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Kinematic predictors of star excursion balance test performance in individuals with chronic ankle instability
Clinical Biomechanics 35 (2016) 37–41
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Clinical Biomechanics journal homepage: www.elsevier.com/locate/clinbiomech
Kinematic predictors of star excursion balance test performance in individuals with chronic ankle instability Matthew C. Hoch a,⁎, Stacey L. Gaven b, Joshua T. Weinhandl c a b c
School of Physical Therapy and Athletic Training, College of Heath Sciences, Old Dominion University, Health Sciences Annex, RM 102, Norfolk, VA, USA Department of Kinesiology, Franklin College, Franklin, IN, USA Department of Kinesiology, Recreation, and Sports Studies, The University of Tennessee, Knoxville, TN, USA
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Article history: Received 13 January 2016 Accepted 12 April 2016 Keywords: Ankle sprain Postural control Kinematics Dorsiflexion
a b s t r a c t Background: The Star Excursion Balance Test has identified dynamic postural control deficits in individuals with chronic ankle instability. While kinematic predictors of Star Excursion Balance Test performance have been evaluated in healthy individuals, this has not been thoroughly examined in individuals with chronic ankle instability. Methods: Fifteen individuals with chronic ankle instability completed the anterior reach direction of the Star Excursion Balance Test and weight-bearing dorsiflexion assessments. Maximum reach distances on the Star Excursion Balance Test were measured in cm and normalized to leg length. Three-dimensional trunk, hip, knee, and ankle motion of the stance limb were recorded during each anterior reach trial using a motion capture system. Sagittal, frontal, and transverse plane displacement observed from trial initiation to the point of maximum reach was calculated for each joint or segment and averaged for analysis. Pearson product–moment correlations were performed to examine the relationships between kinematic variables, maximal reach, and weight-bearing dorsiflexion. A backward multiple linear regression model was developed with maximal reach as the criterion variable and kinematic variables as predictors. Findings: Frontal plane displacement of the trunk, hip, and ankle and sagittal plane knee displacement were entered into the analysis. The final model (p = 0.004) included all three frontal plane variables and explained 81% of the variance in maximal reach. Maximal reach distance and several kinematic variables were significantly related to weight-bearing dorsiflexion. Interpretation: Individuals with chronic ankle instability who demonstrated greater lateral trunk displacement toward the stance limb, hip adduction, and ankle eversion achieved greater maximal reach. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Chronic ankle instability (CAI) is experienced by approximately 1 in 3 people who sustain an acute ankle sprain (Konradsen et al., 2002). CAI is categorized by recurrent ankle sprain symptoms, repetitive episodes of ankle “giving way,” and repeated ankle sprain injuries (Hertel, 2002). Ultimately, many individuals with CAI experience diminished health-related quality of life which may have profound effects on long-term health (Houston et al., 2015). Continuing to advance our understanding of CAI is an important step toward developing innovative treatment strategies to help patients with CAI overcome their health condition. Many of the aforementioned characteristics of CAI are thought to be linked to sensorimotor impairments which result in functional movement alterations (Hertel, 2008). This has been exemplified by a number of studies which have identified postural control deficits in people with ⁎ Corresponding author. E-mail address: [email protected] (M.C. Hoch).
http://dx.doi.org/10.1016/j.clinbiomech.2016.04.008 0268-0033/© 2016 Elsevier Ltd. All rights reserved.
CAI (Arnold et al., 2009). Postural control has been assessed with a number of measurement strategies which range from instrumented static techniques to clinically oriented dynamic techniques such as the Star Excursion Balance Test (SEBT) (Arnold et al., 2009). The SEBT involves unilateral stance while attempting to perform a maximal reach with contralateral limb in a series of reach directions (Gribble and Hertel, 2003; Gribble et al., 2012). Individuals with CAI have typically demonstrated shorter reach distances on this test which indicates dynamic postural control deficits are present (Arnold et al., 2009; Gribble et al., 2012). The SEBT is thought to better represent functional activity over other postural control assessments because it incorporates a combination of strength, flexibility, and neuromuscular control while testing the limits of postural stability (Gribble et al., 2012). While the validity and reliability of the SEBT have been previously established, this test is interesting in that a theoretically vast number of strategies can be used to execute the movement goal and achieve a similar outcome (Gribble et al., 2012, 2013). This aspect of the SEBT has sparked several investigations with the purpose of examining the kinematics which contribute to the successful execution of this task
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(Fullam et al., 2014; Gribble et al., 2007; Robinson and Gribble, 2008a). In healthy individuals, hip and knee flexion appear to be the dominant kinematics as they accounted for 62–95% of the variance in reach distances when examined across all eight reach directions (Robinson and Gribble, 2008a). This is supported by another study which determined that changes in knee and hip flexion explained 21–59% of the variance in changes in reach distance following fatigue when data were examined in both healthy and CAI participants (Gribble et al., 2007). Finally, a later study determined that ankle dorsiflexion was the greatest sagittal plane contributor to maximal anterior reach distances in healthy participants (Fullam et al., 2014). Therefore, it appears that lower extremity sagittal plane kinematics seem to be the greatest contributors to SEBT performance in healthy individuals. Fewer studies have examined the kinematics incorporated into SEBT performance in people with CAI. A recent study (de la Motte et al., 2015) determined that individuals with CAI utilized greater amounts of trunk rotation, pelvic rotation, and hip flexion at the point of maximal reach compared to healthy individuals despite observing no significant differences between groups in any reach distances. This study (de la Motte et al., 2015) demonstrated that individuals with CAI may