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Ankle work and dynamic joint stiffness in high- compared to low-arched athletes during a barefoot running task
Human Movement Science 34 (2014) 147–156
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Human Movement Science journal homepage: www.elsevier.com/locate/humov
Ankle work and dynamic joint stiffness in high- compared to low-arched athletes during a barefoot running task Douglas W. Powell a,⇑, D.S. Blaise Williams 3rd b, Brett Windsor a, Robert J. Butler c, Songning Zhang d a
Department of Physical Therapy, Campbell University, Buies Creek, NC, USA Department of Physical Therapy, Virginia Commonwealth University, Richmond, VA, USA c Doctor of Physical Therapy Division, Duke University, Durham, NC, USA d Department of Kinesiology, Recreation & Sport Studies, The University of Tennessee, Knoxville, TN, USA b
a r t i c l e
i n f o
Article history: Available online 17 February 2014 PsycINFO classification: 2540 Keywords: Running Barefoot Kinetics Injury Ankle Arch Foot
a b s t r a c t High- (HA) and low-arched (LA) athletes have an exaggerated risk of injury. Ankle joint stiffness is a potential underlying mechanism for the greater rate of injury within these two functionally different groups. An alternative candidate mechanism of injury in HA and LA athletes pertains to the efficacy of the foot as a rigid lever during propulsion. The purpose of this study was to quantify the differences in ankle dynamic joint stiffness, and ankle braking work and ankle propulsive work during stance phase of running. Methods: Ten HA and ten LA athletes performed five barefoot running trials while ground reaction forces and three-dimensional kinematics were recorded. Ankle dynamic joint stiffness was calculated as the slope of the ankle joint moment–ankle joint angle plot during load attenuation. Ankle braking and propulsive work values were calculated for the stance phase. Results: HA athletes had significantly greater ankle dynamic joint stiffness and significantly smaller ankle net and propulsive work than LA athletes. Conclusions: These data demonstrate that HA and LA athletes exhibit unique biomechanical patterns during running. These patterns may be related to lower extremity injury. Ó 2014 Elsevier B.V. All rights reserved.
⇑ Corresponding author. Address: Department of Physical Therapy, Campbell University, PO Box 1090, Buies Creek, NC, USA. Office: +1 (910) 893 1757. E-mail address: [email protected] (D.W. Powell). http://dx.doi.org/10.1016/j.humov.2014.01.007 0167-9457/Ó 2014 Elsevier B.V. All rights reserved.
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1. Introduction Mal-alignment and aberrant mechanics of the foot and ankle have been implicated as contributing factors to lower extremity injury (Kaufman, Brodine, Shaffer, Johnson, & Cullison, 1999; Williams, McClay, & Hamill, 2001). It has been demonstrated that individuals with high- or lowarched feet have a greater incidence of lower extremity injury than individuals with a normal arch (Kaufman et al., 1999). Further, it has been shown that high- and low-arched athletes exhibit divergent overuse injury patterns with high-arched athletes experiencing a greater number of bony injuries to the lateral aspect of the lower extremity while low-arched individuals experience a greater number of soft tissue injuries to the medial aspect of the lower extremity (Williams et al., 2001). These unique injury patterns have been attributed to the role of the foot in load attenuation and the altered transmission of force through the lower extremity kinetic chain (Kaufman et al., 1999; Powell, Hanson, Long, & Williams, 2012a; Powell, Long, Milner, & Zhang, 2011; Powell, Long, Milner, & Zhang, 2012b; Williams, Davis, Scholz, Hamill, & Buchanan, 2004; Williams et al., 2001; Williams et al., 2004). It has been demonstrated that high-arched feet are typically rigid and exhibit greater stiffness while low-arched feet are typically mobile and exhibit less stiffness compared to normal feet (Zifchock, Davis, Hillstrom, & Song, 2006). Previous research has also reported significantly greater knee joint stiffness in high- compared to low-arched athletes during a level running task (Williams et al., 2004). It has been suggested that exaggerated or insufficient stiffness throughout the lower extremity predispose an individual to injury (Butler, Crowell, & Davis, 2003; Williams et al., 2004; Williams, McClay, Hamill, & Buchanan, 2001). Though the roles of foot structure and joint stiffness in lower extremity injury have been established, no previous study has investigated differences in ankle joint stiffness, specifically during the period believed to be most responsible for overuse injury, load attenuation. Currently research hypotheses have identified aberrant patterns of lower extremity loading in response to load attenuation as a potential mechanism for overuse injury to the lower extremity. An alternative hypothesis pertains to the role and efficacy of the foot as a functional lever during the propulsive portion of the stance phase. Research has demonstrated that lower extremity joint work values are significantly greater during the propulsive compared to braking phases of walking (DeVita, Helseth, & Hortobagyi, 2007) and running (Heiderscheit, Chumanov, Michalski, Wille, & Ryan, 2011). Moreover, in running, the greatest differences in lower extremity joint work values, when comparing the braking and propulsive phases of stance, have been observed at the ankle joint (Heiderscheit et al., 2011). Specifically, the magnitude of positive ankle work in propulsion was two- to threefold greater than negative ankle work in braking when athletes ran at different step frequencies. It is possible that the low-arched, mobile foot is a less effective lever for the application of muscle force to the ground and requires greater muscle work to achieve similar mechanical output compared to the normal or high-arched foot. Further, it can be postulated that the interaction of the low-arched, mobile foot with increased muscle work could potentially underlie soft tissue overuse injury in low-arched athletes, particularly during the propulsive portion of the stance phase. However, no previous research study has quantified the differences in ankle joint work between high- and low-arched athletes. If significant differences in ankle dynamic joint stiffness and work values are present in the braking compared to propulsive phases of running stance, greater insight may be gained into the mechanisms underlying the unique injury patterns experienced by these two functionally different groups. Therefore, the purpose of this study is to investigate the differences in dynamic joint stiffness and joint work of the ankle during the total stance phase as well as the braking and propulsive portions of the stance phase during running. It was hypothesized that high- compared to low-arched athletes would exhibit significantly greater ankle dynamic joint stiffness values and significantly smaller ankle work values throughout the stance phase.
