Ankle Bracing Alters Coordination and Coordination Variability in Individuals With and Without Chronic Ankle Instability

in Journal of Sport Rehabilitation

Context: Ankle bracing is an effective form of injury prophylaxis implemented for individuals with and without chronic ankle instability, yet mechanisms surrounding bracing efficacy remain in question. Ankle bracing has been shown to invoke biomechanical and neuromotor alterations that could influence lower-extremity coordination strategies during locomotion and contribute to bracing efficacy. Objective: The purpose of this study was to investigate the effects of ankle bracing on lower-extremity coordination and coordination dynamics during walking in healthy individuals, ankle sprain copers, and individuals with chronic ankle instability. Design: Mixed factorial design. Setting: Laboratory setting. Participants: Forty-eight recreationally active individuals (16 per group) participated in this cross-sectional study. Intervention: Participants completed 15 trials of over ground walking with and without an ankle brace. Main Outcome Measures: Coordination and coordination variability of the foot–shank, shank–thigh, and foot–thigh were assessed during stance and swing phases of the gait cycle through analysis of segment relative phase and relative phase deviation, respectively. Results: Bracing elicited more synchronous, or locked, motion of the sagittal plane foot–shank coupling throughout swing phase and early stance phase, and more asynchronous motion of remaining foot–shank and foot–thigh couplings during early swing phase. Bracing also diminished coordination variability of foot–shank, foot–thigh, and shank–thigh couplings during swing phase of the gait cycle, indicating greater pattern stability. No group differences were observed. Conclusions: Greater stability of lower-extremity coordination patterns as well as spatiotemporal locking of the foot–shank coupling during terminal swing may work to guard against malalignment at foot contact and contribute to the efficacy of ankle bracing. Ankle bracing may also act antagonistically to interventions fostering functional variability.

Owing to the prevalence of acute ankle sprains and high rate of reoccurrence for such injuries, preventative measures such as ankle bracing are often implemented. Ankle bracing is an effective method of preventing ankle injury, particularly in athletes who have previously sustained an ankle injury or who have developed chronic ankle instability (CAI).15 While the efficacy of ankle bracing has garnered support from the literature, the underlying mechanisms that mitigate injury risk remain in question.

Numerous studies have reported effects of ankle bracing on a variety of movement-related parameters. Specifically, ankle bracing has been shown to alter neuromuscular function of hip, knee, and ankle musculature in CAI populations,68 as well as ankle joint position sense,9 ankle and knee kinematics,1012 and kinetics13,14 in healthy populations. This evidence suggests that the application of an ankle brace invokes sensorimotor adaptations, which could result in altered foot, shank, and thigh coordination strategies and ultimately contribute to the prevention of ankle injuries.

It is also important to consider how bracing might affect coordination patterns in individuals with and without CAI. Previous studies reported differences in lower-extremity biomechanics,15,16 coordination,17 and neuromuscular function18,19 during gait when comparing healthy and CAI populations. Furthermore, individuals who have previously sustained an ankle sprain injury but do not exhibit recurring dysfunction (ie, copers) have shown contrasting movement patterns from individuals with CAI.20 Thus, it is plausible that these groups would exhibit disparate lower-extremity coordination strategies during gait when an ankle brace is applied. Identifying distinctive responses to ankle bracing would help improve our understanding of how bracing works to be effective in individuals with and without CAI.

Coordination variability may be considered fluctuations in the coordination pattern between 2 segments and can be measured to assess motor adaptations in the presence of constraints (eg, ankle brace) on the system.21 Ankle taping has been shown to alter foot–shank coordination and decrease coordination variability during walking in healthy and CAI populations.22 It was suggested that with taping, reduced variability in the foot–shank coordination may serve as a mechanism to produce more rigid or stable movement patterns. However, despite previous studies that have highlighted the effects of ankle bracing on lower-extremity neuromuscular and biomechanical variables, it remains unclear how ankle bracing affects coordination strategies of the foot, shank, and thigh collectively during gait in individuals with and without CAI. Therefore, the purpose of this study was to examine the acute effects of ankle bracing on lower-extremity coordination and coordination variability during walking gait in healthy individuals, ankle sprain copers, and individuals with CAI. Analysis of the effects of ankle bracing on lower-extremity coordination strategies could shed light on systemic and potentially distinct movement adaptations that contribute to bracing efficacy in individuals with and without CAI. For this study, 2 hypotheses were considered: first, ankle bracing would induce acute adaptations, resulting in altered lower-extremity coordination and diminished coordination variability of segment couplings across all groups. Second, it is proposed that functional and sensorimotor deficits can inhibit motor adaptability in subjects with CAI.2325 Therefore, it is hypothesized that coordination variability would be more significantly diminished in individuals with CAI compared with healthy individuals and copers when an ankle brace is applied.

Materials and Methods

Research Design

The study was a mixed factorial design including a between-participants factor of group (healthy, coper, and CAI) and a within-participants factor of condition (brace and no brace). The independent variables for this study were group and condition, and the dependent variables consisted of mean relative phase (MRP) and relative phase deviation (RPD) of each segment coupling (foot–shank, shank–thigh, and foot–thigh).