utilize different movement strategies which may be more reliant on nonsagittal plane motion to execute the movement goal. One potential explanation why individuals with CAI may adopt frontal or transverse plane strategies is because of restrictions in ankle dorsiflexion range of motion (RoM) which is commonly identified in these patients (Hoch et al., 2012b). Individuals with CAI have concurrently demonstrated decreased weight-bearing dorsiflexion ROM and shorter reach distances on the SEBT (Hoch et al., 2012b). This relationship has been most defined in the anterior reach direction based on multiple studies which have identified a moderate positive relationship between these assessments (Basnett et al., 2013; Gabriner et al., 2015; Hoch et al., 2012b; Terada et al., 2014). Determining if dorsiflexion RoM contributes to altered movement strategies may be an important factor in restoring preinjury movement patterns. Despite the research to this point, the kinematic predictors of SEBT reach distances in individuals with CAI remain unclear. Additionally, it is uncertain how weight-bearing dorsiflexion RoM influences kinematics patterns during SEBT performance. Therefore, the primary purpose of this study is to identify the kinematic predictors of the anterior reach distances of the SEBT in people with CAI. The secondary purpose of this study is to examine the relationships between weight-bearing RoM, anterior reach distance, and the kinematics utilized during SEBT performance. We hypothesize that anterior reach distances will be significantly predicted by non-sagittal plane kinematic variables and weight-bearing dorsiflexion RoM will be significantly correlated to anterior reach distance and several kinematic variables captured during SEBT performance. 2. Methods 2.1. Participants Fifteen physically active individuals with CAI (10 females, 5 males, 21.9 (2.1) years, 69.4 (13.3) kg, and 1.68 (0.09) m) participated in this cross-sectional study. The International Ankle Consortium's position statement on selection criteria for patients with CAI was used to guide subject inclusion (Gribble et al., 2014). All participants reported a history of ≥ 1 significant ankle sprain (2.7 (2.4)) and N1 episode of “giving way” in the previous 3 months (4.9 (5.5)). Participants also had to answer affirmatively to ≥ 4 items on the Ankle Instability Instrument (Docherty et al., 2006) (6.3 (1.5)) and report at least moderate levels of physical activity (≥4) on the NASA Physical Activity Scale (6.1 (1.8)) (Wier et al., 2001). Additionally, participants completed the Foot and Ankle Ability Measure Activities of Daily Living (90.6 (5.4%)) and Sport (79.0 (12.5%)) (Martin et al., 2005). Participants
were excluded if they experienced an ankle sprain in the 6 weeks prior to the study, had a history of lower extremity fracture or surgery, sustained any other lower extremity injuries in the past 6 months, or reported any other conditions which may affect postural control. If a subject reported bilateral ankle instability, the limb with the lower FAAM scores was used for testing. All participants provided written informed consent in compliance with the University's institutional review board.
2.2. Procedures Participants reported to the laboratory for a single testing session and performed the weight-bearing lunge test (WBLT) and the anterior reach direction of the SEBT on the involved limb. Participants were outfitted with retro-reflective markers for tracking motion during the anterior reach task after completing the WBLT. Participants wore spandex shorts, no shirt for men and a sports bra for women, and low-cut socks in order to accurately capture motion analysis data. Participants also wore Nike sneakers (Air Max Glide, Nike, Beaverton, OR, USA) provided by the investigators and were fitted to each individual in either men's or women's sizes. Maximum weight-bearing ankle dorsiflexion RoM was assessed using the WBLT knee-to-wall principle (Hoch and McKeon, 2011). This assessment technique required participants to perform a series of lunges while facing a wall. During each lunge, the ability of the anterior knee to make contact with the wall and the heel to remain in contact with the ground was assessed on the involved limb. Provided the anterior knee made contact with the wall and the heel remained planted on the floor, the participant was gradually progressed backwards. Maximum lunge distance (cm) was determined as the farthest distance (tip of the great toe to the wall) in which both criterion could be maintained (Hoch and McKeon, 2011). Three trials were performed for each participant and averaged for analysis. Upon completion of the WBLT, participants were prepared for motion capture by applying retro-reflective markers bilaterally over the following locations using double-sided tape for standing calibration: acromioclavicular joint, ASIS, PSIS, iliac crest, greater trochanter, lateral and medial femoral condyles, lateral and medial malleoli, base of the fifth metatarsal, and base of the first metatarsophalangeal joint (Weinhandl and O'Connor 2010a). Cluster plates composed of four markers were attached to the heel of the shoe and the lower leg, thigh, and mid-thoracic region on the back. An 8 camera motion analysis system (Vicon Motion Systems, Denver, CO, USA) collected kinematic data at 200 Hz. Participants were instructed to stand and raise their arms for calibration. Following calibration, all markers except the ASIS, PSIS, and cluster plates were removed for dynamic motion capture. The anterior reach direction of the SEBT was measured on the involved limb for all participants (cm). The anterior reach direction was selected because individuals with CAI have demonstrated kinematic differences in a similar reach direction in previous research (de la Motte et al., 2015). Participants performed four practice trials, followed by three test trials (Robinson and Gribble, 2008b). All participants were positioned with their foot centered in the middle of the testing grid and aligned with a tape measure secured to the floor. Participants were verbally instructed to perform maximal reaches with the uninvolved limb, followed by a single, light toe touch on the tape measure, while maintaining a single limb stance with their hands on their hips. In the event of an error, trials were discarded and repeated. Errors included lifting hands from the hips, the position of the stance foot was not maintained, the heel did not remain in contact with the floor, the toe-touch was prolonged or heavy, or the participant lost balance during the trial (Gribble and Hertel, 2003). The test trials were averaged and normalized to leg length (MAX%) for analysis.