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2. Materials and methods 2.1. Participants Twenty individuals (10 high-arched; 10 low-arched) were recruited for participation in this study from a larger study of 55 healthy female recreational athletes. Table 1 presents subject anthropometric measurements. Participants qualified for inclusion if they were aged between 18 and 30 years, participated a minimum of 8 h per week in recreational athletics, and had an arch height index (AHI) greater than .377 or lower than .283. AHI values used to define the HA and LA groups represent the top and bottom 10% of the population defined as 1.5 standard deviations above and below the mean AHI of .330 (±.031) determined from 604 feet (Zhang, Powell, Keefer, King, & Hamill, 2007). Individuals with an AHI greater than .377 were placed in the high-arched (HA) group while participants with an AHI less than .283 were placed in the low-arched (LA) group. Arch type was determined using arch height index which was defined as the height of the dorsum at half the total foot length divided by the truncated foot length, or the distance between the posterior calcaneus and the first metatarsophalangeal joint (Powell et al., 2011; Williams & McClay, 2000). All participants were free of injury at the time of testing and signed a written informed consent form approved by the Institutional Review Board at the university prior to participating in this study. 2.2. Experimental protocol Each participant completed two laboratory testing sessions. The initial session consisted of collecting subject information, anthropometric measurements, and arch measurements including height, mass, total foot length, truncated foot length and dorsum height. During the second laboratory session, participants performed five barefoot running trials at self-selected velocities. Running velocities were determined using three practice trials prior to testing and were monitored and maintained (±5%) during testing. Ground reaction forces and three-dimensional (3D) kinematic data were collected. 2.3. Instrumentation A seven-camera motion capture system (240 Hz, Vicon Motion Systems Ltd., Oxford, UK) and force platform (1200 Hz, OR-6; AMTI, Watertown, Massachusetts) were used to collect 3D kinematic data and ground reaction forces from the right side of the lower extremity of each participant, respectively. Retro-reflective markers (14 mm) were placed over anatomical landmarks including the first and fifth metatarsal heads, medial and lateral malleoli, medial and lateral femoral condyles to define the joint center of foot, shank and thigh segments, respectively. The pelvis was defined using retro-reflective markers placed on the right and left anterior superior iliac spines, right and left posterior superior iliac spines, right and left iliac crests and the right and left greater trochanters. The pelvis was tracked using two marker clusters, each composed of two 14 mm retro-reflective markers placed on thermoplastic. The thigh and shank segments were tracked using a rigid cluster with four 14 mm retro-reflective markers placed on the lateral aspect of the segment. The foot was tracked using three 9.5 mm markers fixed to the skin using double-sided (wig) tape placed over the bony aspects of the posterior superior and inferior aspects of the calcaneus and the peroneal tubercle. The standing calibration was collected during quiet standing with the arms placed across the chest with the feet pointed forward in line with
Table 1 Anthropometric characteristics, and running velocities in high- (HA) and low-arched (LA) female athletes. Group
Height (m)
Mass (kg)
AHI
Running velocity (m/s)
HA LA
1.62 (.07) 1.63 (.07)
58.3 (5.4) 58.9 (10.9)
.386 (.010)a .259 (.043)
2.79 (.28) 2.73 (.29)
Presented as mean (SD). a Denotes significant difference between HA and LA athletes.
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the global coordinate system. Anatomical markers used to define the segments were removed prior to dynamic trials and only tracking markers remained on the subject during dynamic trials. The subject’s right foot contacted the force platform during each trial. Two pairs of photo cells and an electronic timer (63501 IR, Lafayette Instruments, Inc., IN, USA) were used to monitor running velocities. 2.4. Data analysis Three-dimensional kinematic data and ground reaction force data were filtered with a low-pass, fourth-order zero-lag Butterworth filter with cut-off frequencies of 10 and 50 Hz, respectively (Hunt & Smith, 2004; Powell et al., 2012a; Williams et al., 2004). Joint angles, internal joint moments were calculated using Visual 3D (C-Motion, Inc., Rockville, Maryland). The ankle joint angle was defined as the difference between the angle of the shank and the angle of the foot minus 90°, to account for the orientation of the foot. Internal joint moments and joint powers were normalized to body mass. Ankle joint angles, internal joint moments and ankle powers were only assessed from initial contact to toe-off (stance phase). Custom software (Matlab 2009, MathWorks, Natick, MA, USA) was used to calculate kinetic variables of interest including dynamic joint stiffness and ankle work. Dynamic joint stiffness, determined using a torsional spring model (Butler et al., 2003; Gabriel et al., 2008; Lamontagne, Malouin, & Richards, 2000; Lark, Buckley, Bennett, Jones, & Sargeant, 2003), was calculated as the slope of the ankle moment–angle plot during the braking phase of stance (Fig. 1). Ankle work was quantified as
Fig. 1. An ankle moment–angle plot from a representative athlete during a barefoot running trial. Significant gait events including initial contact (A), midstance (B) and toe-off (C) are depicted. The braking phase was defined as the period between initial contact and midstance while the propulsive phase was defined as the period between midstance and toe-off. Ankle dynamic joint stiffness was quantified as the slope of the ankle moment–angle plot during the braking portion of the stance phase of running, represented by a solid line. Ankle work was defined as the area beneath the ankle moment–angle curve for the entire stance phase (net) as well as the braking and propulsive portions of the stance phase.
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the ankle power integrated with respect to time. Ankle work was calculated for the total stance phase as well as for the braking and propulsive phases independently. The stance phase was divided into the braking and propulsive phases defined by antero-posterior ground reaction forces (AP GRFs). The braking phase was defined as the period prior to the AP GRF crossing baseline (zero), indicating a negative or backward GRF vector. The propulsive phase was defined as the period after the AP GRF crossed baseline (zero), indicating a positive or forward GRF vector. A subject mean was calculated as the average of the five trials from each movement condition for dynamic joint stiffness and ankle work variables. 2.5. Statistical analysis Student’s t-tests were used to compare anthropometric measurements and running velocities between the HA and LA athletes. Independent samples t-tests were used to determine the effect of foot type on ankle dynamic joint stiffness, net ankle work, ankle braking work, and ankle propulsive work during stance phase. Significance was set at p < .05. All statistical analyses were conducted using SPSS 21.0 (IBM, Chicago, IL, USA). 3. Results The HA and LA athletes had similar heights and masses (Table 1). The HA athletes had significantly greater arch height index values than the LA athletes (p < .001). Running velocities were not significantly different between the HA and LA athletes (p = .356; Table 1). Fig. 2 presents ankle joint angle
Fig. 2. Sagittal plane ankle joint angles from representative high- (black, solid) and low-arched athletes (blue, dashed) during the barefoot running protocol. In these representative subjects, the HA athlete had significantly greater plantarflexion angles throughout the stance phase while the LA athlete exhibited greater peak dorsiflexion and dorsiflexion excursion. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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profiles from HA and LA athletes during the barefoot running protocol. Visually, the HA athletes had less plantarflexion at initial contact, displayed less peak dorsiflexion and moved through a smaller range of motion than LA athletes during the stance phase. Fig. 3 presents ankle moment–angle plots in representative high- and low-arched athletes. Visually, the high-arched athletes presented a steeper slope during the braking and propulsive portions of the stance phase than the low-arched athletes. Further, the range of motion over which the ankle moment was produced was substantially smaller in the high- compared to low-arched athletes. Ankle dynamic joint stiffness (Table 2) was calculated using a torsional spring model and was quantified as the slope of the ankle joint moment–ankle joint angle plot during the braking phase of stance. The statistical analysis revealed significantly greater ankle dynamic joint stiffness values in the HA compared to LA athletes (p = .042).
Fig. 3. Representative ankle moment–angle plots for HA (solid) and LA (- - -) athletes from a sample barefoot running trial. HA athletes had significantly greater ankle dynamic joint stiffness values than LA athletes evidenced in this example by the steeper slope of the ankle moment-ankle plot during the braking portion of stance. Further, HA athletes produced significantly less net ankle work and propulsive ankle work than LA athletes, visualized in this figure as a smaller area within the ankle moment– angle plot.
