Footwear Alters Lower Extremity Coordination Variability

Abstract

Footwear has been shown to have a significant effect on numerous kinematic and kinetic variables during walking and running. While footwear mass is an indisputably important influence on gait patterns, we suspected that the amount of outsole material on most footwear would likely diminish or delay the integration of tactile feedback in motor control strategies during gait. Thus, we designed this study to investigate the influence of footwear and augmented tactile feedback on lower extremity coordination patterns during walking. A secondary purpose of the study was to examine gender differences in response to altered footwear conditions. Forty-eight participants (24 male and 24 females) walked during four standardized footwear conditions (barefoot, shod, barefoot with augmented tactile feedback, and shod with augmented tactile feedback), and we collected three-dimensional kinematic data and calculated continuous relative phase values for two adjacent lower extremity joints to determine interjoint coordination patterns. We used deviation phase and the mean of the continuous relative phase to compare motor coordination patterns across conditions. We found significant footwear and gender effects for spatiotemporal variables but only significant footwear effects for motor coordination patterns. Females displayed a significantly higher cadence and shorter height-normalized stride length as compared to males. Participants displayed significantly greater thigh-shank coordination variability in the shod, as compared to the unshod, conditions. Thus, footwear results in a diminished or delayed tactile feedback that alters neuromuscular control strategies during walking.

Keywords

footwear walking coordination variability gait coordination textured insole

Introduction

The influence of footwear on gait mechanics has long been an area of research interest, and it has received considerable mainstream attention in recent years, due to discussions regarding differences in barefoot versus shod gait conditions, the influence of footwear on gait, and the potential implications for developing cumulative trauma from running. During both walking and running, barefoot gait has been associated with a reduced stride length and higher cadence as compared to shod gait (Divert et al., 2008; Larsen, Weidich, & Leboeuf-Yde, 2002; Lieberman et al., 2010; Morio, Lake, Gueguen, Rao, & Baly, 2009; Wegener, Hunt, Vanwanseele, Burns, & Smith, 2011). Similarly, significant differences in joint kinematics have been reported, such as increased plantarflexion, decreased hip flexion, and increased knee flexion at foot contact, during barefoot gait, as compared to shod gait (Kristen, Kastner, Holzreiter, Wagner, & Engel, 1998; Lieberman et al., 2010; Wegener et al., 2011).

A prevailing hypothesis regarding footwear effects on gait has been a mechanical effect, due to the increased mass of the distal segment of the shoe when the walker is shod. For instance, Divert et al. (2008) noted a significant mass effect on mechanical and physiological gait parameters when running. Likewise, Majumdar, Banerjee, Pal, Kumar, and Selvamurthy (2006) have noted a significant rise in stride length, reduction in cadence, and rise in single support time when comparing walking in a military boot to walking barefoot. A secondary and often overlooked component of the discussion regarding footwear effects on gait mechanics is the role of tactile feedback, specifically, the loss of cutaneous feedback due to the interruption of the foot-to-floor interface. Previous research has found a significant decrease in the incidence of extra limb movements as well as center-of-pressure trajectory in response to postural perturbations when older and younger adults wore footwear that provided augmented plantar facilitation (Maki, Perry, Norrie, & McIlroy, 1999). More recent research has indicated the ability of augmented tactile feedback to significantly alter spatiotemporal gait parameters and gait symmetry measures (e.g., stance phase, single support, and swing phase) in young, healthy adults, while others have reported a reduced stride length and walking velocity when older adults wore a textured as opposed to a smooth insole (Aruin & Kanekar, 2013; Hatton, Dixon, Rome, Newton, & Martin, 2012). Likewise, the research by Nurse, Hulliger, Wakeling, Nigg, and Stefanyshyn (2005) has indicated the ability of augmented tactile feedback to alter gait mechanics and muscle activity during walking.

The influence of augmented versus unaugmented tactile feedback on gait mechanics is remarkably similar to differences found between barefoot and shod gait. For instance, past research has shown significant reductions in walking velocity and stride length, with an increase in cadence, during barefoot walking compared to shod walking (Wegener et al., 2011). When examining the potential role of afferent feedback in modulating efferent motor actions, more recent research has reported that the amplitude and time to peak amplitude for the tibialis anterior, peroneus longus, and medial gastrocnemius were significantly different between barefoot and shod gait (Scott, Murley, & Wickham, 2012). Specifically, significantly greater peak tibialis anterior and medial gastrocnemius as well as a significantly shorter time to peak amplitude for the tibialis anterior, during shod gait as compared to barefoot gait. Similar results were reported by Nurse et al. (2005) when examining differences between a textured versus a smooth insert, with a significant reduction in soleus and tibialis anterior activity when participants walked with a textured, as opposed to a smooth, insole.