M.C. Hoch et al. / Clinical Biomechanics 35 (2016) 37–41
2.3. Data reduction Data were post processed using previously described methods (Hoch et al., 2015). In summary, Vicon Nexus software (v1.8.5, Vicon Motion Systems, Denver, CO, USA) identified and filled any missing trajectories less than 10 frames. Data were then transferred to Visual 3D (v5.0, C-Motion, Inc., Rockville, MD) to reconstruct the model and calculate kinematic variables from marker data. Raw threedimensional marker data were low-pass filtered using a fourth-order, zero lag, recursive Butterworth filter with cutoff frequencies of 12 Hz.(Roewer et al., 2014) A kinematic model composed of eight skeletal segments (trunk, pelvis, and bilateral thighs, shanks, and feet) was created from the standing calibration trial (Weinhandl and O'Connor 2010a; Weinhandl et al., 2013). Hip joint centers were defined as 25% of the distance from the ipsilateral to the contralateral greater trochanter markers (Weinhandl and O'Connor, 2010), knee joint centers were defined as the midpoint between the lateral and medial markers on the condyles of the femur (Grood and Suntay, 1983), and ankle joint centers were defined as the midpoint between the medial and lateral malleoli markers (Wu et al., 2002). Three-dimensional ankle, knee, hip, and trunk angles were calculated using a joint coordinate system approach (Grood and Suntay, 1983; Wu et al., 2002). Positive joint angles represented hip flexion, adduction, and internal rotation; knee extension, adduction, and internal rotation; and ankle dorsiflexion, inversion, and toe-in foot progression. Positive trunk angles represented extension, as well as obliquity and rotation toward the stance limb. Kinematics for the ankle, knee, hip, and trunk were observed from initiation of the trial to the point of maximum reach. It was determined that maximum reach corresponded with maximum knee flexion. Displacement of the ankle, knee, hip, and trunk was defined as the final angular position of the joint minus initial angular position of the joint. The average of three successful trials was used to create each variable and entered into analyses. 2.4. Statistical analysis Descriptive statistics including mean and standard deviation were calculated for all dependent variables. Pearson-product moment correlations were conducted to evaluate the relationship between each kinematic displacement variable, MAX%, and the WBLT. Pearson correlation coefficients (R) were interpreted as weak (0.00–0.40), moderate (0.41–0.69), or strong (0.70–1.00) (Lomax, 1998). To examine the kinematic predictors of MAX%, a backward multiple linear regression model was developed with MAX% as the criterion variable and the kinematic variables from each joint serving as potential predictor variables. The sagittal, frontal, or transverse plane ROM variable from each joint (ankle, knee, hip, and trunk) most correlated with MAX% and not demonstrating strong correlations (r b 0.70) with other predictor variables were entered into the regression model. The significance level was set at P ≤ 0.05 for the regression analysis and the coefficient of determination (R2) was also calculated to examine the explained variance in MAX%. 3. Results Descriptive statistics for all dependent variables are presented in Table 1 and the Pearson correlation coefficients, coefficients of determination, and probability statistics between MAX% and each kinematic displacement variable are presented in Table 2. Frontal plane displacement of the trunk, hip, and ankle along with sagittal plane knee displacement were entered into the regression analysis. The final regression model (P = 0.004) included all three frontal plane variables and explained 81% of the variance in MAX%. Including sagittal plane knee displacement in the model explained b1% of additional variance in MAX% and was therefore not retained in the final model.
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Table 1 Descriptive statistics for maximal reach distance (MAX%), weight-bearing dorsiflexion ROM, and kinematic displacement values observed during Star Excursion Balance Test performance. Variable
Mean (SD)
MAX% Weight-bearing dorsiflexion ROM Trunk sagittal displacement Trunk frontal displacement Trunk transverse displacement Hip sagittal displacement Hip frontal displacement Hip transverse displacement Knee sagittal displacement Knee frontal displacement Knee transverse displacement Ankle sagittal displacement Ankle frontal displacement Ankle transverse displacement
76.92 (2.33%) 9.04 (4.28 cm) 10.86 (5.07°) 0.47 (5.30°) −11.23 (3.95°) 13.07 (9.75°) 8.02 (3.87°) 8.47 (3.95°) −50.45 (11.96°) 2.38 (3.97°) 3.27 (6.20°) 25.53 (4.77°) −5.58 (1.84°) −0.92 (2.71°)
Pearson correlation coefficients, coefficients of determination, and probability statistics between maximum weight-bearing dorsiflexion RoM and all kinematic displacement variables are presented in Table 3. Weight-bearing dorsiflexion RoM was significantly correlated to MAX%, frontal plane trunk displacement, and sagittal plane knee displacement. While other variables demonstrated moderate correlations to weight-bearing dorsiflexion RoM, they did not reach the 0.05 level of statistical significance. 4. Discussion The main finding of this study is that individuals with CAI who demonstrated greater trunk displacement toward the stance limb along with hip adduction and ankle eversion on the stance limb achieved greater MAX%. While previous research determined sagittal plane motion strongly predicted MAX% in healthy individuals (Fullam et al., 2014; Robinson and Gribble, 2008a), this study suggests that people with CAI may rely on alternative strategies from the frontal plane to achieve greater MAX%. Additionally, weight-bearing dorsiflexion ROM appears to be an intermediary determinant of MAX% in the anterior reach direction based on its relationship with kinematics throughout the lower extremity and trunk during the execution of this task. These findings suggest that individuals with CAI may adopt new movement strategies to overcome some of the common impairments which plague people with this condition. We hypothesized that MAX% would be significantly predicted by non-sagittal plane kinematic variables. This hypothesis was confirmed as lateral trunk flexion, hip adduction, and ankle eversion emerged as
Table 2 Correlations between maximal anterior reach distances and kinematic displacement variables. Variable
R
R2
P value
Trunk sagittal displacement Trunk frontal displacement⁎ Trunk transverse displacement Hip sagittal displacement Hip frontal displacement⁎ Hip transverse displacement Knee sagittal displacement⁎
−0.27 0.45 −0.24 0.36 0.42 0.30 0.55 −0.40 0.13 0.39 −0.13 −0.02
0.07 0.20 0.06 0.13 0.18 0.09 0.30 0.16 0.02 0.15 0.02 0.004
0.33 0.09 0.38 0.19 0.12 0.28 0.08 0.15 0.69 0.17 0.64 0.93
Knee frontal displacement Knee transverse displacement Ankle sagittal displacement† Ankle frontal displacement⁎ Ankle transverse displacement
⁎ Variable was entered into the regression model. † This variable was not entered into the regression because of its strong correlation to knee sagittal displacement (R = −0.92).