Table 2 Average net ankle work and work done by the ankle during the braking and propulsive phases of the stance phase of running in high- (HA) and low-arched (LA) female athletes. Group
Net work (J/kg)
HA LA
.44 (.09)a .66 (.11)
Braking work (J/kg) .52 (.13) .44 (.08)
Propulsive work (J/kg) .90 (.12)a 1.02 (.07)
Presented as mean (SD). a Denotes significant difference between HA and LA athletes.
Dynamic joint stiffness (Nm/kg/°) .274 (.098)a .199 (.046)
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Ankle joint work was calculated as the ankle joint power integrated with respect to time (Table 2). Statistical analysis revealed that HA athletes exhibited significantly smaller net (p = .023) and propulsive (p = .040) ankle work values compared to LA athletes. No significant differences in braking ankle joint work were observed between the HA and LA athletes (p = .517).
4. Discussion The objective of this study was to compare ankle dynamic joint stiffness and ankle work in highand low-arched athletes during a barefoot running task. This study presents novel findings pertaining to the relationship between foot structure and ankle joint mechanics. Dynamic joint stiffness quantifies the contribution of passive and active tissues to load attenuation during the braking portion of the stance phase (Gabriel et al., 2008; Lamontagne et al., 2000; Lin, Chen, & Lin, 2011). Describing the relationship between ankle joint moments and ankle displacement, dynamic joint stiffness of the ankle has been previously used to investigate the interaction of motor control and ankle joint mechanics in response to advanced age and injury mechanisms (Crenna & Frigo, 2011; Gabriel et al., 2008; Lin et al., 2011). Dynamic joint stiffness was used in the current study to quantify the role of the ankle mechanics in load attenuation. The barefoot running task was selected in the present study to examine the active role of the plantarflexors during both the braking and propulsive portions of the stance phase (Williams, Green, & Wurzinger, 2012) and to elucidate the functional differences in the mechanics of the foot and ankle in high- compared to low-arched athletes. The dynamic joint stiffness values presented in the current study are substantially greater than those previously reported in walking (Gabriel et al., 2008) or running studies using similar calculations of stiffness (Lin et al., 2011). However, these observed differences are likely due to the differences in the experimental protocol used in each study. For example, it is logical that previous studies investigating ankle mechanics in a walking task would report lower dynamic joint stiffness values as walking is associated with lower mechanical demand and smaller ankle joint moments compared to running (Gabriel et al., 2008). Further, dynamic joint stiffness values reported in the present study are also twofold greater than those previously reported in healthy adults (.150 ± .068 Nm/kg/°) during a running task (Lin et al., 2011). However, the exaggerated dynamic joint stiffness values presented currently may be explained by the barefoot condition used in this study compared to the shod running condition previously investigated. A common adaptation in response to barefoot running is the adoption of a mid- to forefoot strike pattern (Lieberman et al., 2010). By performing a barefoot running task, the modified strike pattern requires greater involvement of the ankle plantarflexor musculature during load attenuation, resulting in substantially greater ankle plantarflexion moments. When performing shod running with a heel strike, the ankle plantarflexors are less involved during the load attenuation portion of the stance phase, over which the dynamic joint stiffness values were calculated. In the present study, HA athletes exhibited significantly greater dynamic joint stiffness values than their LA counterparts. The dynamic joint stiffness calculation is a measure of the interaction of ankle joint kinematics and kinetics. The findings of this and previous studies demonstrate that HA athletes absorb load over a shorter period of time using a smaller range of motion in multiple planes of motion (Butler, Davis, & Hamill, 2006; Powell et al., 2011; Williams et al., 2004; Williams et al.,2001). Previous research has demonstrated that high- compared to LA produce significantly greater loading rates due to a significantly earlier peak vertical ground reaction force during a running task (Williams et al., 2004). Similarly, it has been shown that HA athletes move through smaller ranges of ankle motion in the sagittal (Williams et al., 2004) and frontal planes (Butler et al., 2006; Powell et al., 2011; Williams et al.,2001) during running. It could be postulated that the reduced ranges of motion exhibited by HA athletes during running are an extension of reduced flexibility within the foot-Achille’s complex (Zifchock et al., 2006). HA feet have been shown to exhibit greater arch stiffness in response to a vertical load than low-arched athletes (Zifchock et al., 2006). Furthermore, a study using a multisegment foot model demonstrated that HA athletes exhibit smaller eversion and eversion excursions within the foot than LA athletes in response to vertical load (Powell et al., 2012b). The inability of the foot to absorb load through sagittal and frontal plane motions results in greater magnitudes and rates of loading at the level of the ankle and potentially greater ankle dynamic joint stiffness.
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In addition to greater dynamic joint stiffness values during load attenuation, HA runners exhibited significantly smaller net ankle work and smaller ankle work during the propulsive portion of the stance phase. The ankle work values presented in this study are lower than those presented in previous running studies (Heiderscheit et al., 2011); however, participants in this study ran at a slower velocity than the 2.90 m/s in the study by Heiderscheit et al. (2011). Further, these data were collected during barefoot rather than shod running which may have contributed to a reduced running velocity. Therefore, the imposed mechanical demand in the current study would be lower than in the study by Heiderscheit et al. (2011) and could require a smaller mechanical output from the lower extremity to successfully complete the running task. In the present study, HA athletes produced significantly smaller net ankle work than LA athletes. The inequalities in net ankle work were dominated by differences in ankle work during the propulsive portion of the stance phase. Several candidate mechanisms may underlie the observed differences in ankle kinetics. One potential mechanism pertains to the efficacy of the foot as a rigid lever in highcompared to low-arched athletes. Previous research has identified a significant relationship between arch height index and arch stiffness or rigidity of the foot (Zifchock et al., 2006). Therefore, the rigid foot of the high-arched athlete may be a better functional lever during push off than the low-arched foot. A more efficient lever would act to more efficiently apply forces generated by the triceps surae to the ground for propulsion. Therefore, the non-rigid low-arched foot may be a less effective lever than the HA foot and may require greater force generation from the triceps surae muscles to create a similar mechanical output. An alternative but related mechanism potentially explaining the observed differences in net and propulsive ankle work values pertains to the location of the center of pressure beneath the foot during the stance phase of running. Due to the barefoot running condition, all participants adopted a mid- or forefoot strike pattern. A post hoc analysis of the lever arm length of the foot was conducted to determine the validity of