Participants

Forty-eight university students participated in this study, and each group consisted of 16 participants (Table 1). Participants were recreationally active, partaking in a minimum of 90 minutes of physical activity per week, and were excluded if they had reported any of the following: (1) lower-extremity injury within 3 months of the study, (2) neurological impairments or movement disorders (other than ankle dysfunction), and (3) previous lower-extremity fracture or surgery. This study was approved by the university’s institutional review board, and all participants provided consent prior to study enrollment

Table 1

Group Descriptive and Survey Outcome Data

N (no. of females)Age, yHeight, mMass, kgFAAM, %FAAM-S, %AII (Y)
Healthy16 (10)23.1 (1.9)1.69 (0.08)71.8 (12.6)99.6 (1.2)96.5 (6.9)1 (2)
Coper16 (10)22.4 (2.9)1.70 (0.08)76.4 (19.3)97.6 (7.1)93.8 (11.9)3 (1)
CAI16 (10)23.3 (3.1)1.72 (0.09)77.8 (17.2)85.4 (5.6)68.4 (9.6)7 (1)

Abbreviations: AII, Ankle Instability Instrument; CAI, chronic ankle instability; FAAM, Foot and Ankle Ability Measure; FAAM-S, Foot and Ankle Ability Measure Sport. Note: % indicates outcome percentage score determined from FAAM survey responses. Y indicates the number of affirmative answers to questions on the AII. Data are presented as mean (SD).

Individuals in the coper group met the following recommended inclusion criteria according to Wikstrom and Brown26: (1) at least one lateral ankle sprain that necessitated immobilization or assisted weight bearing for at least 3 days; (2) for at least 12 months before testing individuals had no pain, weakness, or instability in the involved ankle and had resumed all preinjury activities without limitation; and (3) minimal self-reported disability determined by The Foot and Ankle Ability Measure, Foot and Ankle Ability Measure Sport, and Ankle Instability Instrument, which quantify dysfunction related to leg, foot, and ankle musculoskeletal conditions, and functional ankle instability.

Participants with CAI met the following recommended inclusion criteria as described by Gribble et al27: (1) history of at least one lateral ankle sprain, occurring >12 months prior to the study, requiring a period of assisted weight bearing or immobilization; (2) chronic weakness, pain, instability, or recurrent episodes of giving way in the involved ankle (without injury), attributed to the original injury; (3) 2 or more episodes of the involved ankle giving way between 3 and 12 months of the study; and (4) no observed ankle injury or participation in rehabilitation associated with the involved limb within the past 3 months of the study. In addition, individuals in the CAI group met the following self-reported scoring criteria: (1) five recorded “yes” answers on the Ankle Instability Instrument, (2) a score of ≤90% on the Foot and Ankle Ability Measure, and (3) a score of ≤80% on Foot and Ankle Ability Measure Sport.

Instrumentation

Forty-one 14-mm retroreflective markers (MKR-6.4; B&L Engineering, Tustin, CA) were attached bilaterally on the pelvis, thigh, shank, and foot of each participant for motion capture (Table 2). Calibration markers were utilized to estimate joint centers from a static calibration trial and were removed prior to walking trials. Measurement of segment motion was obtained using a 10-camera Vicon MX optical motion capture system (Vicon®, Oxford, United Kingdom) with a sampling frequency of 200 Hz. Walking trials were performed barefoot on a 7.6-m flat walkway embedded with 2 AMTI force plates (AMTI, Inc, Watertown, MA; 1000 Hz), aligned in the plane of walking progression near the center of the walkway. The force plates were utilized to determine gait events. An ASO® lace-up ankle brace with stabilizing straps (ASO®; Medical Specialties, Inc, Charlotte, NC) was applied by the same researcher for each participant for the brace condition (Figure 1). The ASO® brace was chosen due to its prevalent use by clinicians28 and implementation in research.

Table 2

Retroreflective Marker Placement

SegmentMarker position
CalibrationPosterior superior iliac spine, greater trochanter, medial/lateral tibiofemoral joint, and medial/lateral malleolus
PelvisAnterior superior iliac spine, iliac crest, and sacrum
ThighLateral thigh—rigid 3 marker cluster
ShankLateral shank—rigid 3 marker cluster
FootPosterior, medial and lateral calcaneus, first and fifth metatarsophalangeal joint, and dorsal midfoot

Note: List of anatomical landmarks for calibration and segment markers.

Figure 1
Figure 1

ASO ankle brace with retroreflective markers.

Citation: Journal of Sport Rehabilitation 2020; 10.1123/jsr.2019-0380

Protocol

Participants completed walking trials with and without an ankle brace. Condition order was counterbalanced within each group and assigned to participants randomly prior to the initiation of the study. Participants were instructed to begin from a set starting point and walk at a preferred normal walking speed across the walkway, with eyes directed straight ahead. Five familiarization trials were completed before test trials for each condition. Brace familiarization was conducted immediately after the brace was applied. Following familiarization, participants performed 15 test trials under each condition during which data were collected. The target limb assessed was considered the affected limb (CAI group) or previously affected limb (coper group). Furthermore, preferred or nonpreferred target limbs were matched across each group (eg, right preferred CAI target limb was matched with right preferred target limbs for coper and healthy groups). The preferred limb was determined by asking each participant which limb was preferred to kick a ball. For each trial, data from one complete gait cycle on the target limb (stance and swing phases) were obtained for analysis.

