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This article was downloaded by: [Universitat Salzburg], [Thomas Stöggl] On: 17 May 2012, At: 06:59 Publisher: Taylor & Francis Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Footwear Science Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/tfws20 Magnitude and variation in muscle activity and kinematics during walking before and after a 10-week adaptation period using unstable (MBT) shoes Thomas Stöggl a b c & Erich Müller a b a Department of Sport Science and Kinesiology, University of Salzburg, Salzburg, Austria b Christian Doppler Laboratory Biomechanics in Skiing, Salzburg, Austria c Swedish Winter Sports Research Centre, Department of Health Sciences, Mid Sweden University, Östersund, Sweden Available online: 17 May 2012 To cite this article: Thomas Stöggl & Erich Müller (2012): Magnitude and variation in muscle activity and kinematics during walking before and after a 10-week adaptation period using unstable (MBT) shoes, Footwear Science, 4:2, 131-143 To link to this article: http://dx.doi.org/10.1080/19424280.2012.683882 PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: http://www.tandfonline.com/page/terms-and-conditions This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

Footwear Science Vol. 4, No. 2, June 2012, 131 143 Magnitude and variation in muscle activity and kinematics during walking before and after a 10-week adaptation period using unstable (MBT) shoes Thomas Sto ggl abc * and Erich Mu ller ab a Department of Sport Science and Kinesiology, University of Salzburg, Salzburg, Austria; b Christian Doppler Laboratory Biomechanics in Skiing, Salzburg, Austria; c Swedish Winter Sports Research Centre, Department of Health Sciences, Mid Sweden University, O stersund, Sweden (Received 9 March 2012; final version received 5 April 2012) Objectives: The purpose of this study was to compare the magnitude and variability of electromyographic (EMG) and kinematic variables during treadmill walking using unstable (Masai Barefoot Technology, MBT) shoes and conventional shoes, before and after a 10-week training period. Methods: Twelve Sport Science students were analysed while walking on a treadmill with both conventional and unstable shoes, before and after a 10-week training intervention consisting of more than 4 h of use of unstable shoes during daily activity. Cycle characteristics, plantar pressure distribution, whole-body three-dimensional (3D) kinematics and EMG signals of selected leg muscles during the entire gait cycle and its subphases were recorded. The coefficient of variation of 20 consecutive cycles in each variable analysed was taken as the measure of variability. Results: A trend towards higher variability but equal magnitude was observed with MBT shoes compared with conventional shoes at the pre-intervention test (pre-test) regarding kinematic and EMG variables. The training period led to interaction effects (p < 0.05 to 0.01) demonstrating a global attenuation in the variability of kinematic and EMG variables in both shoe conditions, with greater reduction in the MBT situation, or an increase in variability with conventional shoes to higher post-test variability compared with MBT. Both situations revealed equal cycle times (1.05 s) but a shortened duration of loading response (136 vs. 146 ms) and terminal stance (211 vs. 223 ms) and an increased duration of midstance (293 vs. 282 ms) and swing time (408 vs. 386 ms) when comparing MBT with conventional shoes (all p < 0.05 to 0.001). Training led to a global reduction in cycle time (p < 0.05) and ground contact time (p < 0.01) in both shoe conditions. Conclusions: The results support the idea that the unstable shoe serves as a motor constraint applicable during everyday activity, inducing changes in the gait pattern with both MBT and conventional shoes. In selected EMG and kinematic variables, an interaction effect towards a greater decrease in movement variability in MBT compared with conventional shoes or an increase in variability with conventional shoes towards a higher post-test variability compared with MBT was observed. Keywords: 3D Kinematics; electromyography; loading response; midstance; terminal stance, training adaptation; whole-body kinematics Introduction Different perspectives in movement science have emphasized the role of variability encompassing nonlinear system dynamics and chaos theory, stochastic resonance, research on natural and artificial neural networks, and the differential learning approach (Scho llhorn et al. 2009) as a practical application. Variability is thought to be central to both development and learning, enabling self-organization to regulate and adapt to perturbations, to facilitate changes in coordination patterns, or to explore a certain movement space to find the appropriate individual movement pattern (e.g. Handford et al. 1997, van Geert and van Dijk 2002, Bartlett et al. 2007, Wilson et al. 2007, Mu ller and Sternad 2009). To help structure the possible movement or system configurations and increase or limit the amount of variability, the use of constraints is common practice. Constraints are boundaries or features that compel a number of components into change to find the optimal states of organization (Davids et al. 2003). For instance, in experiments in the context of stochastic resonance, Priplata et al. (2002, 2003, 2006) increased noise input of the soles of the foot through vibrating platforms or gel-based insoles and improved both young and elderly subjects performance in balance control. The use of *Corresponding author. Email: thomas.stoeggl@sbg.ac.at ISSN 1942 4280 print/issn 1942 4299 online ß 2012 Taylor & Francis http://dx.doi.org/10.1080/19424280.2012.683882 http://www.tandfonline.com