this potential mechanism. The lever arm of the foot was defined as the horizontal distance in the sagittal plane between the center of pressure and the center of ankle joint rotation. A Student’s t-test was used to compare mean lever arms between the high- and low-arched groups. The post hoc analysis revealed that high-arched athletes had significantly longer foot lever arms compared to the low-arched athletes (HA: .093 ± .010 m; LA: .084 ± .006 m). It could be postulated that the flexible LA foot collapsed shortly after initial contact moving the center of pressure closer to the ankle joint center, functionally shortening the lever arm of the foot and requiring a greater muscular work to produce a similar mechanical output. A smaller lever arm due to exaggerated arch flexibility may require LA individuals to produce greater work over a longer duration than HA athletes to produce a given mechanical outcome. Conversely, the rigid HA foot experiences less deformation following initial contact (Butler et al., 2003; Powell et al., 2011; Powell et al., 2012b; Williams et al., 2004; Williams et al.,2001) and the center of pressure remains further from the center of ankle joint rotation. The greater distance of the center of pressure from the center of joint rotation in HA athletes may more effectively transfer the forces of the Achilles tendon and triceps surae to the ground. The enhanced efficacy of the rigid HA foot in transferring forces to the ground may result in smaller durations of propulsive ankle power and therefore lower ankle joint work values. These findings support the hypothesis that the rigid high-arched foot is a more effective lever compared to the flexible low-arched foot. The findings of this study present novel data pertaining to differences in lower extremity biomechanics between high- and low-arched athletes in running. Specifically, previous research investigating the role of foot type in lower extremity running mechanics has focused on load attenuation. To the knowledge of the authors, no previous research study examined the role of the foot in propulsion in these two subject groups. However, the findings of this study suggest that substantial differences in foot and ankle biomechanics exists in high- compared to low-arched athletes. It is possible that these biomechanical differences may be a contributing factor to the unique injury patterns experienced by these two groups. Though the findings of this study present are novel and may relate to candidate injury mechanisms in HA and LA athletes, the authors acknowledge the limitations of this study. The relatively small sample size of ten athletes per group reduces the statistical power and limits the generalizations that can be made from these data. However, statistical differences were found between the HA and LA athletes suggesting that sufficient statistical power was present. Another limitation of this study is that only
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female athletes were investigated. It has been demonstrated that female athletes adopt an anklebased strategy during athletic tasks (Kernozek, Torry, H, Cowley, & Tanner, 2005; McLean et al., 2007), which may exaggerate the differences between high- and low-arched groups observed in this study compared to the general population. 5. Conclusions The findings of this study demonstrate significant differences in ankle biomechanics adopted by high- and low-arched athletes in load attenuation and propulsion during barefoot running. Further, these data demonstrate significant differences in lever arm lengths of the foot–ankle complex in highcompared to low-arched athletes. These unique mechanisms may underlie the distinct overuse injury patterns exhibited by each of these functionally different groups. Conflict of interest None. Financial disclosure None. References Butler, R. J., Crowell, H. P., 3rd, & Davis, I. M. (2003). Lower extremity stiffness: Implications for performance and injury. Clin Biomech (Bristol, Avon), 18(6), 511–517. Butler, R. J., Davis, I. S., & Hamill, J. (2006). Interaction of arch type and footwear on running mechanics. Am J Sports Med, 34(12), 1998–2005. http://dx.doi.org/10.1177/0363546506290401. Crenna, P., & Frigo, C. (2011). Dynamics of the ankle joint analyzed through moment-angle loops during human walking: gender and age effects. Hum Mov Sci, 30(6), 1185–1198. http://dx.doi.org/10.1016/j.humov.2011.02.009. DeVita, P., Helseth, J., & Hortobagyi, T. (2007). Muscles do more positive than negative work in human locomotion. J Exp Biol, 210(Pt 19), 3361–3373. http://dx.doi.org/10.1242/jeb.003970. Gabriel, R. C., Abrantes, J., Granata, K., Bulas-Cruz, J., Melo-Pinto, P., & Filipe, V. (2008). Dynamic joint stiffness of the ankle during walking: Gender-related differences. Phys Ther Sport, 9(1), 16–24. http://dx.doi.org/10.1016/j.ptsp.2007.08.002. Heiderscheit, B. C., Chumanov, E. S., Michalski, M. P., Wille, C. M., & Ryan, M. B. (2011). Effects of step rate manipulation on joint mechanics during running. Med Sci Sports Exerc, 43(2), 296–302. http://dx.doi.org/10.1249/MSS.0b013e3181ebedf4. Hunt, A. E., & Smith, R. M. (2004). Mechanics and control of the flat versus normal foot during the stance phase of walking. Clin Biomech (Bristol, Avon), 19(4), 391–397. Kaufman, K. R., Brodine, S. K., Shaffer, R. A., Johnson, C. W., & Cullison, T. R. (1999). The effect of foot structure and range of motion on musculoskeletal overuse injuries. Am J Sports Med, 27(5), 585–593. Kernozek, T. W., Torry, M. R., Van Hoof, H., Cowley, H., & Tanner, S. (2005). Gender differences in frontal and sagittal plane biomechanics during drop landings. Med Sci Sports Exerc, 37(6), 1003–1012. discussion 1013. Lamontagne, A., Malouin, F., & Richards, C. L. (2000). Contribution of passive stiffness to ankle plantarflexor moment during gait after stroke. Arch Phys Med Rehabil, 81(3), 351–358. Lark, S. D., Buckley, J. G., Bennett, S., Jones, D., & Sargeant, A. J. (2003). Joint torques and dynamic joint stiffness in elderly and young men during stepping down. Clin Biomech (Bristol, Avon), 18(9), 848–855. Lieberman, D. E., Venkadesan, M., Werbel, W. A., Daoud, A. I., D’Andrea, S., Davis, I. S., et al (2010). Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature, 463(7280), 531–535. http://dx.doi.org/10.1038/ nature08723. Lin, C. F., Chen, C. Y., & Lin, C. W. (2011). Dynamic ankle control in athletes with ankle instability during sports maneuvers. Am J Sports Med, 39(9), 2007–2015. http://dx.doi.org/10.1177/0363546511406868. McLean, S. G., Fellin, R. E., Suedekum, N., Calabrese, G., Passerallo, A., & Joy, S. (2007). Impact of fatigue on gender-based highrisk landing strategies. Med Sci Sports Exerc, 39(3), 502–514. http://dx.doi.org/10.1249/mss.0b013e3180d47f0. Powell, D. W., Hanson, N. J., Long, B., & Williams, D. S. 3rd., (2012). Frontal plane landing mechanics in high-arched compared with low-arched female athletes. Clin J Sport Med, 22(5), 430–435. http://dx.doi.org/10.1097/JSM.0b013e318257d5a1. Powell, D. W., Long, B., Milner, C. E., & Zhang, S. (2011). Frontal plane multi-segment foot kinematics in high- and low-arched females during dynamic loading tasks. Hum Mov Sci, 30(1), 105–114. http://dx.doi.org/10.1016/j.humov.2010.08.015. Powell, D. W., Long, B., Milner, C. E., & Zhang, S. (2012). Effects of vertical loading on arch characteristics and intersegmental foot motions. J Appl Biomech, 28(2), 165–173. Williams, D. S., 3rd, Davis, I. M., Scholz, J. P., Hamill, J., & Buchanan, T. S. (2004). High-arched runners exhibit increased leg stiffness compared to low-arched runners. Gait Posture, 19(3), 263–269. Williams, D. S., 3rd, Green, D. H., & Wurzinger, B. (2012). Changes in lower extremity movement and power absorption during forefoot striking and barefoot running. Int J Sports Phys Ther, 7(5), 525–532.