While the role of tactile feedback has received attention in the literature across age and foot pathology groups, results have been mixed as to the long-term effects of tactile feedback on movement dynamics (Hatton, Dixon, Martin, & Rome, 2011; Hatton et al., 2012; Jenkins et al., 2009; Kelleher, Spence, Solomonidis, & Apatsidis, 2010; Nurse et al., 2005; Watanabe & Okubo, 1981; Wilson, Rome, Hodgson, & Ball, 2008). This may be partially explained by group differences in attentional capacity and interference on motor cortex regions, either caused by augmented plantar facilitation or a reduction in tactile feedback on neuromotor control strategies during gait (Woollacott & Shumway-Cook, 2002). Because of a reliance on discrete measures for analysis, many of the previous studies may not have been fully able to capture the alteration in neuromuscular control strategies resulting from footwear or augmented plantar facilitation. Previous research has argued that the use of the continuous relative phase (CRP) would be more useful in determining alterations in neuromuscular control due to the use of an angle-velocity phase portrait containing spatial and temporal information from two adjacent segments (Chiu, Osternig, & Chou, 2013). Related to the role of tactile feedback in modulating coordination patterns, it has also been argued that CRP would be useful in quantifying joint coordination during walking due to the role of afferent fibers in sensing joint position and velocity (Burgess-Limerick, Abernethy, & Neal, 1993; Chiu et al., 2013).

Therefore, it appears as though footwear, footwear components, and tactile feedback are capable of producing significant changes in gait mechanics and lower extremity muscle activity. Despite this influence, no examination of the effect of footwear on segmental coordination patterns during walking has been reported. Consequently, the purpose of this study was to examine the effect of footwear and augmented tactile feedback on lower extremity gait coordination. A secondary purpose was to examine possible gender differences in gait variability.

Method

Participants

We recruited a total of 48 participants from the Auburn, Alabama, United States community—24 young, healthy males (M age = 23.0, SD = 2.5 years; M height = 1.81, SD = 0.07 m; M mass = 83.7, SD = 11.7 kg) and 24 females (M age = 23.4, SD = 3.4 years; M height = 1.64, SD = 0.06 m; M mass = 64.7, SD = 18.1 kg). A power analysis was conducted (effect size = 0.25, alpha = 0.05, and power = 0.80) with G*Power v3.0.10 for Windows, determining that 40 participants would be required to demonstrate significance (Faul, Erdfelder, Lang, & Buchner, 2007). Exclusion criteria for participation included: (a) any current or recent injury ( < 1 year) to the lower extremity, pelvis, low back, or trunk; (b) any previous injury/illness that could jeopardize the successful performance of the requisite tasks; (c) any allergies to adhesives or adhesive type products; (d) any known balance deficits or inner ear disturbances; (e) under 19 years of age; and (f) over 35 years of age. All participants indicated their willingness to participate by signing an Institutional Review Board approved Informed Consent document before data collection commenced.

Instrumentation and Procedure

Participants were sized for footwear and were provided a new pair of shoes for use throughout the duration of the protocol. All participants wore an identical model of the minimalist style shoe, an Adidas® Adipure Adapt (Adidas, Portland, OR, USA). Participants were asked to walk along a 15 -m walkway during four, randomized footwear conditions (see Figure 1): (a) barefoot (BF), (b) shod with Adidas® Adipure (SH), (c) textured insole only (IN), and (d) textured insole within the Adidas® Adipure (INSH). The textured insert was a 3-mm-thick ethylene-vinyl acetate (EVA) insert cut to the foot size from a commercially available outsole material (Evalite Pyramids EVA, 3 mm thickness; Algeos Ltd., Dubai, UAE). The insole material consisted of small pyramidal peaks (1 mm) with center-to-center distances of approximately 2.5 mm (see Figure 1). The insert was worn with texture against the plantar surface of the foot. During the combined insole and footwear condition, the insert was inserted directly into the shoe, negating the need for any additional material. All insoles were previously molded by the research team to a matching shoe size. During data collection, participants were instructed to walk at a normal, self-selected pace. Three trials per footwear condition were completed during each data collection session.