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Table 3 Correlations between weight-bearing dorsiflexion ROM, maximal anterior reach distances, and kinematic displacement variables. Variable
R
R2
P value
MAX% Trunk sagittal displacement Trunk frontal displacement Trunk transverse displacement Hip sagittal displacement Hip frontal displacement Hip transverse displacement Knee sagittal displacement Knee frontal displacement Knee transverse displacement Ankle sagittal displacement Ankle frontal displacement Ankle transverse displacement
0.51 −0.10 0.62 −0.51 0.47 −0.08 0.33 −0.53 0.31 0.41 0.38 −0.17 −0.11
0.26 0.01 0.38 0.26 0.22 0.006 0.11 0.28 0.09 0.17 0.14 0.03 0.01
0.05 0.72 0.01 0.055 0.10 0.77 0.27 0.04 0.26 0.13 0.16 0.55 0.70
the strongest predictors of MAX%. Although knee flexion demonstrated the strongest bivariate correlation to MAX%, this variable added b 1% of additional explained variance to the regression model and was therefore excluded. Interestingly, knee motion in the frontal plane was also moderately correlated to MAX% (r = − 0.40), but because of our method of selecting predictor variables, it was not included in the regression analysis. However, we performed a secondary analysis which determined entering this variable would produce the same final result. The regression analysis indicated that people with CAI who achieved greater reach distances did so by incorporating motion from the frontal plane. Individuals with CAI have previously demonstrated greater rotational movement from the trunk and pelvis and hip flexion compared to healthy individuals when performing the anteromedial reach (de la Motte et al., 2015). These movements were not strong predictors in this current study which may be the result of slight differences in reach direction. However, it should be underscored that the kinematic differences identified by de la Motte et al. (2015) may not have been strong predictors of MAX%. There is growing evidence that people with CAI are adopting different movement strategies than healthy individuals with no history of ankle sprain when performing the SEBT. It has been reported that healthy individuals used primarily knee and hip flexion to achieve greater reach distances (Robinson and Gribble, 2008a). This strategy was particularly evidenced in the anterior reach direction as knee and hip flexion explained 78% of the variance in MAX% (Robinson and Gribble, 2008a). However, Fullam et al. (2014) identified weak correlations between anterior MAX% and knee and hip flexion. These investigators determined that ankle sagittal plane displacement had the strongest correlation to MAX% (Fullam et al., 2014). While this study did not examine frontal or transverse plane motion, it suggests that there may be variability in SEBT execution patterns even within healthy individuals. Despite the disagreement in past research (Fullam et al., 2014; Robinson and Gribble, 2008a), the current study determined that individuals with CAI who achieved greater reach distances utilized greater frontal plane motion at the trunk, hip, and ankle which has not been documented in previous research. This movement pattern may be less stable and more precarious which may open the opportunity for future injuries when encountered in less predictable environments and more complex tasks which place greater amounts of constraint on the sensorimotor system. A secondary purpose of this study was to determine how restrictions in weight-bearing dorsiflexion ROM may contribute to the kinematics observed while performing maximal anterior reach. This is a logical factor to examine what governs the movement patterns to achieve MAX% as several studies; including the current study, have documented a moderate relationship between these variables (Basnett et al., 2013; Gabriner et al., 2015; Hoch et al., 2012b; Terada et al., 2014). Despite the number of studies which have established the correlation in variables, there is a dearth of evidence examining how weight-bearing
dorsiflexion RoM is related to the individual kinematics utilized during SEBT performance. Weight-bearing dorsiflexion RoM was moderately correlated to lateral trunk flexion, trunk rotation, hip flexion, knee flexion, knee valgus, and ankle dorsiflexion. In all cases, individuals with more dorsiflexion RoM exhibited greater motion. This indicates that restrictions in dorsiflexion impact not only ankle function but also motion throughout the lower extremity and trunk. Therefore, it appears that dorsiflexion RoM is related to MAX% because it can influence the kinematic variables which contribute to anterior reach execution. This study is not without limitations. First, the anterior reach of the SEBT was performed wearing shoes and traditionally this assessment would be performed barefoot (Gribble et al., 2012). We selected to perform this test shod because it supported the kinematic data capture protocol which was used widely within our laboratory. One potential limitation to wearing shoes is that a heel lift may occur within the shoe that would go undetected which may result in overestimates of MAX%. Second, because of the retrospective nature of the study design, it is impossible to determine if the predictors of MAX% developed as a result of CAI or if these movement patterns were in place prior to any injury history. Also, it is recommended that a minimum of 10 subjects should be included per variable entered into a multiple linear regression analysis (VanVoorhis and Morgan, 2007). This study had a lower subject to variable ratio than recommended which decreases confidence in R2 values; however, it was comparable to the previous work (Gribble et al., 2007; Robinson and Gribble, 2008a). Finally, this study cannot determine if clinically intervening on any specific kinematic variables or weight-bearing dorsiflexion RoM will restore functional movement patterns which resemble healthy individuals. While clinical interventions (Hoch et al., 2012a; Mckeon et al., 2008) have demonstrated the ability to improve MAX%, it is unclear what kinematic alterations occurred to result in greater reach distances. 5. Conclusion In people with CAI, the strongest predictors of maximal anterior reach on the SEBT were the combination of frontal plane motion of the trunk, hip, and ankle. Because these results differ from what has been established in healthy individuals, this study provides evidence that individuals with CAI adopt alternative movement strategies to accomplish functional movement goals. While a number of factors could contribute to these findings, this study provides evidence that weight-bearing dorsiflexion RoM is not only related to MAX% but also many of the kinematic variables which contribute to anterior reach performance. References Arnold, B.L., De la Motte, S., Linens, S., Ross, S.E., 2009. Ankle instability is associated with balance impairments: a meta-analysis. Med. Sci. Sports Exerc. 41, 1048–1062. Basnett, C.R., Hanish, M.J., Wheeler, T.J., Miriovsky, D.J., Danielson, E.L., Barr, J., Grindstaff, T.L., 2013. Ankle dorsiflexion range of motion influences dynamic balance in individuals with chronic ankle instability. Int. J. Sports Phys. Ther. 8, 121–128. de la Motte, S., Arnold, B.L., Ross, S.E., 2015. Trunk-rotation differences at maximal reach of the star excursion balance test in participants with chronic ankle instability. J. Athl. Train. 50, 358–365. Docherty, C.L., Gansneder, B.M., Arnold, B.L., Hurwitz, S.R., 2006. Development and reliability of the ankle instability instrument. J. Athl. Train. 41, 154–158. Fullam, K., Caulfield, B., Coughlan, G.F., Delahunt, E., 2014. Kinematic analysis of selected reach directions of the star excursion balance test compared with the Y-balance test. J. Sport Rehabil. 23, 27–35. Gabriner, M.L., Houston, M.N., Kirby, J.L., Hoch, M.C., 2015. Contributing factors to star excursion balance test performance in individuals with chronic ankle instability. Gait Posture 41, 912–916. Gribble, P.A., Hertel, J., 2003. Considerations for normalizing measures of the star excursion balance test. Meas. Phys. Educ. Exerc. Sci. 7, 89–100. Gribble, P., Hertel, J., Denegar, C., 2007. Chronic ankle instability and fatigue create proximal joint alterations during performance of the star excursion balance test. Int. J. Sports Med. 28, 236–242. Gribble, P.A., Hertel, J., Plisky, P., 2012. Using the star excursion balance test to assess dynamic postural-control deficits and outcomes in lower extremity injury: a literature and systematic review. J. Athl. Train. 47, 339–357.