132 T. Sto ggl and E. Mu ller constraints may help the system to develop a better basis for more appropriate answers to outer disturbances. An exemplary constraint in terms of standing, walking or running might be the Masai Barefoot Technology (MBT) shoe. The MBT shoe is claimed by the makers to provide an unstable base attempting to simulate an unstable surface by application of a rounded sole in the anterior posterior direction and a cushioning heel sensor in the mediolateral direction of the shoe. In this context, increased instability and variability with unstable shoes might be associated with increased muscle activity and higher variability during gait or standing. Nigg et al. (2006a) reported greater postural sway and electromyographic (EMG) activity in the tibialis anterior muscle during quiet standing and trends towards higher muscle activity during walking when using MBT shoes compared with conventional shoes. Romkes et al. (2006) reported greater leg muscle activity in MBT shoes compared with regular shoes during walking, especially in the gastrocnemius during stance and the tibialis anterior muscle during the swing phase. However, tibialis anterior muscle activity was decreased during the loading response. Landry et al. (2010) demonstrated, by application of EMG circumferential linear arrays, increased EMG activity of selected smaller extrinsic foot muscles while standing in MBT compared with conventional shoes that persisted even after a 6-week accommodation period. Granacher et al. (2011) demonstrated that a sandal construction with an unstable element integrated into the sole of the shoe produced postural instability during standing and walking that was associated with higher activation of lower extremity muscles, greater postural sway during quiet standing and greater step width variability when compared to barefoot walking, but with no difference towards the control sandal. To the best of our knowledge, research on changes in muscle activity and kinematic variables during walking following a training period with unstable shoes has not yet been undertaken. Sto ggl et al. (2010) found that the initial exposure to the MBT shoe in subjects who had no prior MBT experience resulted in higher variability of MBT shoes compared with conventional shoes in the pre-training tests and a decrease in movement variability on the MBT shoes during the training intervention to the level of conventional shoes. However, in the study of Sto ggl et al. (2010), measured EMG parameters, which included integrated EMG (IEMG), EMG root mean square (RMS) and median power frequency (MPF), calculated over ground contact time displayed no differences between MBT and conventional shoes, and no change over time. One of their explanations was that the parameters were calculated over the entire ground contact phase and that possible effects in the subphases of the ground contact might then be nullified. Movement parameters can be considered at different levels, and the macroscopic level refers to parameters that consist of microscopic features whose values allow different versions, resulting in the same value of the higher-order macroscopic parameter (Bernstein 1967). Thus, time-related variables and maximal values during ground contact (e.g. peak EMG values and time-to-peak EMG), pre-activation before ground contact and EMG activity during defined phases of the stance might be considered as microscopic variables that might be sensitive measures towards variability. This aspect is supported by the fact that macroscopic kinetic and kinematic variables such as cycle rate, ground contact time and impulse of force revealed no differences between shoes and no changes on training, whereas variables at a more microscopic level were much more sensitive. In addition, analysis of the variability of kinematic variables in subphases of the gait cycle (loading response, midstance, terminal stance) between shoe conditions and analysis of the effects of training adaptations have not yet been reported. The purpose of this study was to compare the variability and magnitude of EMG and kinematic variables during defined phases of the gait while treadmill walking in MBT shoes and conventional shoes, both before and after a 10-week training period. We hypothesized that: (a) wearing MBT shoes without MBT experience would lead to higher variability in EMG activity and kinematic variables during subphases of the stance compared with conventional shoes, (b) daily usage of MBT shoes would lead to a reduction in variability and (c) daily usage of MBT shoes would lead to a change in variability when wearing conventional shoes. Methods Twelve healthy Sport Science students [six males, six females, with a mean age of 24.8 (SD 1.5) years, mean body weight of 64.7 (SD 8.7) kg and mean body height of 172.3 (SD 7.4) cm] volunteered to participate in the study. None of the participants had MBT experience before the start of the study, but all were familiar with running and walking on a treadmill. The methods and experimental protocol of the study were approved by the ethics committee of the University of Salzburg, and all participants were fully acquainted with the nature of the study before they gave their written, informed consent to participate.