We utilized a 10 camera Vicon® MX motion analysis system (Vicon®, Los Angeles, CA, USA) operating at 200 Hz to collect three-dimensional kinematics during each session. Retroreflective markers were placed at key anatomical landmarks, based on a modified Plug-in Gait marker set (Vicon®, Los Angeles, CA, USA) and data were collected through The MotionMonitor (Innovative Sports Training, Chicago, IL, USA). Kinematic data were filtered using a dual-pass Butterworth filter with a cutoff frequency of 9 Hz.

Data Analysis

Due to the significant influence of footwear on sagittal plane joint kinematics, only the sagittal plane segmental coordination patterns (thigh-shank and shank-foot) were examined (Divert et al., 2008; Lieberman et al., 2010; Morio et al., 2009; Wegener et al., 2011). A custom-made MATLAB program (The Mathworks Inc., Natick, MA) was used to calculate the CRP values of the aforementioned sagittal plane segment coordination patterns. Similar to previous research, kinematic data were interpolated to 100% of the gait cycle, with sagittal plane angular positions (θ) and velocities (ω) normalized to the relative minimum and maximum, resulting in values ranging from 1 to −1 along both dimensions of the phase plane (Chiu et al., 2013; Hamill, van Emmerik, Heiderscheit, & Li, 1999; Figure 2). Phase angles were then calculated as Φ = tan⁻¹ (ω/θ) throughout the entire gait cycle and unwrapped to correct for discontinuities during angle computation (Chiu et al., 2013; Hamill et al., 1999). The CRP was then determined by subtracting the phase plot angle of the distal joint from the proximal joint (Chiu et al., 2013; Hamill et al., 1999).

Segmental coordination values across several gait cycles were examined between conditions utilizing the mean of the CRP portrait (CRP_mean). The variability of segmental coordination was examined through the deviation phase (DP), which is the mean value of all standard deviations for each time point over several gait cycles. A paired samples t-test revealed no significant difference between limbs (p ≥ .29) resulting in average values being utilized for each analysis. We used a two-way mixed-model analysis of variance (ANOVA) with repeated measures to examine the effect of footwear, as well as possible gender differences, on height normalized stride length, cadence, walking velocity, CRP_mean values, and DP values. The analyses for CRP_mean and DP values were completed with height normalized stride lengths as covariates. Follow-up pairwise analyses were conducted using a Least Squares Difference test for footwear effects with the alpha level set a priori at p < .05. All statistical analyses were performed with SPSS (IBM Corp., Armonk, NY).

Results

Data were tested for normality and homogeneity. Results were nonsignificant indicating data were normally distributed and contained equal variances.

Spatiotemporal Variables

Descriptive statistics for spatiotemporal variables are presented in Table 1. Paired samples t-test revealed no significant difference in velocity, cadence, or height-normalized stride length between footwear conditions during the two data collection sessions; therefore, data were combined from the two data collection sessions. Results indicate significant gender differences for cadence, F(1, 46) = 15.290, p < .001, η²= 0.953, and height-normalized stride length, F(1, 46) = 6.026, p = .018, η²= 0.778, while no significant difference was noted for velocity. Descriptive statistics revealed that females displayed a significantly higher cadence and significantly longer stride length, even after normalizing to total standing height. Small, but significant footwear effects were noted for cadence, F(3, 141) = 7.155, p < .001, η²= 0.845; stride length, F(3, 141) = 55.192, p < .001, η²= 0.978; and velocity, F(3, 141) = 10.570, p < .001, η²= 0.901 as well. Follow-up analyses revealed that participants tended to display a significantly higher cadence (p ≤ .024) during BF when compared to all other footwear conditions (IN, SH, and INSH); however, no other significant differences were noted between other footwear conditions.

Table 1.

Means (Standard Deviations) of Spatiotemporal Variables for Each Condition and Gender.