Data Processing and Analysis

Marker trajectories were low-pass filtered (6 Hz), and segment coordinate systems were constructed from static calibration trials obtained for each participant (Figure 2). Visual 3D software (C-Motion Research Biomechanics, Germantown, MD) was used to calculate segment angular position and angular velocity. Segment angular position was calculated in reference to the global lab axes using a Cardan X–Y–Z rotation sequence, and segmental angular velocity was calculated using the global lab axes as the resolution coordinate system. Segment rotations are subsequently described in accordance with conventional planes of motion: ZY rotation—sagittal plane (plane of walking progression), ZX rotation—frontal plane, and XY rotation—transverse plane. Kinematic data were time normalized to 101 data points (0%–100% gait cycle), allowing for between cycle analyses.

Figure 2
Figure 2

Global and segment coordinate systems.

Citation: Journal of Sport Rehabilitation 2020; 10.1123/jsr.2019-0380

Coordination of lower-extremity segments during walking was quantified using relative phase angles, which are a measure of the spatiotemporal relationship of one segment with respect to another (ie, segment coupling) over a given interval of time.21 Relative phase angles were calculated using a custom MATLAB code (MATLAB® R2013b; MathWorks, Inc, Natick, MA). First, segment angular position and angular velocity were normalized to maximum and minimum values, and phase portraits were constructed by plotting the normalized segment position and velocity on the x-axis and y-axis, respectively (Figure 3). Normalization of the angular position and angular velocity allowed the phase portrait trajectory to be centered on a zero origin and accounted for motion amplitude and frequency differences between segments being assessed, as well as instances where the data were not sinusoidal.21

Figure 3
Figure 3

Representative phase portrait of the thigh during walking. Normalized sagittal plane thigh angular position (x-axis) and angular velocity (y-axis) are plotted to construct the phase portrait. Spatiotemporal progression of the thigh during the gait cycle begins at FC and continues clockwise past TO before returning to FC. The phase angle at a given time point (ϕt) is shown. FC indicates foot contact; TO, toe-off

Citation: Journal of Sport Rehabilitation 2020; 10.1123/jsr.2019-0380

From the phase portrait, a phase angle was determined by projecting a ray from the origin of the portrait to each successive data point making up the curve and calculating the angle of the vector from the right horizontal. Specifically, the phase angle calculation is described by:

ϕ(t)=tan1(ω(t)θ(t))
where ω is the angular velocity and θ is the segment angle at time point t within the movement cycle. Relative phase was calculated at each time point within the movement cycle by subtracting the phase angle obtained for the proximal segment from the phase angle for the distal segment, as described by:
ϕRel(t)=ϕD(t)ϕP(t)
where ϕD is the phase angle of the distal segment, and ϕP is the phase angle of the proximal segment at time point t.

Due to redundancies in the interpretation of relative phase values within a 0° to 360° range, values were transformed to a 0° to 180° range.21 Subsequently, measures of central tendency could be used for MRP computations; larger MRP values indicate the segmental motion is more independent or asynchronous while smaller MRP values indicate more synchronous segment motion. Relative phase standard deviation (RPD), a measure of the coordinated pattern variability, was also calculated for each coupling throughout the walking gait cycle. Larger RPD values indicate greater fluctuations in the coordinated pattern, while lower RPD values indicate less pattern fluctuation. Intervals of interest within the gait cycle included foot contact to midstance (0%–25%), toe-off to midswing (60%–75%), and terminal swing (85%–100%). MRP and RPD were assessed for the following lower-extremity segment couplings and corresponding planes of rotation: footsagittal–shanksagittal, footsagittal–thighsagittal, footfrontal–shanktransverse, footfrontal–thighfrontal, and shanksagittal–thighsagittal.

Statistical Analysis

Statistical analyses were conducted using SPSS software (version 18.0; SPSS Inc, Chicago, IL). One-way analyses of variance were conducted to test for between-group differences in height, mass, and age. Mixed-model analyses of variance, with repeated measures on the within-participants factor were employed for stance and swing phase intervals. Post hoc comparisons using the least significant difference test were conducted if significant main effects or interactions were observed. Simple effects were assessed using 1-sample t tests. Corresponding mean differences (MDs), Cohen d effect sizes (d), and 95% confidence intervals for the effect sizes are reported. Statistical significance was reached if the alpha level was ≤.05, the absolute value of the effect size was moderate to strong (>0.49), and the confidence intervals for effect size did not contain zero.29

Results

Measures of height, mass, and age were consistent across groups (P > .40).

