2016). Subjects’ ankle angles were measured using an encoder integrated with the motor. Forces and torques about the ankle were measured using a 6 degree-of-freedom load cell (45E15A4, JR3, Woodland, CA, USA) rigidly secured in between the motor and the subjects’ feet. The forces and torques measured at the load cell were transformed to the center of the ankle, defined as the midpoint between the medial and lateral malleoli, using a Jacobian matrix transformation (Siciliano et al., 2010).

Figure 1.

Figure 1.

Open in a new tab

Schematic of experimental apparatus.

Electromyographic (EMG) activity was measured from 6 ankle muscles: tibialis anterior (TA), medial gastrocnemius (MG), lateral gastrocnemius (LG), soleus (SOL), peroneus longus (PL) and peroneus brevis (PB). These signals were amplified (Delsys Bagnoli™, Natick, MA, USA) by 1000x and bandpass filtered to 20–450 Hz.

All data were anti-alias filtered at 500 Hz using a 5-pole Bessel filter and then sampled at 2.5 kHz (PCI-DAS1602/16, Measurement Computing, Norton, MA, USA). Position data were recorded synchronously using a 24-bit quadrature encoder card (PCI-QUAD04, Measurement Computing, Norton, MA, USA). All data acquisition and motor control were performed using xPC target (The Mathworks Inc., Natick, MA, USA).

3. Protocol

The experiment was designed to measure frontal-plane ankle impedance under weight-bearing conditions. To do so, we configured the rotary motor as a stiff position servo, allowing us to precisely control the angle of the ankle in the frontal plane. Measurements were taken with the foot flat to the ground. Subjects were instructed to place a percentage of bodyweight (%BW, 10–90%, in 20% intervals) on the right foot aided by a visual feedback. The left foot was placed on an adjacent platform of the same height. Two trials of 65 seconds were run at each %BW while the ankle was perturbed, and the resultant forces and torques were measured, for a total of 10 trials. The order of trials was randomized for each subject. The perturbations consisted of a 0.03-rad pseudorandom binary sequence (PRBS) with a switching rate of 150 ms (Ludvig et al., 2017). Subjects were provided visual feedback showing the weight on the right foot and frontal plane torque. Subjects were asked to maintain the weight on the ankle and the frontal-plane torque constant throughout the trial. Both visual feedback signals were low-pass filtered at 1 Hz to prevent subjects from responding to the perturbations.

Prior to and following the perturbation trials, a number of control trials were run to obtain EMG values for normalization (Besomi et al., 2019) and impedance measures of the cast. Prior to the perturbation trials, maximum voluntary contractions (MVCs) were performed in all 6 directions (dorsi/plantarflexion, inversion/eversion, internal and external rotation). Following the perturbation trials, resting EMG was collected with the subject sitting in a chair and their leg supported so no weight was on the ankle. Additionally, 1 perturbation trial was collected with only the cast attached to the rotary motor, to estimate the impedance of the cast, and allow for its subsequent removal during data analysis.

4. Analysis

Estimation of ankle impedance

Ankle impedance was estimated by computing the relationship between the ankle angle and torque in the frontal plane. First, the data were decimated to 100 Hz. To remove the effect of body sway on torque—which could be an order of magnitude greater than the torque produced in response to the perturbation—we high-pass filtered the data at 0.25 Hz. This cut-off frequency was chosen as it was at least ten times less than the resonant frequency, as seen in our collected data, and would not hamper our ability to estimate the impedance of the ankle. Then we computed an impulse response function (IRF) that described the relationship between the imposed ankle displacement in the frontal plane and the frontal plane torque (Ludvig and Kearney, 2007; Ludvig and Perreault, 2012; Ludvig et al., 2017). Stiffness, the steady-state component of impedance was computed by integrating the non-parametric impedance IRF (Ludvig and Kearney, 2007; Ludvig et al., 2017). For comparison between subjects, stiffness was normalized by the bodyweight of the subjects.

To evaluate the quality of our estimated IRFs, we computed the torque variance that was accounted (%VAF) for by the IRFs

%VAF=(1−var(Tq−T^q)var(Tq))×100% (1)

where Tq is the high-pass filtered measured torque and T^q is the torque predicted by the impedance IRF.