Footwear Science 133 Testing and training protocol All tests were performed on a treadmill (HP Cosmos Saturn, Traunstein, Germany); belt dimension 3m1m. The treadmill speed was set at 5 km h 1 at an inclination of 1% for all testing situations in accordance with (a) settings of other treadmill walking tests in our laboratory and (b) walking speeds in the literature (e.g. Nigg et al. 2006a). Following a 3-min phase for accommodation to the test situation, 20 gait cycles were recorded. In the first test, the subject wore a conventional running shoe (Adidas SuperNova, Herzogenaurach, Germany) that was not considered a motion control shoe, after which the set-up was changed to MBT shoes (M-Walk model, Masai Barefoot Technology, Switzerland). The 10-week training intervention started with a standardized introduction to walking in MBT shoes. This process was guided by an authorized MBT instructor and included exercises during standing, walking and running based on the guide for walking with MBT shoes provided by the manufacturer. Participants were then advised to wear the MBT shoes as much as possible, with a minimum daily use of 4 h. For documentation of the training volume, the participants received a protocol instructing them to report the activity and duration when wearing MBT shoes. After the 10-week intervention period, the post-test followed, which was the same as the pre-test but with a changed order in the shoes; in other words, starting with MBT shoes and ending with the conventional running shoe. Because walking is a highly automated routine movement with high stability and the subjects were familiar with running and walking on a treadmill as a result of several test and training sessions prior to the study, the test situation with the conventional shoes served as the control. The fixed order was chosen to (a) not provoke possible shortterm effects in the control shoe situation by first-time usage of MBT shoes in advance at pre-test and (b) not provoke short-term alterations in the MBT shoe situation by use of conventional shoes prior to the tests with MBT shoes at post-test. Therefore, the subjects were advised to report in the laboratory in their MBT shoes. Instruments and phase definitions Plantar pressure distribution and cycle characteristics Plantar pressure distribution was recorded by a Pedar mobile system (Novel GmbH, Munich, Germany) that consisted of two pressure distribution insoles (99 capacitive sensors each), a data logger and cable sets. The signal was transmitted by Bluetooth wireless technology and simultaneously stored (with a sampling rate of 100 Hz) on a computer. The calibration of the insoles was performed using a Pedar calibration device. Validation of the plantar force measurement system was achieved using the procedures proposed by Holmberg et al. (2005). Three-dimensional (3D) kinematic model Whole-body 3D kinematic data were obtained using an eight-camera Vicon MX13 motion capture system (Vicon Peak, Oxford, UK) sampling at 250 Hz. A commercially available gait kinematic model (Plug-In- Gait, Vicon Peak, Oxford, UK) was used as the basis for the attachment of the 39 reflective markers on the anatomical boney landmarks and for calculation of joint centres, segments orientation, centre of mass and joint angles. The 3D joint angle of the knee joint was calculated as Euler rotations of the distal versus the proximal segment. Phase definition Cycle characteristics were calculated from the plantar force data and the time course of the sagittal plane knee angle of the left leg. One cycle was defined from the start of the ground contact of the foot (heel strike) to the start of the subsequent heel strike of the same foot. One cycle was subdivided into ground contact and swing phase. Ground contact started with the heel strike and ended when the plantar force became zero (toe-off). Swing phase was defined as the period from toe-off to the next heel strike of the same foot. In addition, the