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Clinical Biomechanics journal homepage: www.elsevier.com/locate/clinbiomech
Kinematic predictors of star excursion balance test performance in individuals with chronic ankle instability Matthew C. Hoch a,⁎, Stacey L. Gaven b, Joshua T. Weinhandl c a b c
School of Physical Therapy and Athletic Training, College of Heath Sciences, Old Dominion University, Health Sciences Annex, RM 102, Norfolk, VA, USA Department of Kinesiology, Franklin College, Franklin, IN, USA Department of Kinesiology, Recreation, and Sports Studies, The University of Tennessee, Knoxville, TN, USA
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Article history: Received 13 January 2016 Accepted 12 April 2016 Keywords: Ankle sprain Postural control Kinematics Dorsiflexion
a b s t r a c t Background: The Star Excursion Balance Test has identified dynamic postural control deficits in individuals with chronic ankle instability. While kinematic predictors of Star Excursion Balance Test performance have been evaluated in healthy individuals, this has not been thoroughly examined in individuals with chronic ankle instability. Methods: Fifteen individuals with chronic ankle instability completed the anterior reach direction of the Star Excursion Balance Test and weight-bearing dorsiflexion assessments. Maximum reach distances on the Star Excursion Balance Test were measured in cm and normalized to leg length. Three-dimensional trunk, hip, knee, and ankle motion of the stance limb were recorded during each anterior reach trial using a motion capture system. Sagittal, frontal, and transverse plane displacement observed from trial initiation to the point of maximum reach was calculated for each joint or segment and averaged for analysis. Pearson product–moment correlations were performed to examine the relationships between kinematic variables, maximal reach, and weight-bearing dorsiflexion. A backward multiple linear regression model was developed with maximal reach as the criterion variable and kinematic variables as predictors. Findings: Frontal plane displacement of the trunk, hip, and ankle and sagittal plane knee displacement were entered into the analysis. The final model (p = 0.004) included all three frontal plane variables and explained 81% of the variance in maximal reach. Maximal reach distance and several kinematic variables were significantly related to weight-bearing dorsiflexion. Interpretation: Individuals with chronic ankle instability who demonstrated greater lateral trunk displacement toward the stance limb, hip adduction, and ankle eversion achieved greater maximal reach. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Chronic ankle instability (CAI) is experienced by approximately 1 in 3 people who sustain an acute ankle sprain (Konradsen et al., 2002). CAI is categorized by recurrent ankle sprain symptoms, repetitive episodes of ankle “giving way,” and repeated ankle sprain injuries (Hertel, 2002). Ultimately, many individuals with CAI experience diminished health-related quality of life which may have profound effects on long-term health (Houston et al., 2015). Continuing to advance our understanding of CAI is an important step toward developing innovative treatment strategies to help patients with CAI overcome their health condition. Many of the aforementioned characteristics of CAI are thought to be linked to sensorimotor impairments which result in functional movement alterations (Hertel, 2008). This has been exemplified by a number of studies which have identified postural control deficits in people with ⁎ Corresponding author. E-mail address: [email protected] (M.C. Hoch).
http://dx.doi.org/10.1016/j.clinbiomech.2016.04.008 0268-0033/© 2016 Elsevier Ltd. All rights reserved.
CAI (Arnold et al., 2009). Postural control has been assessed with a number of measurement strategies which range from instrumented static techniques to clinically oriented dynamic techniques such as the Star Excursion Balance Test (SEBT) (Arnold et al., 2009). The SEBT involves unilateral stance while attempting to perform a maximal reach with contralateral limb in a series of reach directions (Gribble and Hertel, 2003; Gribble et al., 2012). Individuals with CAI have typically demonstrated shorter reach distances on this test which indicates dynamic postural control deficits are present (Arnold et al., 2009; Gribble et al., 2012). The SEBT is thought to better represent functional activity over other postural control assessments because it incorporates a combination of strength, flexibility, and neuromuscular control while testing the limits of postural stability (Gribble et al., 2012). While the validity and reliability of the SEBT have been previously established, this test is interesting in that a theoretically vast number of strategies can be used to execute the movement goal and achieve a similar outcome (Gribble et al., 2012, 2013). This aspect of the SEBT has sparked several investigations with the purpose of examining the kinematics which contribute to the successful execution of this task
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(Fullam et al., 2014; Gribble et al., 2007; Robinson and Gribble, 2008a). In healthy individuals, hip and knee flexion appear to be the dominant kinematics as they accounted for 62–95% of the variance in reach distances when examined across all eight reach directions (Robinson and Gribble, 2008a). This is supported by another study which determined that changes in knee and hip flexion explained 21–59% of the variance in changes in reach distance following fatigue when data were examined in both healthy and CAI participants (Gribble et al., 2007). Finally, a later study determined that ankle dorsiflexion was the greatest sagittal plane contributor to maximal anterior reach distances in healthy participants (Fullam et al., 2014). Therefore, it appears that lower extremity sagittal plane kinematics seem to be the greatest contributors to SEBT performance in healthy individuals. Fewer studies have examined the kinematics incorporated into SEBT performance in people with CAI. A recent study (de la Motte et al., 2015) determined that individuals with CAI utilized greater amounts of trunk rotation, pelvic rotation, and hip flexion at the point of maximal reach compared to healthy individuals despite observing no significant differences between groups in any reach distances. This study (de la Motte et al., 2015) demonstrated that individuals with CAI may utilize different movement strategies which may be more reliant on nonsagittal plane motion to execute