EMG Analysis

EMG activity was measured to quantify changes in ankle muscle activity with increasing %BW. For each trial, the EMG activity of each muscle was 1) demeaned 2) rectified and 3) averaged across the entire duration of the trial (Besomi et al., 2019). This provided an average muscle activity throughout the trial. The EMG signals were normalized by subtracting off the resting EMG value and then dividing by the MVC EMG value. This resulted in EMG signals that ranged from 0% MVC representing the muscle at rest to 100% representing the muscle at maximum activity. One subject (male) was removed from the EMG analysis, due to poor recording of the EMG during MVCs

Statistical analysis

Our primary hypothesis was that frontal-plane ankle stiffness increases with increasing weight on the ankle. We tested this by computing a linear mixed-effects model with stiffness as the dependent variable, percentage of bodyweight, EMG activity and sex as independent continuous factors and subject as a random effect. The inclusion of EMG activity allowed us to determine if the changes in stiffness were due purely to muscle activity. The inclusion of sex allowed us to test whether there were differences between men and women. Significance, for all hypothesis, were determined using an α of 0.05.

Results

1. Estimation of impedance and stiffness

The torque in the frontal plane was accurately predicted by the impedance IRFs. A 10-s sample of data is shown in Fig. 2A–B. For this subject and trial, the torque predicted by the impedance IRF was a good match for the measured torque (%VAF = 89%). Overall the average %VAF was 89 ± 9% (mean ± SD). The impedance IRFs were more successful in predicting the torque at lower %BW than at higher %BW (Fig 2C), as there was a significant decrease in %VAF with %BW (slope = −0.11 ± 0.03 %VAF/%BW, p < 1×10−4). Though even at 90% of bodyweight, the impedance IRFs accounted for 83 ± 13%. This decrease in %VAF may be attributed to the contribution of sway to the measured torque. As weight on the ankle increases, the torque due to sway will increase, and cause a decrease in %VAF.

Figure 2.

Figure 2.

Open in a new tab

A) Ankle angle, and B) measured torque, and predicted torque for a 10-s sample from one subject. The predicted torque was a good fit for this trial accounting for 89% of the variance. C) Overall, the impedance IRFs accounted for on average 89% of the torque variance. This impedance was a better predictor of the torque at lower %BW, as %VAF dropped with increasing %BW. D) Our estimates of impedance resulted in reliable stiffness parameters that were consistent between repeated trials as the repeated estimates of stiffness were strongly correlated (r = 0.89, p < 1 ×10−8) with the initial estimates and distributed about the unity line (%VAF = 77%).

To assess the reliability of the stiffness estimates we compared the stiffness estimates generated by each of the repeated measures. The repeated estimates of stiffness were strongly correlated (r = 0.89, p < 1 ×10−8) and distributed about the unity line (%VAF = 77%; Fig. 2D), demonstrating the reliability of the stiffness estimates.

2. The effect of weight-bearing on stiffness

Frontal-plane ankle stiffness increased proportionally with increasing weight on the ankle. A linear model relating ankle stiffness to weight on the ankle was a good fit for an example subject shown in Fig. 3A (r2 = 0.82) as well as the entire group (r2 = 0.82). For both the example subject and the entire group (Fig. 3B), there was a significant increase in stiffness with increasing weight on the ankle (group: 0.053 ± 0.006 Nm/(rad N %BW), p < 1 × 10−8). On average, stiffness was 2.6 times greater at 50% of bodyweight (normal standing on two legs) and 4.1 times greater during full-weight bearing (equivalent to single-leg stance) than unloaded (0% BW) stiffness.

Figure 3.

Figure 3.

Open in a new tab

Frontal-plane ankle stiffness increased with increasing weight on the ankle. A) Stiffness estimates for one subject, showing how stiffness increased linearly with weight on the ankle. B) This trend was conserved when looking across all subjects using a linear mixed-effects model.