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Williams, D. S., & McClay, I. S. (2000). Measurements used to characterize the foot and the medial longitudinal arch: reliability and validity. Phys Ther, 80(9), 864–871. Williams, D. S., 3rd, McClay, I. S., & Hamill, J. (2001). Arch structure and injury patterns in runners. Clin Biomech (Bristol, Avon), 16(4), 341–347. Williams, D. S., McClay, I. S., Hamill, J., & Buchanan, T. S. (2001). Lower extremity kinematic and kinetic differences in runners with high and low arches. J Appl. Biomech., 17, 153–163. Zhang, S., Powell, D. W., Keefer, M., King, J., & Hamill, J. (2007). Foot and arch structure characteristics across age groups. Proceedings of the 8th Footwear Biomechanics Symposium, Taiwan. Zifchock, R. A., Davis, I., Hillstrom, H., & Song, J. (2006). The effect of gender, age, and lateral dominance on arch height and arch stiffness. Foot Ankle Int, 27(5), 367–372.
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Human Movement Science journal homepage: www.elsevier.com/locate/humov
Ankle work and dynamic joint stiffness in high- compared to low-arched athletes during a barefoot running task Douglas W. Powell a,⇑, D.S. Blaise Williams 3rd b, Brett Windsor a, Robert J. Butler c, Songning Zhang d a
Department of Physical Therapy, Campbell University, Buies Creek, NC, USA Department of Physical Therapy, Virginia Commonwealth University, Richmond, VA, USA c Doctor of Physical Therapy Division, Duke University, Durham, NC, USA d Department of Kinesiology, Recreation & Sport Studies, The University of Tennessee, Knoxville, TN, USA b
a r t i c l e
i n f o
Article history: Available online 17 February 2014 PsycINFO classification: 2540 Keywords: Running Barefoot Kinetics Injury Ankle Arch Foot
a b s t r a c t High- (HA) and low-arched (LA) athletes have an exaggerated risk of injury. Ankle joint stiffness is a potential underlying mechanism for the greater rate of injury within these two functionally different groups. An alternative candidate mechanism of injury in HA and LA athletes pertains to the efficacy of the foot as a rigid lever during propulsion. The purpose of this study was to quantify the differences in ankle dynamic joint stiffness, and ankle braking work and ankle propulsive work during stance phase of running. Methods: Ten HA and ten LA athletes performed five barefoot running trials while ground reaction forces and three-dimensional kinematics were recorded. Ankle dynamic joint stiffness was calculated as the slope of the ankle joint moment–ankle joint angle plot during load attenuation. Ankle braking and propulsive work values were calculated for the stance phase. Results: HA athletes had significantly greater ankle dynamic joint stiffness and significantly smaller ankle net and propulsive work than LA athletes. Conclusions: These data demonstrate that HA and LA athletes exhibit unique biomechanical patterns during running. These patterns may be related to lower extremity injury. Ó 2014 Elsevier B.V. All rights reserved.
⇑ Corresponding author. Address: Department of Physical Therapy, Campbell University, PO Box 1090, Buies Creek, NC, USA. Office: +1 (910) 893 1757. E-mail address: [email protected] (D.W. Powell). http://dx.doi.org/10.1016/j.humov.2014.01.007 0167-9457/Ó 2014 Elsevier B.V. All rights reserved.
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1. Introduction Mal-alignment and aberrant mechanics of the foot and ankle have been implicated as contributing factors to lower extremity injury (Kaufman, Brodine, Shaffer, Johnson, & Cullison, 1999; Williams, McClay, & Hamill, 2001). It has been demonstrated that individuals with high- or lowarched feet have a greater incidence of lower extremity injury than individuals with a normal arch (Kaufman et al., 1999). Further, it has been shown that high- and low-arched athletes exhibit divergent overuse injury patterns with high-arched athletes experiencing a greater number of bony injuries to the lateral aspect of the lower extremity while low-arched individuals experience a greater number of soft tissue injuries to the medial aspect of the lower extremity (Williams et al., 2001). These unique injury patterns have been attributed to the role of the foot in load attenuation and the altered transmission of force through the lower extremity kinetic chain (Kaufman et al., 1999; Powell, Hanson, Long, & Williams, 2012a; Powell, Long, Milner, & Zhang, 2011; Powell, Long, Milner, & Zhang, 2012b; Williams, Davis, Scholz, Hamill, & Buchanan, 2004; Williams et al., 2001; Williams et al., 2004). It has been demonstrated that high-arched feet are typically rigid and exhibit greater stiffness while low-arched feet are typically mobile and exhibit less stiffness compared to normal feet (Zifchock, Davis, Hillstrom, & Song, 2006). Previous research has also reported significantly greater knee joint stiffness in high- compared to low-arched athletes during a level running task (Williams et al., 2004). It has been suggested that exaggerated or insufficient stiffness throughout the lower extremity predispose an individual to injury (Butler, Crowell, & Davis, 2003; Williams et al., 2004; Williams, McClay, Hamill, & Buchanan, 2001). Though the roles of foot structure and joint stiffness in lower extremity injury have been established, no previous study has investigated differences in ankle joint stiffness, specifically during the period believed to be most responsible for overuse injury, load attenuation. Currently research hypotheses have identified aberrant patterns of lower extremity loading in response to load attenuation as a potential mechanism for overuse injury to the lower extremity. An alternative hypothesis pertains to the role and efficacy of the foot as a functional lever during the propulsive portion of the stance phase. Research has demonstrated that lower extremity joint work values are significantly greater during the propulsive compared to braking phases of walking (DeVita, Helseth, & Hortobagyi, 2007) and running (Heiderscheit, Chumanov, Michalski, Wille, & Ryan, 2011). Moreover, in running, the greatest differences in lower extremity joint work values, when comparing the braking and propulsive phases of stance, have been observed at the ankle joint (Heiderscheit et al., 2011). Specifically, the magnitude of positive ankle work in propulsion was two- to threefold greater than negative ankle work in braking when athletes ran at different step frequencies. It is possible that the low-arched, mobile foot is a less effective lever for the application of muscle force to the ground and requires greater muscle work to achieve similar mechanical output compared to the normal or high-arched foot. Further, it can be postulated that the interaction of the low-arched, mobile foot with increased muscle work could potentially underlie soft tissue overuse injury in low-arched athletes, particularly during the propulsive portion of the stance phase. However, no previous research study has quantified the differences in ankle joint work between high- and low-arched athletes. If significant differences in ankle dynamic joint stiffness and work values are present in the braking compared to propulsive phases of running stance, greater insight may be gained into the mechanisms underlying the unique injury patterns experienced by these two functionally different groups. Therefore, the purpose of this study is to investigate the differences in dynamic joint stiffness and joint work of the ankle during the total stance phase as well as the braking and propulsive portions of the stance phase during running. It was hypothesized that high- compared to low-arched athletes would exhibit significantly greater ankle dynamic joint stiffness values and significantly smaller ankle work values throughout the stance phase.