Bracing Effects—Coordination

Data were collapsed across groups for within-subjects analysis of coordination. Significant condition by coupling interactions were observed from foot contact to midstance phase (P = .001), initial swing phase (P < .001), and terminal swing phase (P < .001) (Table 3). From foot contact to midstance, footsagittal–shanksagittal coordination was more in phase during the brace condition compared with the no brace condition (MD = −1.87, P < .001).

Table 3

MRP Values

No braceBrace
PhaseCouplingMean (SD)Mean (SD)d95% CI for d
Foot contact to midstance128.99 (4.05)27.12 (4.09)−1.0−1.95 to −0.13
247.83 (8.35)46.97 (8.25)−0.3−0.41 to −0.14
3170.53 (7.48)170.70 (7.97)0.00.04 to 0.01
4160.99 (17.26)160.86 (19.14)0.0−0.05 to −0.02
519.01 (10.34)20.02 (10.22)0.40.52 to 0.20
Toe-off to midswing119.88 (4.00)15.68 (2.99)−1.8−3.39 to −0.17
258.02 (6.51)62.19 (5.22)1.12.21 to 0.01
3109.37 (32.30)124.03 (30.23)0.50.88 to 0.04
4101.00 (32.80)114.64 (30.96)0.71.24 to 0.22
577.43 (4.41)77.79 (4.25)0.10.18 to 0.02
Terminal swing12.53 (1.56)2.08 (1.76)−0.5−0.99 to −0.03
218.02 (10.23)17.35 (10.14)−0.1−0.18 to −0.04
3134.59 (30.26)137.28 (28.35)0.10.23 to 0.03
4131.40 (41.85)138.57 (35.22)0.30.50 to 0.08
518.83 (10.05)17.53 (9.60)−0.2−0.34 to −0.06

Abbreviations: CI, confidence interval; MRP, mean relative phase. MRP values are listed in units of degrees. Couplings: (1) footsagittal–shanksagittal, (2) footsagittal–thighsagittal, (3) footfrontal–shanktransverse, (4) footfrontal–thighfrontal, and (5) shanksagittal–thighsagittal. Bold text indicates statistical significance based on the criteria: P < .05, |d| > 0.49, and CIs do not contain 0.

From toe-off to midswing, footsagittal–shanksagittal coordination became more in phase during the brace condition (MD = −4.20, P < .001). The opposite effect was observed during the brace condition for the footsagittal–thighsagittal (MD = 4.17, P < .001), footfrontal–shanktransverse (MD = 14.66, P = .003), and footfrontal–thighfrontal (MD = 13.64, P < .001) couplings. During terminal swing phase, footsagittal–shanksagittal coordination became more in phase during the brace condition (MD = −0.45, P = .001). A summary of percentage changes in segment coordination from the no brace to brace conditions is presented in Figure 4.

Figure 4
Figure 4

Percentage change in segment coordination from no brace to brace conditions. MRP indicates mean relative phase.

Citation: Journal of Sport Rehabilitation 2020; 10.1123/jsr.2019-0380

Bracing Effects—Coordination Variability

Data were collapsed across groups for within-subjects analysis of coordination variability. Significant condition by coupling interactions were observed during initial swing phase (P < .001) and terminal swing phase (P < .001) (Table 4). During toe-off to midswing, bracing diminished coordination variability in the footsagittal–shanksagittal (MD = −4.99 P < .001), footsagittal–thighsagittal (MD = −2.21, P < .001), and shanksagittal–thighsagittal (MD = −0.58, P = .001) couplings. During terminal swing phase, bracing diminished coordination variability of the footsagittal–shanksagittal coupling (MD = −1.02, P < .001). A summary of percentage changes in coordination variability from the no brace to brace conditions is presented in Figure 5.

Table 4

RPD Values

No braceBrace
PhaseCouplingMean (SD)Mean (SD)d95% CI for d
Toe-off to midswing112.89 (4.36)7.90 (2.75)−2.3−4.58 to −0.06
211.72 (2.76)9.51 (2.43)−1.0−2.06 to −0.02
352.63 (10.84)55.94 (9.41)0.40.78 to 0.08
448.69 (11.74)49.30 (12.15)0.00.06 to 0.00
59.86 (3.18)9.28 (3.04)−0.5−0.80 to −0.26
Terminal swing15.11 (2.57)4.09 (1.97)−0.7−1.35 to −0.09
221.30 (8.85)22.65 (9.95)0.20.31 to 0.09
329.48 (12.76)27.16 (13.04)−0.3−0.52 to −0.12
429.90 (13.20)28.00 (13.14)−0.3−0.49 to −0.11
522.26 (7.80)22.84 (9.12)0.00.02 to −0.02

Abbreviations: CI, confidence interval; RPD, relative phase deviation. Note: RPD values are listed in units of degrees. Couplings: (1) footsagittal–shanksagittal, (2) footsagittal–thighsagittal, (3) footfrontal–shanktransverse, (4) footfrontal–thighfrontal, and (5) shanksagittal–thighsagittal. Bold text indicates statistical significance based on the criteria: P < .05, |d| > 0.49, and CIs do not contain 0.

Figure 5
Figure 5

Percentage change in coordination variability from no brace to brace conditions. RPD indicates relative phase deviation.