Frontal-plane ankle stiffness at full-weight bearing was not correlated with that estimated at unloaded conditions. To assess whether estimates of unloaded stiffness, as typically done in the clinic, are predictive of ankle stiffness during the weight-bearing conditions in which sprains typically occur, we examined the relationship between stiffness at 0% BW and that at 100% BW. Figure 4A shows two example subjects, who had similar unloaded (0% BW) stiffnesses, but had vastly different full-weight-bearing (100% BW) stiffnesses. Overall, we found no correlation between the estimated unloaded stiffness and that at full-weight bearing BW (r=0.07, p =0.79). Stiffness estimates at both 0% or 100% BW were derived from our linear model, and extrapolating these stiffness values to 0 and 100% may not be accurate. Thus we verified this correlation with the stiffness estimates generated directly from the data at 10% and 90% BW. Again, we found no correlation with stiffness estimated at 10% BW with that estimated at 90% BW (r=0.17, p =0.53). Thus, measures of stiffness generated under unloaded conditions were not predictive of ankle stiffness during weight-bearing conditions.

Figure 4.

Figure 4.

Open in a new tab

Unloaded ankle stiffness was not predictive of the stiffness at full-weight bearing. A) Two example subjects who had similar unloaded ankle stiffness (at 0% BW) but vastly different stiffness at full-weight bearing (100%). B) Across all subjects there was no correlation between unloaded stiffness and the stiffness at full-weight bearing. Each data point shows a measure of unloaded and full-weight-bearing stiffness for individual subject.

3. Influence of Muscle Activation

To explore the possibility that the increase in stiffness with increasing weight on the ankle was due to muscle activation, we quantified how muscle activity varied with weight on the ankle. EMG activity in 4 of the 6 recorded muscles increased significantly with increasing weight on the ankle (Fig. 5). MG (0.4 ± 0.1 %MVC/%BW, p = 0.001) and SOL (0.22 ± 0.07 %MVC/%BW, p = 0.002) had the largest increases with weight on the ankle. PL (0.08 ± 0.03 %MVC/%BW, p = 0.01) and PB (0.04 ± 0.02 %MVC/%BW, p = 0.04) had smaller increases, but were more consistent across subjects. LG also showed a small increase in activity (0.06 ± 0.03 %MVC/%BW, p = 0.06), but failed to reach significance. TA showed no change in activity with weight on the ankle (−0.004 ± 0.007 %MVC/%BW, p = 0.58).

Figure 5.

Figure 5.

Open in a new tab

Changes in muscle activation with increasing weight on the ankle. Four muscles showed significant increases in activity with increasing weight on the ankle (MG, SOL, PL, PB). TA showed little change with increasing weight on the ankle, while LG activity increased with weight on the ankle, but did not reach significance levels.

Muscle activity could not completely explain the increase in stiffness with increasing weight on the ankle, but it did account for some of the change in stiffness that could not be attributed to weight on the ankle. To determine the influence of muscle activity on stiffness we modelled the stiffness as a function of both weight-bearing and EMG activity. Including both weight and muscle activity (r2 = 0.89) resulted in a significant improvement in model quality compared to muscle activity alone (r2 = 0.78, likelihood ratio stat = 95, df = 3, p < 1 × 10−8). This demonstrates that muscle activity could not completely explain the linear relationship between weight bearing and ankle stiffness. In contrast, including both weight and muscle activity (r2 = 0.89) resulted in a significant improvement in model quality compared to weight only (r2 = 0.82, likelihood ratio stat = 25, df = 12, p =0.02), demonstrating the unique contribution of muscle activity to the stiffness. Due to the high correlation in the EMG activity between muscles as well as with weight bearing, we could not conclude which and to what extent each of the muscles contribute to stiffness. But we could conclude that muscle activity had an influence on stiffness beyond what could be attributed to weight on the ankle.

4. Differences in ankle stiffness between men and women

Men had modestly larger ankle stiffness than women over a majority of the BW range. The relationship between weight-bearing and stiffness did not differ significantly between men (5.7 ± 0.8 ×10−4 Nm/(rad N %BW)) and women (4.9 ± 0.8 ×10−4 Nm/(rad N %BW), p = 0.045). Unloaded stiffness also did not differ significantly between men (0.021 ± 0.004 Nm/(rad N)) and women (0.013 ± 0.004 Nm/(rad N), p = 0.16). However, when these two parameters were combined, we found that the men did have significantly higher ankle stiffness over the majority of the weight-bearing range (Fig 6). From 13% BW to 100% BW, men had a significantly greater ankle stiffness at any given percentage of body weight (p < 0.05 throughout that range) compared to women.