the movement goal. One potential explanation why individuals with CAI may adopt frontal or transverse plane strategies is because of restrictions in ankle dorsiflexion range of motion (RoM) which is commonly identified in these patients (Hoch et al., 2012b). Individuals with CAI have concurrently demonstrated decreased weight-bearing dorsiflexion ROM and shorter reach distances on the SEBT (Hoch et al., 2012b). This relationship has been most defined in the anterior reach direction based on multiple studies which have identified a moderate positive relationship between these assessments (Basnett et al., 2013; Gabriner et al., 2015; Hoch et al., 2012b; Terada et al., 2014). Determining if dorsiflexion RoM contributes to altered movement strategies may be an important factor in restoring preinjury movement patterns. Despite the research to this point, the kinematic predictors of SEBT reach distances in individuals with CAI remain unclear. Additionally, it is uncertain how weight-bearing dorsiflexion RoM influences kinematics patterns during SEBT performance. Therefore, the primary purpose of this study is to identify the kinematic predictors of the anterior reach distances of the SEBT in people with CAI. The secondary purpose of this study is to examine the relationships between weight-bearing RoM, anterior reach distance, and the kinematics utilized during SEBT performance. We hypothesize that anterior reach distances will be significantly predicted by non-sagittal plane kinematic variables and weight-bearing dorsiflexion RoM will be significantly correlated to anterior reach distance and several kinematic variables captured during SEBT performance. 2. Methods 2.1. Participants Fifteen physically active individuals with CAI (10 females, 5 males, 21.9 (2.1) years, 69.4 (13.3) kg, and 1.68 (0.09) m) participated in this cross-sectional study. The International Ankle Consortium's position statement on selection criteria for patients with CAI was used to guide subject inclusion (Gribble et al., 2014). All participants reported a history of ≥ 1 significant ankle sprain (2.7 (2.4)) and N1 episode of “giving way” in the previous 3 months (4.9 (5.5)). Participants also had to answer affirmatively to ≥ 4 items on the Ankle Instability Instrument (Docherty et al., 2006) (6.3 (1.5)) and report at least moderate levels of physical activity (≥4) on the NASA Physical Activity Scale (6.1 (1.8)) (Wier et al., 2001). Additionally, participants completed the Foot and Ankle Ability Measure Activities of Daily Living (90.6 (5.4%)) and Sport (79.0 (12.5%)) (Martin et al., 2005). Participants
were excluded if they experienced an ankle sprain in the 6 weeks prior to the study, had a history of lower extremity fracture or surgery, sustained any other lower extremity injuries in the past 6 months, or reported any other conditions which may affect postural control. If a subject reported bilateral ankle instability, the limb with the lower FAAM scores was used for testing. All participants provided written informed consent in compliance with the University's institutional review board.
2.2. Procedures Participants reported to the laboratory for a single testing session and performed the weight-bearing lunge test (WBLT) and the anterior reach direction of the SEBT on the involved limb. Participants were outfitted with retro-reflective markers for tracking motion during the anterior reach task after completing the WBLT. Participants wore spandex shorts, no shirt for men and a sports bra for women, and low-cut socks in order to accurately capture motion analysis data. Participants also wore Nike sneakers (Air Max Glide, Nike, Beaverton, OR, USA) provided by the investigators and were fitted to each individual in either men's or women's sizes. Maximum weight-bearing ankle dorsiflexion RoM was assessed using the WBLT knee-to-wall principle (Hoch and McKeon, 2011). This assessment technique required participants to perform a series of lunges while facing a wall. During each lunge, the ability of the anterior knee to make contact with the wall and the heel to remain in contact with the ground was assessed on the involved limb. Provided the anterior knee made contact with the wall and the heel remained planted on the floor, the participant was gradually progressed backwards. Maximum lunge distance (cm) was determined as the farthest distance (tip of the great toe to the wall) in which both criterion could be maintained (Hoch and McKeon, 2011). Three trials were performed for each participant and averaged for analysis. Upon completion of the WBLT, participants were prepared for motion capture by applying retro-reflective markers bilaterally over the following locations using double-sided tape for standing calibration: acromioclavicular joint, ASIS, PSIS, iliac crest, greater trochanter, lateral and medial femoral condyles, lateral and medial malleoli, base of the fifth metatarsal, and base of the first metatarsophalangeal joint (Weinhandl and O'Connor 2010a). Cluster plates composed of four markers were attached to the heel of the shoe and the lower leg, thigh, and mid-thoracic region on the back. An 8 camera motion analysis system (Vicon Motion Systems, Denver, CO, USA) collected kinematic data at 200 Hz. Participants were instructed to stand and raise their arms for calibration. Following calibration, all markers except the ASIS, PSIS, and cluster plates were removed for dynamic motion capture. The anterior reach direction of the SEBT was measured on the involved limb for all participants (cm). The anterior reach direction was selected because individuals with CAI have demonstrated kinematic differences in a similar reach direction in previous research (de la Motte et al., 2015). Participants performed four practice trials, followed by three test trials (Robinson and Gribble, 2008b). All participants were positioned with their foot centered in the middle of the testing grid and aligned with a tape measure secured to the floor. Participants were verbally instructed to perform maximal reaches with the uninvolved limb, followed by a single, light toe touch on the tape measure, while maintaining a single limb stance with their hands on their hips. In the event of an error, trials were discarded and repeated. Errors included lifting hands from the hips, the position of the stance foot was not maintained, the heel did not remain in contact with the floor, the toe-touch was prolonged or heavy, or the participant lost balance during the trial (Gribble and Hertel, 2003). The test trials were averaged and normalized to leg length (MAX%) for analysis.