ground contact phase was further divided into three phases: loading response (heel strike until midstance maximal knee flexion angle), midstance (midstance maximal knee flexion angle until terminal minimal knee extension angle) and terminal stance (terminal knee extension angle until toe-off) (Figure 1) (Schmitt and Rudolph 2008). Electromyography EMG activity was recorded for the biceps femoris (caput longum), vastus medialis, gastrocnemius (caput mediale), tibialis anterior and peroneus longus muscles of the left leg. EMG activity was recorded at 2000 Hz using pre-gelled bipolar Ag/AgCl surface electrodes (Skintact, Leonhard Lang GmbH, Innsbruck, Austria). Prior to electrode fixation, the skin surface was shaved, lightly abraded, degreased and disinfected with alcohol. The electrodes (circle shaped with an 18-mm diameter gel area and a 10-mm diameter iron contact area) were positioned parallel to the fibre direction with an interelectrode spacing of 30 mm on

134 T. Sto ggl and E. Mu ller Figure 1. Representative time course of plantar force (solid line) and sagittal knee angle (dashed line) for determination of subphases within the gait cycle. the surface of the muscle belly according to international standards (Hermens et al. 1999). The reference electrode was attached to the patella. To secure equal location of electrode positioning between pre- and post-tests, the electrode positions were marked with a waterproof marker. If the marking started to wear off or fade, subjects were asked to redraw it. The active and reference electrodes for each muscle were connected to single differential amplifiers (amplification up to 5000; input impedance 10 G; common mode rejection ratio 120 db) and the EMG signal was hardware band-passed (10 500 Hz at 3 db) to remove noise at low and high frequencies. Before calculation of EMG variables, the raw EMG signals were digitally band-pass filtered (10 400 Hz; Butterworth secondorder) to remove low- and high-frequency noise that was not completely suppressed by the hardware bandpass filter (Winter 1990). The cut-off frequency of the filter was based on visual inspection of the power spectra of the EMG signals. IEMG, RMS EMG and MPF were calculated. For an estimation and comparison of the maximal relative intensity of activation of different muscles, an EMG peak value was determined. Therefore, the band-pass filtered data were full-wave rectified and low-pass filtered (50 Hz; Butterworth second-order) to create a linear envelope, allowing a clearer determination of peak values according to real peak EMG activation and excluding short-term EMG spikes. The maximum value and the time point of the maximal value were denoted as EMG peak and temg peak, respectively. The EMG variables were calculated for each muscle and for each of the following phases: total cycle, ground contact phase, swing phase, loading response, midstance and terminal stance. For further statistical analysis, mean values across all measured muscles in the single analysed phases were calculated. Collection and analysis of biomechanical data Data for plantar force, 3D kinematics and EMG activity were collected by single measurement systems. EMG activity was recorded by a complete system (Biovision, Werheim, Germany) consisting of one input box with 16 channels connected to an A/D converter card (DAQ 6024 E A/D card 12-bit, National Instruments, Austin, TX, USA) and a portable pocket PC (Compaq ipaq H3800) to store the kinetic and kinematic data for further off-line analysis. Synchronization between the data logger, the Vicon system and the Pedar mobile system was achieved with a flashlight and with a synchronization signal produced by the start of the Pedar mobile system. The measurement equipment in its entirety weighed 1.5 kg and was installed in a hip belt. The processing of all data was managed using Vicon Nexus 1.6 (Vicon Peak, Oxford, UK) and IKE-master software (IKE-Software Solutions, Salzburg, Austria).