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2. Materials and methods 2.1. Participants Twenty individuals (10 high-arched; 10 low-arched) were recruited for participation in this study from a larger study of 55 healthy female recreational athletes. Table 1 presents subject anthropometric measurements. Participants qualified for inclusion if they were aged between 18 and 30 years, participated a minimum of 8 h per week in recreational athletics, and had an arch height index (AHI) greater than .377 or lower than .283. AHI values used to define the HA and LA groups represent the top and bottom 10% of the population defined as 1.5 standard deviations above and below the mean AHI of .330 (±.031) determined from 604 feet (Zhang, Powell, Keefer, King, & Hamill, 2007). Individuals with an AHI greater than .377 were placed in the high-arched (HA) group while participants with an AHI less than .283 were placed in the low-arched (LA) group. Arch type was determined using arch height index which was defined as the height of the dorsum at half the total foot length divided by the truncated foot length, or the distance between the posterior calcaneus and the first metatarsophalangeal joint (Powell et al., 2011; Williams & McClay, 2000). All participants were free of injury at the time of testing and signed a written informed consent form approved by the Institutional Review Board at the university prior to participating in this study. 2.2. Experimental protocol Each participant completed two laboratory testing sessions. The initial session consisted of collecting subject information, anthropometric measurements, and arch measurements including height, mass, total foot length, truncated foot length and dorsum height. During the second laboratory session, participants performed five barefoot running trials at self-selected velocities. Running velocities were determined using three practice trials prior to testing and were monitored and maintained (±5%) during testing. Ground reaction forces and three-dimensional (3D) kinematic data were collected. 2.3. Instrumentation A seven-camera motion capture system (240 Hz, Vicon Motion Systems Ltd., Oxford, UK) and force platform (1200 Hz, OR-6; AMTI, Watertown, Massachusetts) were used to collect 3D kinematic data and ground reaction forces from the right side of the lower extremity of each participant, respectively. Retro-reflective markers (14 mm) were placed over anatomical landmarks including the first and fifth metatarsal heads, medial and lateral malleoli, medial and lateral femoral condyles to define the joint center of foot, shank and thigh segments, respectively. The pelvis was defined using retro-reflective markers placed on the right and left anterior superior iliac spines, right and left posterior superior iliac spines, right and left iliac crests and the right and left greater trochanters. The pelvis was tracked using two marker clusters, each composed of two 14 mm retro-reflective markers placed on thermoplastic. The thigh and shank segments were tracked using a rigid cluster with four 14 mm retro-reflective markers placed on the lateral aspect of the segment. The foot was tracked using three 9.5 mm markers fixed to the skin using double-sided (wig) tape placed over the bony aspects of the posterior superior and inferior aspects of the calcaneus and the peroneal tubercle. The standing calibration was collected during quiet standing with the arms placed across the chest with the feet pointed forward in line with
Table 1 Anthropometric characteristics, and running velocities in high- (HA) and low-arched (LA) female athletes. Group
Height (m)
Mass (kg)
AHI
Running velocity (m/s)
HA LA
1.62 (.07) 1.63 (.07)
58.3 (5.4) 58.9 (10.9)
.386 (.010)a .259 (.043)
2.79 (.28) 2.73 (.29)
Presented as mean (SD). a Denotes significant difference between HA and LA athletes.
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the global coordinate system. Anatomical markers used to define the segments were removed prior to dynamic trials and only tracking markers remained on the subject during dynamic trials. The subject’s right foot contacted the force platform during each trial. Two pairs of photo cells and an electronic timer (63501 IR, Lafayette Instruments, Inc., IN, USA) were used to monitor running velocities. 2.4. Data analysis Three-dimensional kinematic data and ground reaction force data were filtered with a low-pass, fourth-order zero-lag Butterworth filter with cut-off frequencies of 10 and 50 Hz, respectively (Hunt & Smith, 2004; Powell et al., 2012a; Williams et al., 2004). Joint angles, internal joint moments were calculated using Visual 3D (C-Motion, Inc., Rockville, Maryland). The ankle joint angle was defined as the difference between the angle of the shank and the angle of the foot minus 90°, to account for the orientation of the foot. Internal joint moments and joint powers were normalized to body mass. Ankle joint angles, internal joint moments and ankle powers were only assessed from initial contact to toe-off (stance phase). Custom software (Matlab 2009, MathWorks, Natick, MA, USA) was used to calculate kinetic variables of interest including dynamic joint stiffness and ankle work. Dynamic joint stiffness, determined using a torsional spring model (Butler et al., 2003; Gabriel et al., 2008; Lamontagne, Malouin, & Richards, 2000; Lark, Buckley, Bennett, Jones, & Sargeant, 2003), was calculated as the slope of the ankle moment–angle plot during the braking phase of stance (Fig. 1). Ankle work was quantified as
Fig. 1. An ankle moment–angle plot from a representative athlete during a barefoot running trial. Significant gait events including initial contact (A), midstance (B) and toe-off (C) are depicted. The braking phase was defined as the period between initial contact and midstance while the propulsive phase was defined as the period between midstance and toe-off. Ankle dynamic joint stiffness was quantified as the slope of the ankle moment–angle plot during the braking portion of the stance phase of running, represented by a solid line. Ankle work was defined as the area beneath the ankle moment–angle curve for the entire stance phase (net) as well as the braking and propulsive portions of the stance phase.
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the ankle power integrated with respect to time. Ankle work was calculated for the total stance phase as well as for the braking and propulsive phases independently. The stance phase was divided into the braking and propulsive phases defined by antero-posterior ground reaction forces (AP GRFs). The braking phase was defined as the period prior to the AP GRF crossing baseline (zero), indicating a negative or backward GRF vector. The propulsive phase was defined as the period after the AP GRF crossed baseline (zero), indicating a positive or forward GRF vector. A subject mean was calculated as the average of the five trials from each movement condition for dynamic joint stiffness and ankle work variables. 2.5. Statistical analysis Student’s t-tests were used to compare anthropometric measurements and running velocities between the HA and LA athletes. Independent samples t-tests were used to determine the effect of foot type on ankle dynamic joint stiffness, net ankle work, ankle braking work, and ankle propulsive work during stance phase. Significance was set at p < .05. All statistical analyses were conducted using SPSS 21.0 (IBM, Chicago, IL, USA). 3. Results The HA and LA athletes had similar heights and masses (Table 1). The HA athletes had significantly greater arch height index values than the LA athletes (p < .001). Running velocities were not significantly different between the HA and LA athletes (p = .356; Table 1). Fig. 2 presents ankle joint angle
Fig. 2. Sagittal plane ankle joint angles from representative high- (black, solid) and low-arched athletes (blue, dashed) during the barefoot running protocol. In these representative subjects, the HA athlete had significantly greater plantarflexion angles throughout the stance phase while the LA athlete exhibited greater peak dorsiflexion and dorsiflexion excursion. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
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profiles from HA and LA athletes during the barefoot running protocol. Visually, the HA athletes had less plantarflexion at initial contact, displayed less peak dorsiflexion and moved through a smaller range of motion than LA athletes during the stance phase. Fig. 3 presents ankle moment–angle plots in representative high- and low-arched athletes. Visually, the high-arched athletes presented a steeper slope during the braking and propulsive portions of the stance phase than the low-arched athletes. Further, the range of motion over which the ankle moment was produced was substantially smaller in the high- compared to low-arched athletes. Ankle dynamic joint stiffness (Table 2) was calculated using a torsional spring model and was quantified as the slope of the ankle joint moment–ankle joint angle plot during the braking phase of stance. The statistical analysis revealed significantly greater ankle dynamic joint stiffness values in the HA compared to LA athletes (p = .042).