	Velocity (m·s⁻¹)	Cadence (steps·min⁻¹)	Stride length (m·m⁻¹)
SH	1.3 (0.13)^a,b	112.3 (7.9)^c	0.813 (0.05)^d,e
BF	1.27 (0.13)^a	113.9 (7.4)^c	0.782 (0.049)^d,e
IN	1.26 (0.12)^b	112.9 (7.8)	0.784 (0.044)^e
INSH	1.3 (0.13)^a,b	112.2 (8.2)^c	0.814 (0.052)^d,e
Male	1.28 (0.13)	109 (7.6)^f	0.78 (0.048)^g
Female	1.3 (0.12)	116.7 (3.3)^f	0.81 (0.049)^g

Note. SH: shod; BF: barefoot; IN: insole-only; INSH: insole, shod.

Walking velocity was significantly lower during BF as compared to INSH or SH (p ≤ .001).

Walking velocity was significantly lower during IN as compared to INSH or SH (p < .001).

Stride length was significantly lower during BF as compared to all other conditions (p ≤ .024).

Stride length was significantly lower during BF as compared to INSH or SH (p < .001).

Stride length was significantly lower during IN as compared to INSH or SH (p ≤ .001).

Females displayed a significantly greater cadence (p < .001) than males.

Females displayed a significantly greater stride length (p = .018) than males.

For height-normalized stride length, participants displayed significantly shorter strides during the BF and IN condition as compared to the SH (p < .001) or INSH (p < .001) conditions, but no significant difference was present between BF or IN conditions. Furthermore, no significant differences were found between SH or INSH conditions. As with height-normalized stride length, participants displayed significantly lower walking velocity during the BF and IN conditions as compared to SH (p < .001) or INSH (p = .001) conditions, yet no difference existed between the BF and IN conditions or between the SH and INSH conditions.

Coordination Patterns

Ensemble CRP curves for the thigh-shank and shank-foot are presented in Figure 2, and the CRP mean values for the lower extremity are presented in Figure 3. While no significant differences were noted in the intersegmental coordination pattern of the shank-foot, significant differences, F(3, 139.151) =6.039, p < .001, η²= 0.812, in coordination were noted between the thigh-shank. Specifically, participants exhibited a significantly more in-phase relationship during the BF condition as compared to the IN (p < .001) or INSH (p = .005) conditions. Participants also displayed a significantly more in-phase relationship in the SH as compared to the IN condition (p = .028).

Finally, no significant footwear or gender differences were noted in the DP (Figure 4) for the shank-foot; however, a significant footwear effect, F(3, 139.151) = 10.090, p < .001, η²= 0.899, was found for the thigh-shank DP (Figure 4). Follow-up analyses revealed that participants displayed a significantly lower thigh-shank DP during the IN condition as compared to BF, INSH, or SH conditions (p = .04, p < .001, and p < .001, respectively). Furthermore, participants displayed a significantly lower thigh-shank DP during the BF condition when compared to INSH or SH conditions (p = .013 and p = .011, respectively).

Discussion

This study indicates that while footwear causes significant alterations in spatiotemporal variables during walking, it also results in significant change in lower extremity coordination variability. Considerable research effort has been spent describing the influence of footwear on discrete kinematic variables during gait (Divert et al., 2008; Larsen et al., 2002; Lieberman et al., 2010; Morio et al., 2009; Wegener et al., 2011). Likewise, numerous authors have described the influence of augmented tactile feedback on spatiotemporal gait variables across numerous different populations (Aruin & Kanekar, 2013; Hatton et al., 2012). Unique to this study is the focus on coordination patterns throughout the gait cycle with regard to both items. Similar to previous research, a significant footwear effect on spatiotemporal variables was noted in this study (Wegener et al., 2011). Specifically, we observed a significantly increased cadence, coupled with reductions in stride length and walking velocity. Significant reductions in walking velocity and stride length were also found during augmented plantar facilitation trials, but these differences were only present during the insole-only conditions. However, unlike previous research, the addition of augmented plantar facilitation did not appear to significantly alter spatiotemporal variables during shod conditions (SH vs. INSH); this study did utilize healthy young adults (Aruin & Kanekar, 2013; Hatton et al., 2012).