Figure 6.

Figure 6.

Open in a new tab

Differences in frontal-plane ankle stiffness between men and women. A) Ankle stiffness was slightly greater in men than in women, though the rate at which stiffness increases with weight on the ankle did not differ significantly between men and women. B) The p-values of the hypothesis test that men and women had significantly different ankle stiffness as a function of bodyweight. The stiffness was significantly different between 13% and 100% bodyweight, based on an alpha of 0.05 (dotted line).

Discussion

The goal of this study was to determine how weight-bearing affected frontal-plane ankle impedance. Previous studies had seen differences in sagittal-plane ankle impedance between weight-bearing and non-weight-bearing conditions. However, none of those studies systematically tested the effect of weight-bearing or focused on the frontal plane of the ankle. We had subjects systematically vary the weight on their right ankles, while rotational perturbations were applied in the frontal plane to estimate ankle impedance. We found that stiffness, the steady-state component of impedance, increased proportionally with weight on the ankle, being 2.6 and 4.1 times greater than unloaded stiffness at 50% and 100% bodyweight respectively. Furthermore, there was no correlation between unloaded stiffness and stiffness at full-weight bearing, limiting the predictive ability of unloaded measures to functional weight-bearing conditions. Our results suggest that this increase in frontal-plane stiffness resulted from both the compressive load on the joint as well as muscle activation. Finally, we found that over a large range of weight-bearing men had a greater stiffness than women. These results demonstrate that frontal-plane ankle stiffness is sensitive to weight-bearing and to accurately evaluate frontal-plane ankle instability weight-bearing needs to be considered. This in an important finding, as typical clinical measures of ankle instability are done during non-weight-bearing conditions.

1. Implications

Our results suggest that common clinical measures of ankle stability do not reflect the relevant mechanical properties of the ankle during the loaded conditions relevant to when ankle sprains occur. Ankle stability is often assessed clinically through a series of laxity assessments performed under unloaded conditions. One of these laxity assessments is a talar-tilt test, which measures the amount of ankle inversion/eversion when a clinician applies an inversion/eversion torque (Docherty and Rybak-Webb, 2009). This metric is similar to the stiffness estimates we have generated in our study, however can only be done during unloaded conditions. Our results suggest that these unloaded laxity assessments are not indicative of ankle stiffness during weight-bearing conditions. Ankle stiffness increased by factors of 2.6 and 4.1 at 50% and 100% weight-bearing respectively. Not only was stiffness much greater during weight bearing, stiffness at full-weight bearing was decoupled from unloaded stiffness. Thus, unloaded measures such as the talar-tilt test or similar laxity assessments are not predictive of ankle stiffness during the weight-bearing conditions that sprains occur.

2. Mechanism for the increase of stiffness with weight-bearing

Two possible mechanisms exist for the increase in stiffness with weight bearing: increased muscle activation (i.e. active) and joint-loading induced changes in ankle mechanics (i.e passive). Our study was not designed to disentangle the relative contributions of muscle activity and joint loading to bodyweight dependent changes in ankle stiffness. However, our results suggest that both factors contribute to our observed results.

We found that muscle activation contributed to the estimated ankle stiffness beyond what could be attributed to weight bearing alone. This sensitivity of stiffness to muscle activation is consistent with previous studies of the ankle stiffness. In the sagittal plane of the ankle, muscle activity in the LG, MG, and SOL can increase the stiffness by an order of magnitude relative to passive conditions (Hunter and Kearney, 1982). However, these muscles act mainly in the sagittal plane and have small moment arms in the frontal plane (McCullough et al., 2011). Other muscles do have substantial moment arms in the frontal plane (PL, PB, TA) (McCullough et al., 2011), but they are smaller and weaker (~ 20% of total strength of gastrocnemius and soleus) (Silver et al., 1985). Indeed, frontal plane stiffness has been shown to increase with activation of the TA and SOL, but much less than the increase in sagittal plane impedance (Lee et al., 2014b). We do see an increase in muscle activity in both PL and PB during weight bearing, which could lead to the increase in stiffness with weight bearing. Though these increases in activity were small (up to 8% MVC over the full range of weight-bearing in the PL), small amounts of muscle activation have been shown to substantially increase joint impedance in other planes and joints (Weiss et al., 1988; Zhang et al., 1998). However, due to the high correlation of the PL and PB activity with the load on the joint, and with the other muscles, we cannot conclude to what extent activity in these two muscles contributed the measured stiffness