Fig. 3. Representative ankle moment–angle plots for HA (solid) and LA (- - -) athletes from a sample barefoot running trial. HA athletes had significantly greater ankle dynamic joint stiffness values than LA athletes evidenced in this example by the steeper slope of the ankle moment-ankle plot during the braking portion of stance. Further, HA athletes produced significantly less net ankle work and propulsive ankle work than LA athletes, visualized in this figure as a smaller area within the ankle moment– angle plot.
Table 2 Average net ankle work and work done by the ankle during the braking and propulsive phases of the stance phase of running in high- (HA) and low-arched (LA) female athletes. Group
Net work (J/kg)
HA LA
.44 (.09)a .66 (.11)
Braking work (J/kg) .52 (.13) .44 (.08)
Propulsive work (J/kg) .90 (.12)a 1.02 (.07)
Presented as mean (SD). a Denotes significant difference between HA and LA athletes.
Dynamic joint stiffness (Nm/kg/°) .274 (.098)a .199 (.046)
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Ankle joint work was calculated as the ankle joint power integrated with respect to time (Table 2). Statistical analysis revealed that HA athletes exhibited significantly smaller net (p = .023) and propulsive (p = .040) ankle work values compared to LA athletes. No significant differences in braking ankle joint work were observed between the HA and LA athletes (p = .517).
4. Discussion The objective of this study was to compare ankle dynamic joint stiffness and ankle work in highand low-arched athletes during a barefoot running task. This study presents novel findings pertaining to the relationship between foot structure and ankle joint mechanics. Dynamic joint stiffness quantifies the contribution of passive and active tissues to load attenuation during the braking portion of the stance phase (Gabriel et al., 2008; Lamontagne et al., 2000; Lin, Chen, & Lin, 2011). Describing the relationship between ankle joint moments and ankle displacement, dynamic joint stiffness of the ankle has been previously used to investigate the interaction of motor control and ankle joint mechanics in response to advanced age and injury mechanisms (Crenna & Frigo, 2011; Gabriel et al., 2008; Lin et al., 2011). Dynamic joint stiffness was used in the current study to quantify the role of the ankle mechanics in load attenuation. The barefoot running task was selected in the present study to examine the active role of the plantarflexors during both the braking and propulsive portions of the stance phase (Williams, Green, & Wurzinger, 2012) and to elucidate the functional differences in the mechanics of the foot and ankle in high- compared to low-arched athletes. The dynamic joint stiffness values presented in the current study are substantially greater than those previously reported in walking (Gabriel et al., 2008) or running studies using similar calculations of stiffness (Lin et al., 2011). However, these observed differences are likely due to the differences in the experimental protocol used in each study. For example, it is logical that previous studies investigating ankle mechanics in a walking task would report lower dynamic joint stiffness values as walking is associated with lower mechanical demand and smaller ankle joint moments compared to running (Gabriel et al., 2008). Further, dynamic joint stiffness values reported in the present study are also twofold greater than those previously reported in healthy adults (.150 ± .068 Nm/kg/°) during a running task (Lin et al., 2011). However, the exaggerated dynamic joint stiffness values presented currently may be explained by the barefoot condition used in this study compared to the shod running condition previously investigated. A common adaptation in response to barefoot running is the adoption of a mid- to forefoot strike pattern (Lieberman et al., 2010). By performing a barefoot running task, the modified strike pattern requires greater involvement of the ankle plantarflexor musculature during load attenuation, resulting in substantially greater ankle plantarflexion moments. When performing shod running with a heel strike, the ankle plantarflexors are less involved during the load attenuation portion of the stance phase, over which the dynamic joint stiffness values were calculated. In the present study, HA athletes exhibited significantly greater dynamic joint stiffness values than their LA counterparts. The dynamic joint stiffness calculation is a measure of the interaction of ankle joint kinematics and kinetics. The findings of this and previous studies demonstrate that HA athletes absorb load over a shorter period of time using a smaller range of motion in multiple planes of motion (Butler, Davis, & Hamill, 2006; Powell et al., 2011; Williams et al., 2004; Williams et al.,2001). Previous research has demonstrated that high- compared to LA produce significantly greater loading rates due to a significantly earlier peak vertical ground reaction force during a running task (Williams et al., 2004). Similarly, it has been shown that HA athletes move through smaller ranges of ankle motion in the sagittal (Williams et al., 2004) and frontal planes (Butler et al., 2006; Powell et al., 2011; Williams et al.,2001) during running. It could be postulated that the reduced ranges of motion exhibited by HA athletes during running are an extension of reduced flexibility within the foot-Achille’s complex (Zifchock et al., 2006). HA feet have been shown to exhibit greater arch stiffness in response to a vertical load than low-arched athletes (Zifchock et al., 2006). Furthermore, a study using a multisegment foot model demonstrated that HA athletes exhibit smaller eversion and eversion excursions within the foot than LA athletes in response to vertical load (Powell et al., 2012b). The inability of the foot to absorb load through sagittal and frontal plane motions results in greater magnitudes and rates of loading at the level of the ankle and potentially greater ankle dynamic joint stiffness.
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In addition to greater dynamic joint stiffness values during load attenuation, HA runners exhibited significantly smaller net ankle work and smaller ankle work during the propulsive portion of the stance phase. The ankle work values presented in this study are lower than those presented in previous running studies (Heiderscheit et al., 2011); however, participants in this study ran at a slower velocity than the 2.90 m/s in the study by Heiderscheit et al. (2011). Further, these data were collected during barefoot rather than shod running which may have contributed to a reduced running velocity. Therefore, the imposed mechanical demand in the current study would be lower than in the study by Heiderscheit et al. (2011) and could require a smaller mechanical output from the lower extremity to successfully complete the running task. In the present study, HA athletes produced significantly smaller net ankle work than LA athletes. The inequalities in net ankle work were dominated by differences in ankle work during the propulsive portion of the stance phase. Several candidate mechanisms may underlie the observed differences in ankle kinetics. One potential mechanism pertains to the efficacy of the foot as a rigid lever in highcompared to low-arched athletes. Previous research has identified a significant relationship between arch height index and arch stiffness or rigidity of the foot (Zifchock et al., 2006). Therefore, the rigid foot of the high-arched athlete may be a better functional lever during push off than the low-arched foot. A more efficient lever would act to more efficiently apply forces generated by the triceps surae to the ground for propulsion. Therefore, the non-rigid low-arched foot may be a less effective lever than the HA foot and may require greater force generation from the triceps surae muscles to create a similar mechanical output. An alternative but related mechanism potentially explaining the observed differences in net and propulsive ankle work values pertains to the location of the center of pressure beneath the foot during the stance