Citation: Journal of Sport Rehabilitation 2020; 10.1123/jsr.2019-0380

Group Effects

No significant group main effects or interactions were observed.

Discussion

To the author’s knowledge, this is the first study to report effects of ankle bracing on coordination and coordination variability of thigh, shank, and foot couplings during walking. The findings indicate that ankle bracing invoked acute adaptations to lower-extremity coordination strategies during walking in healthy, coper, and CAI groups. Furthermore, individuals with and without CAI exhibited similar adaptive coordination strategies in response to ankle bracing.

With respect to group comparisons, the present results contribute to some discrepancy in the literature. Using a relative phase technique to assess coordination, Drewes et al16 found that participants with CAI demonstrated a more out of phase foot–shank coupling during 94% to 97% of the gait cycle (late terminal swing phase) of normal walking, but exhibited no differences in coordination variability compared with healthy participants. Contrarily, Herb et al17 implemented a vector coding technique to assess coordination and found that participants with CAI had less relative excursion between the foot and shank during terminal swing phase of walking, and less foot–shank variability during late stance phase, toe-off, and early swing phase. The results of our study indicate that there was no difference in the coordination and coordination variability across healthy, coper, and CAI groups in brace and no brace conditions. Our terminal swing analysis encompassed 85% to 100% of the gait cycle, which is a considerably larger interval than where statistically significant differences were found (94%–97%) in the Drewes et al16 paper. It is possible that the breadth of the terminal swing interval in the current study was too large to identify group differences in foot–shank coordination. However, given the statistical and methodological differences in assessing segment coordination and coordination variability between aforementioned studies, direct comparison of results should be made with caution; additional research is needed to explore differences in kinematic coordination patterns between individuals with and without CAI.

Irrespective of group, 2 main findings surrounding coordination responses to ankle bracing are highlighted. The first is that ankle bracing yielded more synchronous, or locked, sagittal plane foot–shank motion in critical areas within the gait cycle pertaining to ankle sprain injury (ie, terminal swing and after foot contact), and these results were associated with moderate to strong effect sizes. Herb et al22 reported a decrease in the magnitude of coupled motion between foot inversion/eversion and shank internal/external rotation at foot contact when healthy participants and participants with CAI were walking with a taped ankle, although sagittal plane coupling of the foot–shank was not investigated. Additionally, ankle bracing has been shown to limit both passive and dynamic range of motion of the ankle in healthy and CAI populations,9,14 and previous studies show that individuals with CAI exhibit a more neutral ankle position in swing phase30 and at foot contact31 while walking with prophylactic ankle support. Considering the mechanism of lateral ankle sprain injury can involve excessive inversion and plantar flexion,23 proper foot alignment surrounding foot contact carries great clinical significance for mitigating risk of ankle sprain injury. Collectively, evidence suggests that ankle bracing creates a spatiotemporal lock of the ankle joint (ie, less independent foot–shank motion) and promotes more neutral ankle position to guard against malalignment near foot contact.

Notably, footfrontal–shanktransverse coordination as well as both frontal and sagittal plane foot–thigh coordination were more asynchronous during toe-off to midswing phase of the brace condition. Limitations in plantar flexion and inversion range of motion at toe-off could explain the spatiotemporal asynchrony mentioned above. For example, if the ankle experiences less plantar flexion and inversion at toe-off when braced, the amplitude of thigh motion would dominate the foot–thigh coupling and yield more asynchronous motion between the foot and thigh. Although ankle joint range of motion was not directly measured in this study, these findings demonstrate that ankle bracing altered coordination in segments proximal to the ankle joint from toe-off to midswing, suggesting that strategies to propel the lower-extremity through swing phase may be impacted when an ankle brace is applied.

The second main finding is that bracing diminished coordination variability of the foot–shank, foot–thigh, and shank–thigh couplings during swing phase, and these results were associated with moderate to strong effect sizes. These findings highlight that effects of ankle bracing are not solely mechanical in nature, but also involve reorganization of lower-extremity motor control strategies throughout swing phase of the gait cycle. Ankle bracing has been shown to alter ankle joint position sense, proprioception, as well as the timing and amplitude of activation of lower-extremity muscles.6,7,3234 Therefore, it is plausible that a sensorimotor response to ankle bracing elicited changes in movement variability characteristics observed in this study.

Coordination variability is considered as a measure of the level of stability of the motor system.21,35 Thus, the observed reductions in lower-extremity coordination variability demonstrates more stable stride-to-stride behavior. Herb et al22 also reported decreases in foot–shank variability with taping during gait and suggested that lower coordination variability serves as protective mechanism by creating more stable gait pattern between strides. Here, we note that reductions in coordination variability existed across the entire lower-extremity, demonstrating that gait patterns were indeed more stable, in that a narrower range of movement strategies were adopted when the ankle brace was applied. This stride-to-stride consistency in gait patterns may be important for preventing foot malalignment as the lower-extremity progresses through swing phase and approaches foot contact; however, further research is needed to explore the relationship between coordination variability and foot alignment at foot contact during the gait cycle.