We found that weight-bearing contributed to the estimated ankle stiffness beyond what could be attributed to muscle activation. This increase in stiffness with weight may be due to increase loading on the articular surfaces of the joint. Cadaveric studies have shown that the mechanism behind passive frontal-plane ankle stiffness shifts drastically when load is applied to the ankle. During unloaded conditions, ligaments are responsible for nearly the entirety of passive stiffness, while during loaded conditions the geometry of the articular surfaces produces resistive forces that lead to an increase in passive stiffness (Stormont et al., 1985). The magnitude of the passive stiffness resulting from articular surface contact is load-dependent (Stiehl et al., 1993), and may also contribute to our results.

3. Differences in frontal plane ankle stiffness between men and women

In general, women have higher joint and ligament laxity than men (Quatman et al., 2008; Wilkerson and Mason, 2000), which has been linked to higher rates of musculoskeletal injury (Alentorn-Geli et al., 2009; Sueyoshi et al., 2016). The ankle is no exception, as ankle laxity is also greater in women than in men (Ericksen and Gribble, 2012; Hollis et al., 1995; Trevino and Lee, 2018; Wilkerson and Mason, 2000). In certain population subsets, such as young basketball players (Beynnon et al., 2005), and individuals over the age of 30 (Waterman et al., 2010), women do suffer an increased rate of ankle sprains. Our results are consistent with these findings. We found that women do have unloaded stiffnesses, a metric similar to joint laxity, that is 62% smaller than in men. This finding is consistent and extends the results of Trevino & Lee (Trevino and Lee, 2018), who found relaxed unloaded stiffness was greater in men than in women. Though this difference in unloaded stiffness failed to reach significance levels when we normalized by bodyweight, we did find that women had significantly less ankle stiffness than men throughout the majority of the weight-bearing range, even when the results were normalized by bodyweight. This normalization by bodyweight is key, as the loads that are applied to the ankle during many movement tasks will be scaled by bodyweight (Monaghan et al., 2006). Thus, the effect of weight-bearing may explain why certain populations of women suffer greater incidences of ankle sprains than men.

Acknowledgements

The authors would like to thank Constantine Nicolozakes and Kristen Jakubowski for their help in collecting data, Timothy Haswell for his help in building the apparatus and Zoe Villamar for her help in preparing the manuscript. This work was supported in part by the National Institutes of Health’s National Center for Advancing Translational Sciences, Grant Number UL1TR001422.