phase of running. Due to the barefoot running condition, all participants adopted a mid- or forefoot strike pattern. A post hoc analysis of the lever arm length of the foot was conducted to determine the validity of this potential mechanism. The lever arm of the foot was defined as the horizontal distance in the sagittal plane between the center of pressure and the center of ankle joint rotation. A Student’s t-test was used to compare mean lever arms between the high- and low-arched groups. The post hoc analysis revealed that high-arched athletes had significantly longer foot lever arms compared to the low-arched athletes (HA: .093 ± .010 m; LA: .084 ± .006 m). It could be postulated that the flexible LA foot collapsed shortly after initial contact moving the center of pressure closer to the ankle joint center, functionally shortening the lever arm of the foot and requiring a greater muscular work to produce a similar mechanical output. A smaller lever arm due to exaggerated arch flexibility may require LA individuals to produce greater work over a longer duration than HA athletes to produce a given mechanical outcome. Conversely, the rigid HA foot experiences less deformation following initial contact (Butler et al., 2003; Powell et al., 2011; Powell et al., 2012b; Williams et al., 2004; Williams et al.,2001) and the center of pressure remains further from the center of ankle joint rotation. The greater distance of the center of pressure from the center of joint rotation in HA athletes may more effectively transfer the forces of the Achilles tendon and triceps surae to the ground. The enhanced efficacy of the rigid HA foot in transferring forces to the ground may result in smaller durations of propulsive ankle power and therefore lower ankle joint work values. These findings support the hypothesis that the rigid high-arched foot is a more effective lever compared to the flexible low-arched foot. The findings of this study present novel data pertaining to differences in lower extremity biomechanics between high- and low-arched athletes in running. Specifically, previous research investigating the role of foot type in lower extremity running mechanics has focused on load attenuation. To the knowledge of the authors, no previous research study examined the role of the foot in propulsion in these two subject groups. However, the findings of this study suggest that substantial differences in foot and ankle biomechanics exists in high- compared to low-arched athletes. It is possible that these biomechanical differences may be a contributing factor to the unique injury patterns experienced by these two groups. Though the findings of this study present are novel and may relate to candidate injury mechanisms in HA and LA athletes, the authors acknowledge the limitations of this study. The relatively small sample size of ten athletes per group reduces the statistical power and limits the generalizations that can be made from these data. However, statistical differences were found between the HA and LA athletes suggesting that sufficient statistical power was present. Another limitation of this study is that only
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female athletes were investigated. It has been demonstrated that female athletes adopt an anklebased strategy during athletic tasks (Kernozek, Torry, H, Cowley, & Tanner, 2005; McLean et al., 2007), which may exaggerate the differences between high- and low-arched groups observed in this study compared to the general population. 5. Conclusions The findings of this study demonstrate significant differences in ankle biomechanics adopted by high- and low-arched athletes in load attenuation and propulsion during barefoot running. Further, these data demonstrate significant differences in lever arm lengths of the foot–ankle complex in highcompared to low-arched athletes. These unique mechanisms may underlie the distinct overuse injury patterns exhibited by each of these functionally different groups. Conflict of interest None. Financial disclosure None. References Butler, R. J., Crowell, H. P., 3rd, & Davis, I. M. (2003). Lower extremity stiffness: Implications for performance and injury. Clin Biomech (Bristol, Avon), 18(6), 511–517. Butler, R. J., Davis, I. S., & Hamill, J. (2006). Interaction of arch type and footwear on running mechanics. Am J Sports Med, 34(12), 1998–2005. http://dx.doi.org/10.1177/0363546506290401. Crenna, P., & Frigo, C. (2011). Dynamics of the ankle joint analyzed through moment-angle loops during human walking: gender and age effects. Hum Mov Sci, 30(6), 1185–1198. http://dx.doi.org/10.1016/j.humov.2011.02.009. DeVita, P., Helseth, J., & Hortobagyi, T. (2007). Muscles do more positive than negative work in human locomotion. J Exp Biol, 210(Pt 19), 3361–3373. http://dx.doi.org/10.1242/jeb.003970. Gabriel, R. C., Abrantes, J., Granata, K., Bulas-Cruz, J., Melo-Pinto, P., & Filipe, V. (2008). Dynamic joint stiffness of the ankle during walking: Gender-related differences. Phys Ther Sport, 9(1), 16–24. http://dx.doi.org/10.1016/j.ptsp.2007.08.002. Heiderscheit, B. C., Chumanov, E. S., Michalski, M. P., Wille, C. M., & Ryan, M. B. (2011). Effects of step rate manipulation on joint mechanics during running. Med Sci Sports Exerc, 43(2), 296–302. http://dx.doi.org/10.1249/MSS.0b013e3181ebedf4. Hunt, A. E., & Smith, R. M. (2004). Mechanics and control of the flat versus normal foot during the stance phase of walking. Clin Biomech (Bristol, Avon), 19(4), 391–397. Kaufman, K. R., Brodine, S. K., Shaffer, R. A., Johnson, C. W., & Cullison, T. R. (1999). The effect of foot structure and range of motion on musculoskeletal overuse injuries. Am J Sports Med, 27(5), 585–593. Kernozek, T. W., Torry, M. R., Van Hoof, H., Cowley, H., & Tanner, S. (2005). Gender differences in frontal and sagittal plane biomechanics during drop landings. Med Sci Sports Exerc, 37(6), 1003–1012. discussion 1013. Lamontagne, A., Malouin, F., & Richards, C. L. (2000). Contribution of passive stiffness to ankle plantarflexor moment during gait after stroke. Arch Phys Med Rehabil, 81(3), 351–358. Lark, S. D., Buckley, J. G., Bennett, S., Jones, D., & Sargeant, A. J. (2003). Joint torques and dynamic joint stiffness in elderly and young men during stepping down. Clin Biomech (Bristol, Avon), 18(9), 848–855. Lieberman, D. E., Venkadesan, M., Werbel, W. A., Daoud, A. I., D’Andrea, S., Davis, I. S., et al (2010). Foot strike patterns and collision forces in habitually barefoot versus shod runners. Nature, 463(7280), 531–535. http://dx.doi.org/10.1038/ nature08723. Lin, C. F., Chen, C. Y., & Lin, C. W. (2011). Dynamic ankle control in athletes with ankle instability during sports maneuvers. Am J Sports Med, 39(9), 2007–2015. http://dx.doi.org/10.1177/0363546511406868. McLean, S. G., Fellin, R. E., Suedekum, N., Calabrese, G., Passerallo, A., & Joy, S. (2007). Impact of fatigue on gender-based highrisk landing strategies. Med Sci Sports Exerc, 39(3), 502–514. http://dx.doi.org/10.1249/mss.0b013e3180d47f0. Powell, D. W., Hanson, N. J., Long, B., & Williams, D. S. 3rd., (2012). Frontal plane landing mechanics in high-arched compared with low-arched female athletes. Clin J Sport Med, 22(5), 430–435. http://dx.doi.org/10.1097/JSM.0b013e318257d5a1. Powell, D. W., Long, B., Milner, C. E., & Zhang, S. (2011). Frontal plane multi-segment foot kinematics in high- and low-arched females during dynamic loading tasks. Hum Mov Sci, 30(1), 105–114. http://dx.doi.org/10.1016/j.humov.2010.08.015. Powell, D. W., Long, B., Milner, C. E., & Zhang, S. (2012). Effects of vertical loading on arch characteristics and intersegmental foot motions. J Appl Biomech, 28(2), 165–173. Williams, D. S., 3rd, Davis, I. M., Scholz, J. P., Hamill, J., & Buchanan, T. S. (2004). High-arched runners exhibit increased leg stiffness compared to low-arched runners. Gait Posture, 19(3), 263–269. Williams, D. S., 3rd, Green, D. H., & Wurzinger, B. (2012). Changes in lower extremity movement and power absorption during forefoot striking and barefoot running. Int J Sports Phys Ther, 7(5), 525–532.
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