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2.3. Data reduction Data were post processed using previously described methods (Hoch et al., 2015). In summary, Vicon Nexus software (v1.8.5, Vicon Motion Systems, Denver, CO, USA) identified and filled any missing trajectories less than 10 frames. Data were then transferred to Visual 3D (v5.0, C-Motion, Inc., Rockville, MD) to reconstruct the model and calculate kinematic variables from marker data. Raw threedimensional marker data were low-pass filtered using a fourth-order, zero lag, recursive Butterworth filter with cutoff frequencies of 12 Hz.(Roewer et al., 2014) A kinematic model composed of eight skeletal segments (trunk, pelvis, and bilateral thighs, shanks, and feet) was created from the standing calibration trial (Weinhandl and O'Connor 2010a; Weinhandl et al., 2013). Hip joint centers were defined as 25% of the distance from the ipsilateral to the contralateral greater trochanter markers (Weinhandl and O'Connor, 2010), knee joint centers were defined as the midpoint between the lateral and medial markers on the condyles of the femur (Grood and Suntay, 1983), and ankle joint centers were defined as the midpoint between the medial and lateral malleoli markers (Wu et al., 2002). Three-dimensional ankle, knee, hip, and trunk angles were calculated using a joint coordinate system approach (Grood and Suntay, 1983; Wu et al., 2002). Positive joint angles represented hip flexion, adduction, and internal rotation; knee extension, adduction, and internal rotation; and ankle dorsiflexion, inversion, and toe-in foot progression. Positive trunk angles represented extension, as well as obliquity and rotation toward the stance limb. Kinematics for the ankle, knee, hip, and trunk were observed from initiation of the trial to the point of maximum reach. It was determined that maximum reach corresponded with maximum knee flexion. Displacement of the ankle, knee, hip, and trunk was defined as the final angular position of the joint minus initial angular position of the joint. The average of three successful trials was used to create each variable and entered into analyses. 2.4. Statistical analysis Descriptive statistics including mean and standard deviation were calculated for all dependent variables. Pearson-product moment correlations were conducted to evaluate the relationship between each kinematic displacement variable, MAX%, and the WBLT. Pearson correlation coefficients (R) were interpreted as weak (0.00–0.40), moderate (0.41–0.69), or strong (0.70–1.00) (Lomax, 1998). To examine the kinematic predictors of MAX%, a backward multiple linear regression model was developed with MAX% as the criterion variable and the kinematic variables from each joint serving as potential predictor variables. The sagittal, frontal, or transverse plane ROM variable from each joint (ankle, knee, hip, and trunk) most correlated with MAX% and not demonstrating strong correlations (r b 0.70) with other predictor variables were entered into the regression model. The significance level was set at P ≤ 0.05 for the regression analysis and the coefficient of determination (R2) was also calculated to examine the explained variance in MAX%. 3. Results Descriptive statistics for all dependent variables are presented in Table 1 and the Pearson correlation coefficients, coefficients of determination, and probability statistics between MAX% and each kinematic displacement variable are presented in Table 2. Frontal plane displacement of the trunk, hip, and ankle along with sagittal plane knee displacement were entered into the regression analysis. The final regression model (P = 0.004) included all three frontal plane variables and explained 81% of the variance in MAX%. Including sagittal plane knee displacement in the model explained b1% of additional variance in MAX% and was therefore not retained in the final model.
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Table 1 Descriptive statistics for maximal reach distance (MAX%), weight-bearing dorsiflexion ROM, and kinematic displacement values observed during Star Excursion Balance Test performance. Variable
Mean (SD)
MAX% Weight-bearing dorsiflexion ROM Trunk sagittal displacement Trunk frontal displacement Trunk transverse displacement Hip sagittal displacement Hip frontal displacement Hip transverse displacement Knee sagittal displacement Knee frontal displacement Knee transverse displacement Ankle sagittal displacement Ankle frontal displacement Ankle transverse displacement
76.92 (2.33%) 9.04 (4.28 cm) 10.86 (5.07°) 0.47 (5.30°) −11.23 (3.95°) 13.07 (9.75°) 8.02 (3.87°) 8.47 (3.95°) −50.45 (11.96°) 2.38 (3.97°) 3.27 (6.20°) 25.53 (4.77°) −5.58 (1.84°) −0.92 (2.71°)
Pearson correlation coefficients, coefficients of determination, and probability statistics between maximum weight-bearing dorsiflexion RoM and all kinematic displacement variables are presented in Table 3. Weight-bearing dorsiflexion RoM was significantly correlated to MAX%, frontal plane trunk displacement, and sagittal plane knee displacement. While other variables demonstrated moderate correlations to weight-bearing dorsiflexion RoM, they did not reach the 0.05 level of statistical significance. 4. Discussion The main finding of this study is that individuals with CAI who demonstrated greater trunk displacement toward the stance limb along with hip adduction and ankle eversion on the stance limb achieved greater MAX%. While previous research determined sagittal plane motion strongly predicted MAX% in healthy individuals (Fullam et al., 2014; Robinson and Gribble, 2008a), this study suggests that people with CAI may rely on alternative strategies from the frontal plane to achieve greater MAX%. Additionally, weight-bearing dorsiflexion ROM appears to be an intermediary determinant of MAX% in the anterior reach direction based on its relationship with kinematics throughout the lower extremity and trunk during the execution of this task. These findings suggest that individuals with CAI may adopt new movement strategies to overcome some of the common impairments which plague people with this condition. We hypothesized that MAX% would be significantly predicted by non-sagittal plane kinematic variables. This hypothesis was confirmed as lateral trunk flexion, hip adduction, and ankle eversion emerged as
Table 2 Correlations between maximal anterior reach distances and kinematic displacement variables. Variable
R
R2
P value
Trunk sagittal displacement Trunk frontal displacement⁎ Trunk transverse displacement Hip sagittal displacement Hip frontal displacement⁎ Hip transverse displacement Knee sagittal displacement⁎
−0.27 0.45 −0.24 0.36 0.42 0.30 0.55 −0.40 0.13 0.39 −0.13 −0.02
0.07 0.20 0.06 0.13 0.18 0.09 0.30 0.16 0.02 0.15 0.02 0.004
0.33 0.09 0.38 0.19 0.12 0.28 0.08 0.15 0.69 0.17 0.64 0.93
Knee frontal displacement Knee transverse displacement Ankle sagittal displacement† Ankle frontal displacement⁎ Ankle transverse displacement
⁎ Variable was entered into the regression model. † This variable was not entered into the regression because of its strong correlation to knee sagittal displacement (R = −0.92).