Potential negative implications from these results should also be considered. In sports medicine, proponents of dynamic systems theory of motor behavior suggest that interventions surrounding training and rehabilitation should foster functional variability within the movement system to promote patterns that can adapt to changing task, environmental, and individual constraints.24,25,3638 Results from this study showed that ankle bracing elicited acute adaptations of coordination pattern dynamics, characterized by diminished functional variability of the lower-extremity. Thus, clinicians should be aware of the potential barriers that ankle bracing may present in situations where functional variability is warranted.

Several limitations of this study should be noted. First, although commonly implemented in biomechanics research, skin mounted rigid marker clusters may contribute to some error in the derived kinematics due to skin movement artifact. Despite the inherent artifact associated with skin mounted markers, proper cluster design and placement, as well as raw marker position data filtering, were put into practice in accordance with recommended procedures for minimizing error with cluster use.39 Second, the current study considered only acute adaptations to ankle bracing, requiring further analysis of the prolonged or chronic effects of bracing applications on coordination strategies. Finally, additional recommended criteria (eg, number of recurrent ankle sprains, time since first/last ankle sprain, coper self-reported score minimums) were not attained from participants. A more stringent grouping criteria within both coper and CAI groups may be necessary to uncover differences related to lower-extremity coordination and coordination dynamics.

In conclusion, ankle bracing resulted in foot–shank spatiotemporal locking and more stable lower-extremity coordination patterns during swing phase of walking gait, which may contribute to the effectiveness of ankle bracing for preventing ankle sprain injury in individuals with and without CAI. These adaptations highlight that both mechanical functioning of the lower-extremity and lower-extremity motor control strategies are affected following application of an ankle brace. Additional research is needed to uncover underlying sensorimotor mechanisms that contribute to coordination adaptations during walking gait when an ankle brace is applied. Furthermore, researchers and clinicians should consider both lower-extremity coordination and coordination variability as relevant factors that may contribute to ankle sprain injury, as well as the role that ankle bracing plays in mediating lower-extremity coordination patterns.

Acknowledgments

The authors report no conflict of interest. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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    • Export Citation
  • 13.

    Klem NR, Wild CY, Williams SA, Ng L. Effect of external ankle support on ankle and knee biomechanics during the cutting maneuver in basketball players. Am J Sports Med. 2017;45(3):685691. PubMed ID: 27872123 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Mason-Mackay AR, Whatman C, Reid D. The effect of ankle bracing on lower extremity biomechanics during landing: a systematic review. J Sci Med Sport. 2016;19(7):531540. doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Chinn L, Dicharry J, Hertel J. Ankle kinematics of individuals with chronic ankle instability while walking and jogging on a treadmill in shoes. Phys Ther Sport. 2013;14(4):232239. PubMed ID: 23623243 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Drewes LK, McKeon PO, Paolini G, et al. Altered ankle kinematics and shank-rear-foot coupling in those with chronic ankle instability. J Sport Rehabil. 2009;18(3):375388. PubMed ID: 19827501 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Herb CC, Chinn L, Dicharry J, McKeon PO, Hart JM, Hertel J. Shank-rearfoot joint coupling with chronic ankle instability. J Appl Biomech. 2014;30(3):366372. PubMed ID: 24347533 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Delahunt E, Monaghan K, Caulfield B. Altered neuromuscular control and ankle joint kinematics during walking in subjects with functional instability of the ankle joint. Am J Sports Med. 2006;34(12):19701976. PubMed ID: 16926342 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Feger MA, Donovan L, Hart JM, Hertel J. Lower extremity muscle activation in patients with or without chronic ankle instability during walking. J Athl Train. 2015;50(4):350357. PubMed ID: 25562453 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Doherty C, Bleakley C, Hertel J, Caulfield B, Ryan J, Delahunt E. Locomotive biomechanics in persons with chronic ankle instability and lateral ankle sprain copers. J Sci Med Sport. 2016;19(7):524530. doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Lamb PF, Stockl M. On the use of continuous relative phase: review of current approaches and outline for a new standard. Clin Biomech. 2014;29(5):484493. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Herb CC, Chinn L, Hertel J. Altering shank-rear-foot joint coupling during gait with ankle taping in patients with chronic ankle instability and healthy controls. J Sport Rehabil. 2016;25(1):1322. PubMed ID: 25658069 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Hertel J. Functional anatomy, pathomechanics, and pathophysiology of lateral ankle instability. J Athl Train. 2002;37(4):364. PubMed ID: 12937557

  • 24.