Footnotes

Conflict of Interest Statement

The authors declare no conflict of interests.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  1. Alentorn-Geli E, Myer GD, Silvers HJ, Samitier G, Romero D, Lazaro-Haro C, Cugat R, 2009. Prevention of non-contact anterior cruciate ligament injuries in soccer players. Part 1: Mechanisms of injury and underlying risk factors. Knee Surg Sports Traumatol Arthrosc 17, 705–729. [DOI] [PubMed] [Google Scholar]
  2. Amiri P, Kearney RE, 2019. Ankle intrinsic stiffness changes with postural sway. J. Biomech. 85, 50–58. [DOI] [PubMed] [Google Scholar]
  3. Anandacoomarasamy A, Barnsley L, 2005. Long term outcomes of inversion ankle injuries. Br J Sports Med 39, e14; discussion e14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Arnold BL, Linens SW, de la Motte SJ, Ross SE, 2009. Concentric evertor strength differences and functional ankle instability: a meta-analysis. J Athl Train 44, 653–662. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Arnold BL, Wright CJ, Ross SE, 2011. Functional ankle instability and health-related quality of life. J Athl Train 46, 634–641. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Besomi M, Hodges PW, Van Dieen J, Carson RG, Clancy EA, Disselhorst-Klug C, Holobar A, Hug F, Kiernan MC, Lowery M, McGill K, Merletti R, Perreault E, Sogaard K, Tucker K, Besier T, Enoka R, Falla D, Farina D, Gandevia S, Rothwell JC, Vicenzino B, Wrigley T, 2019. Consensus for experimental design in electromyography (CEDE) project: Electrode selection matrix. J. Electromyogr. Kinesiol. 48, 128–144. [DOI] [PubMed] [Google Scholar]
  7. Beynnon BD, Murphy DF, Alosa DM, 2002. Predictive Factors for Lateral Ankle Sprains: A Literature Review. J Athl Train 37, 376–380. [PMC free article] [PubMed] [Google Scholar]
  8. Beynnon BD, Vacek PM, Murphy D, Alosa D, Paller D, 2005. First-time inversion ankle ligament trauma: the effects of sex, level of competition, and sport on the incidence of injury. The American journal of sports medicine 33, 1485–1491. [DOI] [PubMed] [Google Scholar]
  9. Brockett CL, Chapman GJ, 2016. Biomechanics of the ankle. Orthop Trauma 30, 232–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Casadio M, Morasso PG, Sanguineti V, 2005. Direct measurement of ankle stiffness during quiet standing: implications for control modelling and clinical application. Gait Posture 21, 410–424. [DOI] [PubMed] [Google Scholar]
  11. Docherty CL, Rybak-Webb K, 2009. Reliability of the anterior drawer and talar tilt tests using the LigMaster joint arthrometer. J Sport Rehabil 18, 389–397. [DOI] [PubMed] [Google Scholar]
  12. Ericksen H, Gribble PA, 2012. Sex differences, hormone fluctuations, ankle stability, and dynamic postural control. J Athl Train 47, 143–148. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Ferran NA, Maffulli N, 2006. Epidemiology of sprains of the lateral ankle ligament complex. Foot Ankle Clin 11, 659–662. [DOI] [PubMed] [Google Scholar]
  14. Ficanha EM, Ribeiro GA, Knop L, Rastgaar M, 2017. Time-varying impedance of the human ankle in the sagittal and frontal planes during straight walk and turning steps. IEEE Int Conf Rehabil Robot 2017, 1413–1418. [DOI] [PubMed] [Google Scholar]
  15. Freeman MA, 1965. Instability of the foot after injuries to the lateral ligament of the ankle. J Bone Joint Surg Br 47, 669–677. [PubMed] [Google Scholar]
  16. Gerber JP, Williams GN, Scoville CR, Arciero RA, Taylor DC, 1998. Persistent disability associated with ankle sprains: a prospective examination of an athletic population. Foot Ankle Int 19, 653–660. [DOI] [PubMed] [Google Scholar]
  17. Gottlieb GL, Agarwal GC, 1978. Dependence of human ankle compliance on joint angle. J. Biomech. 11, 177–181. [DOI] [PubMed] [Google Scholar]
  18. Hertel J, 2008. Sensorimotor deficits with ankle sprains and chronic ankle instability. Clin Sports Med 27, 353–370, vii. [DOI] [PubMed] [Google Scholar]