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Table 3 Correlations between weight-bearing dorsiflexion ROM, maximal anterior reach distances, and kinematic displacement variables. Variable
R
R2
P value
MAX% Trunk sagittal displacement Trunk frontal displacement Trunk transverse displacement Hip sagittal displacement Hip frontal displacement Hip transverse displacement Knee sagittal displacement Knee frontal displacement Knee transverse displacement Ankle sagittal displacement Ankle frontal displacement Ankle transverse displacement
0.51 −0.10 0.62 −0.51 0.47 −0.08 0.33 −0.53 0.31 0.41 0.38 −0.17 −0.11
0.26 0.01 0.38 0.26 0.22 0.006 0.11 0.28 0.09 0.17 0.14 0.03 0.01
0.05 0.72 0.01 0.055 0.10 0.77 0.27 0.04 0.26 0.13 0.16 0.55 0.70
the strongest predictors of MAX%. Although knee flexion demonstrated the strongest bivariate correlation to MAX%, this variable added b 1% of additional explained variance to the regression model and was therefore excluded. Interestingly, knee motion in the frontal plane was also moderately correlated to MAX% (r = − 0.40), but because of our method of selecting predictor variables, it was not included in the regression analysis. However, we performed a secondary analysis which determined entering this variable would produce the same final result. The regression analysis indicated that people with CAI who achieved greater reach distances did so by incorporating motion from the frontal plane. Individuals with CAI have previously demonstrated greater rotational movement from the trunk and pelvis and hip flexion compared to healthy individuals when performing the anteromedial reach (de la Motte et al., 2015). These movements were not strong predictors in this current study which may be the result of slight differences in reach direction. However, it should be underscored that the kinematic differences identified by de la Motte et al. (2015) may not have been strong predictors of MAX%. There is growing evidence that people with CAI are adopting different movement strategies than healthy individuals with no history of ankle sprain when performing the SEBT. It has been reported that healthy individuals used primarily knee and hip flexion to achieve greater reach distances (Robinson and Gribble, 2008a). This strategy was particularly evidenced in the anterior reach direction as knee and hip flexion explained 78% of the variance in MAX% (Robinson and Gribble, 2008a). However, Fullam et al. (2014) identified weak correlations between anterior MAX% and knee and hip flexion. These investigators determined that ankle sagittal plane displacement had the strongest correlation to MAX% (Fullam et al., 2014). While this study did not examine frontal or transverse plane motion, it suggests that there may be variability in SEBT execution patterns even within healthy individuals. Despite the disagreement in past research (Fullam et al., 2014; Robinson and Gribble, 2008a), the current study determined that individuals with CAI who achieved greater reach distances utilized greater frontal plane motion at the trunk, hip, and ankle which has not been documented in previous research. This movement pattern may be less stable and more precarious which may open the opportunity for future injuries when encountered in less predictable environments and more complex tasks which place greater amounts of constraint on the sensorimotor system. A secondary purpose of this study was to determine how restrictions in weight-bearing dorsiflexion ROM may contribute to the kinematics observed while performing maximal anterior reach. This is a logical factor to examine what governs the movement patterns to achieve MAX% as several studies; including the current study, have documented a moderate relationship between these variables (Basnett et al., 2013; Gabriner et al., 2015; Hoch et al., 2012b; Terada et al., 2014). Despite the number of studies which have established the correlation in variables, there is a dearth of evidence examining how weight-bearing
dorsiflexion RoM is related to the individual kinematics utilized during SEBT performance. Weight-bearing dorsiflexion RoM was moderately correlated to lateral trunk flexion, trunk rotation, hip flexion, knee flexion, knee valgus, and ankle dorsiflexion. In all cases, individuals with more dorsiflexion RoM exhibited greater motion. This indicates that restrictions in dorsiflexion impact not only ankle function but also motion throughout the lower extremity and trunk. Therefore, it appears that dorsiflexion RoM is related to MAX% because it can influence the kinematic variables which contribute to anterior reach execution. This study is not without limitations. First, the anterior reach of the SEBT was performed wearing shoes and traditionally this assessment would be performed barefoot (Gribble et al., 2012). We selected to perform this test shod because it supported the kinematic data capture protocol which was used widely within our laboratory. One potential limitation to wearing shoes is that a heel lift may occur within the shoe that would go undetected which may result in overestimates of MAX%. Second, because of the retrospective nature of the study design, it is impossible to determine if the predictors of MAX% developed as a result of CAI or if these movement patterns were in place prior to any injury history. Also, it is recommended that a minimum of 10 subjects should be included per variable entered into a multiple linear regression analysis (VanVoorhis and Morgan, 2007). This study had a lower subject to variable ratio than recommended which decreases confidence in R2 values; however, it was comparable to the previous work (Gribble et al., 2007; Robinson and Gribble, 2008a). Finally, this study cannot determine if clinically intervening on any specific kinematic variables or weight-bearing dorsiflexion RoM will restore functional movement patterns which resemble healthy individuals. While clinical interventions (Hoch et al., 2012a; Mckeon et al., 2008) have demonstrated the ability to improve MAX%, it is unclear what kinematic alterations occurred to result in greater reach distances. 5. Conclusion In people with CAI, the strongest predictors of maximal anterior reach on the SEBT were the combination of frontal plane motion of the trunk, hip, and ankle. Because these results differ from what has been established in healthy individuals, this study provides evidence that individuals with CAI adopt alternative movement strategies to accomplish functional movement goals. While a number of factors could contribute to these findings, this study provides evidence that weight-bearing dorsiflexion RoM is not only related to MAX% but also many of the kinematic variables which contribute to anterior reach performance. References Arnold, B.L., De la Motte, S., Linens, S., Ross, S.E., 2009. Ankle instability is associated with balance impairments: a meta-analysis. Med. Sci. Sports Exerc. 41, 1048–1062. Basnett, C.R., Hanish, M.J., Wheeler, T.J., Miriovsky, D.J., Danielson, E.L., Barr, J., Grindstaff, T.L., 2013. Ankle dorsiflexion range of motion influences dynamic balance in individuals with chronic ankle instability. Int. J. Sports Phys. Ther. 8, 121–128. de la Motte, S., Arnold, B.L., Ross, S.E., 2015. Trunk-rotation differences at maximal reach of the star excursion balance test in participants with chronic ankle instability. J. Athl. Train. 50, 358–365. Docherty, C.L., Gansneder, B.M., Arnold, B.L., Hurwitz, S.R., 2006. Development and reliability of the ankle instability instrument. J. Athl. Train. 41, 154–158. Fullam, K., Caulfield, B., Coughlan, G.F., Delahunt, E., 2014. Kinematic analysis of selected reach directions of the star excursion balance test compared with the Y-balance test. J. Sport Rehabil. 23, 27–35. Gabriner, M.L., Houston, M.N., Kirby, J.L., Hoch, M.C., 2015. Contributing factors to star excursion balance test performance in individuals with chronic ankle instability. Gait Posture 41, 912–916. Gribble, P.A., Hertel, J., 2003. Considerations for normalizing measures of the star excursion balance test. Meas. Phys. Educ. Exerc. Sci. 7, 89–100. Gribble, P., Hertel, J., Denegar, C., 2007. Chronic ankle instability and fatigue create proximal joint alterations during performance of the star excursion balance test. Int. J. Sports Med. 28, 236–242. Gribble, P.A., Hertel, J., Plisky, P., 2012. Using the star excursion balance test to assess dynamic postural-control deficits and outcomes in lower extremity injury: a literature and systematic review. J. Athl. Train. 47, 339–357.
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