    Hoch MC, McKeon PO. Integrating contemporary models of motor control and health in chronic ankle instability. Athl Train Sports Health Care. 2010;2(2):8288. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Wikstrom EA, Hubbard-Turner T, McKeon PO. Understanding and treating lateral ankle sprains and their consequences: a constraints-based approach. Sports Med. 2013;43(6):385393. PubMed ID: 23580392 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Wikstrom EA, Brown CN. Minimum reporting standards for copers in chronic ankle instability research. Sports Med. 2014;44(2):251268. PubMed ID: 24122774 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Gribble PA, Delahunt E, Bleakley C, et al. Selection criteria for patients with chronic ankle instability in controlled research: a position statement of the international ankle consortium. J Orthop Sports Phys Ther. 2013;43(8):585591. PubMed ID: 23902805 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Denton JM, Waldhelm A, Hacke JD, Gross MT. Clinician recommendations and perceptions of factors associated with ankle brace use. Sports Health. 2015;7(3):267269. PubMed ID: 26131306 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Lee DK. Alternatives to p value: confidence interval and effect size. Korean J Anesthesiol. 2016;69(6):555562. PubMed ID: 27924194 doi:

  • 30.

    Chinn L, Dicharry J, Hart JM, Saliba S, Wilder R, Hertel J. Gait kinematics after taping in participants with chronic ankle instability. J Athl Train. 2014;49(3):322330. PubMed ID: 24840583 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Spaulding SJ, Livingston LA, Hartsell HD. The influence of external orthotic support on the adaptive gait characteristics of individuals with chronically unstable ankles. Gait Posture. 2003;17(2):152158. PubMed ID: 12633776 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Hartsell HD. The effects of external bracing on joint position sense awareness for the chronically unstable ankle. J Sport Rehabil. 2000;9(4):279289. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33.

    Heit EJ, Lephart SM, Rozzi SL. The effect of ankle bracing and taping on joint position sense in the stable ankle. J Sport Rehabil. 1996;5(3):206213. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34.

    Ozer D, Senbursa G, Baltaci G, Hayran M. The effect on neuromuscular stability, performance, multi-joint coordination and proprioception of barefoot, taping or preventative bracing. Foot. 2009;19(4):205210. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 35.

    Stergiou N, Decker LM. Human movement variability, nonlinear dynamics, and pathology: is there a connection? Hum Mov Sci. 2011;30(5):869888. PubMed ID: 21802756 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36.

    Holt K, Wagenaar R, Saltzman E. A dynamic systems/constraints approach to rehabilitation. Braz J Phys Ther. 2010;14(6):446463. doi:

  • 37.

    McKeon PO. Cultivating functional variability: the dynamical-systems approach to rehabilitation. Int J Athl Ther Train. 2009;14(4):13.

    • Search Google Scholar
    • Export Citation
  • 38.

    McKeon PO, Hertel J. The dynamical-systems approach to studying athletic injury. Int J Athl Ther Train. 2006;11(1):3133.

  • 39.

    Cappozzo A, Cappello A, Croce UD, Pensalfini F. Surface-marker cluster design criteria for 3-D bone movement reconstruction. IEEE Trans Biomed Eng. 1997;44(12):11651174. PubMed ID: 9401217 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

If the inline PDF is not rendering correctly, you can download the PDF file here.

Jagodinsky is with the School of Kinesiology and Recreation, Illinois State University, Normal, IL, USA. Wilburn, Moore, and Weimar are with the School of Kinesiology, Auburn University, Auburn, AL, USA. Fox is with the Department of Physical Therapy Program, Methodist University, Fayetteville, NC, USA.

Jagodinsky (aejagod@ilstu.edu) is corresponding author.
  • View in gallery

    ASO ankle brace with retroreflective markers.

  • View in gallery

    Global and segment coordinate systems.

  • View in gallery

    Representative phase portrait of the thigh during walking. Normalized sagittal plane thigh angular position (x-axis) and angular velocity (y-axis) are plotted to construct the phase portrait. Spatiotemporal progression of the thigh during the gait cycle begins at FC and continues clockwise past TO before returning to FC. The phase angle at a given time point (ϕt) is shown. FC indicates foot contact; TO, toe-off

  • View in gallery

    Percentage change in segment coordination from no brace to brace conditions. MRP indicates mean relative phase.

  • View in gallery

    Percentage change in coordination variability from no brace to brace conditions. RPD indicates relative phase deviation.

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    Mason-Mackay AR, Whatman C, Reid D, Lorimer A. The effect of ankle bracing on landing biomechanics in female netballers. Phys Ther Sport. 2016;20:1318. PubMed ID: 27325534 doi:

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    Tamura K, Radzak KN, Vogelpohl RE, et al. The effects of ankle braces and taping on lower extremity running kinematics and energy expenditure in healthy, non-injured adults. Gait Posture. 2017;58:108114. PubMed ID: 28772129 doi:

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    Klem NR, Wild CY, Williams SA, Ng L. Effect of external ankle support on ankle and knee biomechanics during the cutting maneuver in basketball players. Am J Sports Med. 2017;45(3):685691. PubMed ID: 27872123 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14.

    Mason-Mackay AR, Whatman C, Reid D. The effect of ankle bracing on lower extremity biomechanics during landing: a systematic review. J Sci Med Sport. 2016;19(7):531540. doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15.

    Chinn L, Dicharry J, Hertel J. Ankle kinematics of individuals with chronic ankle instability while walking and jogging on a treadmill in shoes. Phys Ther Sport. 2013;14(4):232239. PubMed ID: 23623243 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 16.