  19. Hollis JM, Blasier RD, Flahiff CM, 1995. Simulated lateral ankle ligamentous injury. Change in ankle stability. Am J Sports Med 23, 672–677. [DOI] [PubMed] [Google Scholar]
  20. Hubbard TJ, Hertel J, 2006. Mechanical contributions to chronic lateral ankle instability. Sports Med 36, 263–277. [DOI] [PubMed] [Google Scholar]
  21. Hubbard TJ, Kaminski TW, Vander Griend RA, Kovaleski JE, 2004. Quantitative Assessment of Mechanical Laxity in the Functionally Unstable Ankle. Medicine & Science in Sports & Exercise, 760–766. [DOI] [PubMed] [Google Scholar]
  22. Hunter IW, Kearney RE, 1982. Dynamics of human ankle stiffness: variation with mean ankle torque. J. Biomech. 15, 747–752. [DOI] [PubMed] [Google Scholar]
  23. Kearney RE, Hunter IW, 1990. System identification of human joint dynamics. Crit. Rev. Biomed. Eng. 18, 55–87. [PubMed] [Google Scholar]
  24. Konradsen L, 2002. Sensori-motor control of the uninjured and injured human ankle. J Electromyogr Kinesiol 12, 199–203. [DOI] [PubMed] [Google Scholar]
  25. Korkala O, Rusanen M, Jokipii P, Kytomaa J, Avikainen V, 1987. A prospective study of the treatment of severe tears of the lateral ligament of the ankle. Int Orthop 11, 13–17. [DOI] [PubMed] [Google Scholar]
  26. Kovaleski JE, Gurchiek LR, Heitman RJ, Hollis JM, Pearsall A.W.t., 1999. Instrumented measurement of anteroposterior and inversion-eversion laxity of the normal ankle joint complex. Foot Ankle Int 20, 808–814. [DOI] [PubMed] [Google Scholar]
  27. Lee H, Ho P, Rastgaar M, Krebs HI, Hogan N, 2014a. Multivariable Static Ankle Mechanical Impedance With Active Muscles. IEEE Trans Neural Syst Rehabil Eng 22, 44–52. [DOI] [PubMed] [Google Scholar]
  28. Lee H, Hogan N, 2015. Time-Varying Ankle Mechanical Impedance During Human Locomotion. IEEE Trans Neural Syst Rehabil Eng 23, 755–764. [DOI] [PubMed] [Google Scholar]
  29. Lee H, Krebs HI, Hogan N, 2014b. Multivariable dynamic ankle mechanical impedance with active muscles. IEEE Trans Neural Syst Rehabil Eng 22, 971–981. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Liu W, Siegler S, Techner L, 2001. Quantitative measurement of ankle passive flexibility using an arthrometer on sprained ankles. Clin Biomech (Bristol, Avon) 16, 237–244. [DOI] [PubMed] [Google Scholar]
  31. Loram ID, Lakie M, 2002. Direct measurement of human ankle stiffness during quiet standing: the intrinsic mechanical stiffness is insufficient for stability. J Physiol 545, 1041–1053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Ludvig D, Kearney RE, 2007. Real-time estimation of intrinsic and reflex stiffness. IEEE Trans. Biomed. Eng. 54, 1875–1884. [DOI] [PubMed] [Google Scholar]
  33. Ludvig D, Perreault EJ, 2012. System identification of physiological systems using short data segments. IEEE Trans. Biomed. Eng. 59, 3541–3549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Ludvig D, Plocharski M, Plocharski P, Perreault EJ, 2017. Mechanisms contributing to reduced knee stiffness during movement. Exp. Brain Res. 235, 2959–2970. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Magerkurth O, Frigg A, Hintermann B, Dick W, Valderrabano V, 2010. Frontal and lateral characteristics of the osseous configuration in chronic ankle instability. Br J Sports Med 44, 568–572. [DOI] [PubMed] [Google Scholar]
  36. McCullough MB, Ringleb SI, Arai K, Kitaoka HB, Kaufman KR, 2011. Moment arms of the ankle throughout the range of motion in three planes. Foot Ankle Int 32, 300–306. [DOI] [PubMed] [Google Scholar]
  37. McKay GD, Goldie PA, Payne WR, Oakes BW, 2001. Ankle injuries in basketball: injury rate and risk factors. Br J Sports Med 35, 103–108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Mirbagheri MM, Barbeau H, Kearney RE, 2000. Intrinsic and reflex contributions to human ankle stiffness: variation with activation level and position. Exp. Brain Res. 135, 423–436. [DOI] [PubMed] [Google Scholar]
  39. Monaghan K, Delahunt E, Caulfield B, 2006. Ankle function during gait in patients with chronic ankle instability compared to controls. Clin Biomech (Bristol, Avon) 21, 168–174. [DOI] [PubMed] [Google Scholar]