Despite significant footwear effects on gait variability, this study found no significant gender differences for CRP mean or DP values. Specifically, participants displayed a significantly greater DP during SH and INSH conditions as compared to BF or IN conditions (Figure 4). Furthermore, small, but significant differences in the CRP mean curves were also noted between footwear conditions, with participants displaying a more in-phase relationship during the BF as compared to the IN or INSH conditions (Figure 3). Participants also displayed a more in-phase coordination pattern in the SH as compared to INSH condition (Figure 3). Given the lack of a significant difference in this study for DP between SH and INSH conditions even though there was a significant difference between BF and IN as compared to SH and INSH conditions, it appears that shod walking results in increased instability and places additional challenges on the neuromuscular system (Harbourne & Stergiou, 2009).

The use of the textured insole by itself appeared to cause a significant reduction in thigh-shank variability as compared to all other conditions; however, when the textured insole was included in the shoe, no significant difference was noted between shod conditions with and without the insole. Participants also displayed significantly lower thigh-shank variability when barefoot as compared to either of the shod conditions (SH and INSH). While these findings are unique in that it indicates significant alterations to lower extremity gait coordination patterns, results also indicate that the primary source of neuromuscular adaptations between shod and barefoot gait is through the more proximal joint rather than the distal lower extremity joint, despite a considerable footwear influence on lower extremity kinematics at foot strike (Kristen et al., 1998; Lieberman et al., 2010; Wegener et al., 2011).

Variability in joint coordination has been postulated as a representation of adaptability of the neuromuscular system (Chiu & Chou, 2012). An increase in variability may indicate a lower synergistic state among the various movement control centers (Harbourne & Stergiou, 2009). Previous research has indicated increased lower extremity variability during slower than normal walking, which was attributed to a greater challenge to the neuromuscular system due to a temporal increase in the single support phase of gait (Chiu & Chou, 2012). In this study, participants displayed a significantly lower walking velocity during the BF or IN conditions as compared to either shod condition (SH and INSH), yet displayed greater variability during the latter conditions. The difference in this study and that of Chiu et al. (2011) may be attributed to the considerable difference in the range of velocities between the present and former project. Specifically, though significant differences were noted in walking velocity, these differences are small and may not be of clinical significance. Rather, a considerable footwear effect was noted for stride length, accounting for an approximately 3% difference in height-normalized stride length and may be the altered coordination variability.

The alterations in lower extremity coordination may result from the increased mass of the foot during shod walking. For instance, previous research has indicated significant interlimb cross-correlation measures and RMS differences during walking with a unilateral load on the lower extremity (Haddad, van Emmerik, Whittlesey, & Hamill, 2006); however, given the lack of significant gender differences for CRP mean or DP measures, it would appear that stride length effects on lower extremity sagittal plane gait coordination may not be meaningful within this particular population. Likewise, participants displayed a significantly lower thigh-shank DP during IN walking as compared to BF walking. Numerous studies have indicated a significant improvement in balance when provided with augmented plantar feedback, while others have shown significant modifications to gait patterns when using a textured insole versus smooth or no insole (Aruin & Kanekar, 2013; Hatton et al., 2011; Maki et al., 1999; Nurse et al., 2005; Perry, Radtke, McIllroy, Fernie, & Maki, 2008). Given this evidence, augmented tactile feedback appears to enhance the proprioceptive feedback and neuromuscular control in a variety of populations. Therefore, the inherent components of the footwear (e.g., outsole or midsole cushioning) resulted in a diminished or delayed tactile feedback that challenged other sensory systems, altering neuromuscular control strategies during gait.

Although this study did observe significant findings, there are some limitations to these findings as well. First, we used only a single, minimalist style footwear in this study. Similarly, we used only a single type of textured insole. There were also age limitations to the study in that, most notably, participant recruitment was limited to individuals aged between 19 and 35 years.

Conclusion

This study suggests that footwear significantly alters neuromuscular control strategies in young, healthy adults. Furthermore, individuals appear to adopt a knee dominant strategy, rather than an ankle dominant intersegmental coordination strategy, to footwear. The use of a textured insole appears to have no effect on lower extremity coordination when placed within a shoe, though a textured insole treatment significantly reduced lower extremity variability. This study also indicated that females displayed a significantly higher cadence but a shorter height-normalized stride length, as compared to males. Additional research is needed to explore footwear and tactile feedback on coordination patterns in populations of athletic (e.g., running) and clinical interests (e.g., elderly adults, peripheral neuropathy).

Footnotes

Article Notes

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