    Drewes LK, McKeon PO, Paolini G, et al. Altered ankle kinematics and shank-rear-foot coupling in those with chronic ankle instability. J Sport Rehabil. 2009;18(3):375388. PubMed ID: 19827501 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Herb CC, Chinn L, Dicharry J, McKeon PO, Hart JM, Hertel J. Shank-rearfoot joint coupling with chronic ankle instability. J Appl Biomech. 2014;30(3):366372. PubMed ID: 24347533 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18.

    Delahunt E, Monaghan K, Caulfield B. Altered neuromuscular control and ankle joint kinematics during walking in subjects with functional instability of the ankle joint. Am J Sports Med. 2006;34(12):19701976. PubMed ID: 16926342 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19.

    Feger MA, Donovan L, Hart JM, Hertel J. Lower extremity muscle activation in patients with or without chronic ankle instability during walking. J Athl Train. 2015;50(4):350357. PubMed ID: 25562453 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20.

    Doherty C, Bleakley C, Hertel J, Caulfield B, Ryan J, Delahunt E. Locomotive biomechanics in persons with chronic ankle instability and lateral ankle sprain copers. J Sci Med Sport. 2016;19(7):524530. doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21.

    Lamb PF, Stockl M. On the use of continuous relative phase: review of current approaches and outline for a new standard. Clin Biomech. 2014;29(5):484493. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 22.

    Herb CC, Chinn L, Hertel J. Altering shank-rear-foot joint coupling during gait with ankle taping in patients with chronic ankle instability and healthy controls. J Sport Rehabil. 2016;25(1):1322. PubMed ID: 25658069 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 23.

    Hertel J. Functional anatomy, pathomechanics, and pathophysiology of lateral ankle instability. J Athl Train. 2002;37(4):364. PubMed ID: 12937557

  • 24.

    Hoch MC, McKeon PO. Integrating contemporary models of motor control and health in chronic ankle instability. Athl Train Sports Health Care. 2010;2(2):8288. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Wikstrom EA, Hubbard-Turner T, McKeon PO. Understanding and treating lateral ankle sprains and their consequences: a constraints-based approach. Sports Med. 2013;43(6):385393. PubMed ID: 23580392 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 26.

    Wikstrom EA, Brown CN. Minimum reporting standards for copers in chronic ankle instability research. Sports Med. 2014;44(2):251268. PubMed ID: 24122774 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Gribble PA, Delahunt E, Bleakley C, et al. Selection criteria for patients with chronic ankle instability in controlled research: a position statement of the international ankle consortium. J Orthop Sports Phys Ther. 2013;43(8):585591. PubMed ID: 23902805 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 28.

    Denton JM, Waldhelm A, Hacke JD, Gross MT. Clinician recommendations and perceptions of factors associated with ankle brace use. Sports Health. 2015;7(3):267269. PubMed ID: 26131306 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 29.

    Lee DK. Alternatives to p value: confidence interval and effect size. Korean J Anesthesiol. 2016;69(6):555562. PubMed ID: 27924194 doi:

  • 30.

    Chinn L, Dicharry J, Hart JM, Saliba S, Wilder R, Hertel J. Gait kinematics after taping in participants with chronic ankle instability. J Athl Train. 2014;49(3):322330. PubMed ID: 24840583 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 31.

    Spaulding SJ, Livingston LA, Hartsell HD. The influence of external orthotic support on the adaptive gait characteristics of individuals with chronically unstable ankles. Gait Posture. 2003;17(2):152158. PubMed ID: 12633776 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 32.

    Hartsell HD. The effects of external bracing on joint position sense awareness for the chronically unstable ankle. J Sport Rehabil. 2000;9(4):279289. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 33.

    Heit EJ, Lephart SM, Rozzi SL. The effect of ankle bracing and taping on joint position sense in the stable ankle. J Sport Rehabil. 1996;5(3):206213. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 34.

    Ozer D, Senbursa G, Baltaci G, Hayran M. The effect on neuromuscular stability, performance, multi-joint coordination and proprioception of barefoot, taping or preventative bracing. Foot. 2009;19(4):205210. doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 35.

    Stergiou N, Decker LM. Human movement variability, nonlinear dynamics, and pathology: is there a connection? Hum Mov Sci. 2011;30(5):869888. PubMed ID: 21802756 doi:

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 36.

    Holt K, Wagenaar R, Saltzman E. A dynamic systems/constraints approach to rehabilitation. Braz J Phys Ther. 2010;14(6):446463. doi:

  • 37.

    McKeon PO. Cultivating functional variability: the dynamical-systems approach to rehabilitation. Int J Athl Ther Train. 2009;14(4):13.

    • Search Google Scholar
    • Export Citation
  • 38.

    McKeon PO, Hertel J. The dynamical-systems approach to studying athletic injury. Int J Athl Ther Train. 2006;11(1):3133.

  • 39.

    Cappozzo A, Cappello A, Croce UD, Pensalfini F. Surface-marker cluster design criteria for 3-D bone movement reconstruction. IEEE Trans Biomed Eng. 1997;44(12):11651174. PubMed ID: 9401217 doi:

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
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