  40. Quatman CE, Ford KR, Myer GD, Paterno MV, Hewett TE, 2008. The effects of gender and pubertal status on generalized joint laxity in young athletes. J Sci Med Sport 11, 257–263. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Rouse EJ, Hargrove LJ, Perreault EJ, Kuiken TA, 2014. Estimation of human ankle impedance during the stance phase of walking. IEEE Trans Neural Syst Rehabil Eng 22, 870–878. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Sakanaka TE, Gill J, Lakie MD, Reynolds RF, 2018. Intrinsic ankle stiffness during standing increases with ankle torque and passive stretch of the Achilles tendon. PLoS One 13, e0193850. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Shorter AL, Rouse EJ, 2018. Mechanical Impedance of the Ankle During the Terminal Stance Phase of Walking. IEEE Trans Neural Syst Rehabil Eng 26, 135–143. [DOI] [PubMed] [Google Scholar]
  44. Siciliano B, Sciavicco L, Villani L, Oriolo G, 2010. Robotics: modelling, planning and control. Springer Science & Business Media. [Google Scholar]
  45. Silver RL, de la Garza J, Rang M, 1985. The myth of muscle balance. A study of relative strengths and excursions of normal muscles about the foot and ankle. J Bone Joint Surg Br 67, 432–437. [DOI] [PubMed] [Google Scholar]
  46. Sinkjaer T, Toft E, Andreassen S, Hornemann BC, 1988. Muscle stiffness in human ankle dorsiflexors: intrinsic and reflex components. J. Neurophysiol. 60, 1110–1121. [DOI] [PubMed] [Google Scholar]
  47. Stiehl JB, Skrade DA, Needleman RL, Scheidt KB, 1993. Effect of axial load and ankle position on ankle stability. J. Orthop. Trauma 7, 72–77. [DOI] [PubMed] [Google Scholar]
  48. Stormont DM, Morrey BF, An KN, Cass JR, 1985. Stability of the loaded ankle. Relation between articular restraint and primary and secondary static restraints. Am. J. Sports Med. 13, 295–300. [DOI] [PubMed] [Google Scholar]
  49. Sueyoshi T, Emoto G, Yuasa T, 2016. Generalized Joint Laxity and Ligament Injuries in High School-Aged Female Volleyball Players in Japan. Orthop J Sports Med 4, 2325967116667690. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Trevino J, Lee H, 2018. Sex Differences in 2-DOF Human Ankle Stiffness in Relaxed and Contracted Muscles. Ann. Biomed. Eng. 46, 2048–2056. [DOI] [PubMed] [Google Scholar]
  51. Valderrabano V, Hintermann B, Horisberger M, Fung TS, 2006. Ligamentous posttraumatic ankle osteoarthritis. Am J Sports Med 34, 612–620. [DOI] [PubMed] [Google Scholar]
  52. Verhagen RA, de Keizer G, van Dijk CN, 1995. Long-term follow-up of inversion trauma of the ankle. Arch Orthop Trauma Surg 114, 92–96. [DOI] [PubMed] [Google Scholar]
  53. Watanabe K, Kitaoka HB, Berglund LJ, Zhao KD, Kaufman KR, An KN, 2012. The role of ankle ligaments and articular geometry in stabilizing the ankle. Clin Biomech (Bristol, Avon) 27, 189–195. [DOI] [PubMed] [Google Scholar]
  54. Waterman BR, Owens BD, Davey S, Zacchilli MA, Belmont PJ Jr., 2010. The epidemiology of ankle sprains in the United States. J Bone Joint Surg Am 92, 2279–2284. [DOI] [PubMed] [Google Scholar]
  55. Weiss PL, Hunter IW, Kearney RE, 1988. Human ankle joint stiffness over the full range of muscle activation levels. J. Biomech. 21, 539–544. [DOI] [PubMed] [Google Scholar]
  56. Weiss PL, Kearney RE, Hunter IW, 1986a. Position dependence of ankle joint dynamics--I. Passive mechanics. J. Biomech. 19, 727–735. [DOI] [PubMed] [Google Scholar]
  57. Weiss PL, Kearney RE, Hunter IW, 1986b. Position dependence of ankle joint dynamics--II. Active mechanics. J. Biomech. 19, 737–751. [DOI] [PubMed] [Google Scholar]
  58. Wilkerson RD, Mason MA, 2000. Differences in men’s and women’s mean ankle ligamentous laxity. Iowa Orthop J 20, 46–48. [PMC free article] [PubMed] [Google Scholar]
  59. Zhang LQ, Nuber G, Butler J, Bowen M, Rymer WZ, 1998. In vivo human knee joint dynamic properties as functions of muscle contraction and joint position. J. Biomech. 31, 71–76. [DOI] [PubMed] [Google Scholar]

RESOURCES