Footwear Science 135 Table 1. Variability (coefficient of variation over 20 cycles) of kinematic variables analysed with MBT and conventional shoes (CS), before (PRE) and after (POST) the training intervention. PRE POST Variable MBT CS MBT CS F 1,11 p value p 2 Duration of midstance 4.9 2.4 3.7 1.1 3.5 1.1 4.6 2.0 0.14 a 0.0 b 6.7 c Duration of terminal stance 6.1 2.2y 4.7 2.3 4.1 1.4** 4.1 2.0 11.7 a 2.2 b 8.2 c Swing time 2.4 0.7 2.2 0.8 2.4 0.5y 1.9 0.6 0.2 a 4.1 b 0.6 c Global variability of cycle 4.0 1.2y 3.2 0.7 3.0 0.7* 3.0 0.9 6.8 a characteristics 2.1 b 5.8 c COM end loading response 0.31 0.23 0.22 0.07 0.19 0.08 0.24 0.12 0.5 a 1.3 b 11.0 c COM end midstance 0.35 0.20 0.30 0.08 0.26 0.10 0.25 0.10* 3.9 a COM, centre of mass;, not statistically significant. Results are expressed as percentage mean SD. F and p values are presented for two-way (2 2) ANOVA. *p<0.05, **p<0.01. Different from pre-test. ydifferent from conventional shoe. a Main effect time. b Main effect shoe. c Time shoe interactive effect. Statistical analysis All data were checked for normality using the Shapiro Wilk test and presented as means and standard deviations (SD). For measure of variability, the coefficient of variation over 20 consecutive gait cycles was taken. Two-way repeated measures ANOVAs (time - shoe) were performed to check for global differences between the pre- and post-training situations, between the conventional shoe and the MBT shoe and for interaction effects. Paired sample t-tests were applied to check for differences between MBT and conventional shoes during pre- and post-test, and changes within each group from pre- to post-test. Effect sizes using partial eta squared ( p 2 ) were calculated. Statistical significance was set at <0.05 for all analyses. All statistical tests were processed using SPSS version 18.0 (SPSS Inc., Chicago, IL, USA) and Office Excel 2010 (Microsoft Corporation, Redmond, WA, USA). Results The mean daily usage of MBT shoes during the 10-week training intervention was 5.1 (SD 1.2) h among the participants, which was above the set minimum goal of 4 h per day. Significant differences in 1.5 b 0.7 c <0.05 0.38 <0.01 0.52 <0.05 0.43 <0.1 0.27 <0.05 0.38 <0.05 0.35 <0.01 0.51 <0.1 0.26 the variability between the MBT shoe vs. conventional shoe situation during both pre- and post-training interventions are presented in Tables 1 and 2. Concerning variables describing cycle characteristics and kinematics of the knee angle and centre of mass, the basic pattern was characterized by a global reduction in variability from pre- to post-test, with, in part, greater reduction in variability with MBT shoes compared to conventional shoes. No differences in the variability between MBT and conventional shoes at either the pre- or post-test were found for ground contact time and cycle rate (both p > 0.05). For the EMG-related variables, the basic pattern was generally characterized by equal variability, with only a minority of variables demonstrating higher variability at pre-test for the MBT shoe compared with the conventional shoe, followed by a reduction in variability with the MBT shoe and an increase in variability with the conventional shoe towards post-test. No significant differences between shoes or changes with time were observed concerning MPF, and regarding all the calculated parameters of muscle activity for the tibialis anterior. Significant differences between the magnitudes of the collected variables describing cycle characteristics are presented in Table 3. No differences between shoe conditions were found for cycle time at both pre- and

136 T. Sto ggl and E. Mu ller Table 2. Variability (coefficient of variation over 20 cycles) of electromyographic variables analysed with MBT and conventional shoes (CS), before (PRE) and after (POST) the training intervention. PRE POST Variable MBT CS MBT CS F 1,11 p value p 2 Gastrocnemius Peroneus longus Vastus medialis Biceps femoris RMS loading response 38.9 13.9 29.4 27.1 31.5 5.0y 48.2 25.6 1.6 a 0.5 b 7.3 c EMG peak loading 45.4 14.9 35.7 22.7 40.8 11.1y 58.9 27.8* 3.9 a response 0.5 b 9.9 c RMS midstance 16.8 4.5 13.5 6.7 13.1 4.8** 32.8 39.5 1.6 a 2.9 b 3.9 c EMG peak 27.8 6.1 24.7 6.1 21.5 5.0** 44.0 39.1 1.2 a midstance 3.6 b 4.7 c IEMG swing 19.5 4.6yy 13.3 4.7 18.6 8.6 34.9 36.8 0.9 a phase 3.2 b 4.6 c EMG peak 35.7 10.7 31.9 12.6 22.4 7.2***yy 41.4 23.0 0.4 a midstance 6.2 b 10.2 c temg peak swing 41.3 1.0 41.1 1.1 40.3 1.0 40.5 0.8 8.1 a 0.01 b 0.4 c RMS loading 18.0 7.9 16.7 6.7 19.3 8.9 34.7 26.2* 4.1 a response 2.5 b 6.4 c IEMG midstance 34.7 10.5y 23.4 13.6 20.8 5.4*** 48.0 58.2 0.8 a 0.3 b 4.9 c RMS midstance 39.1 12.6 29.2 13.7 21.4 7.0** 51.2 64.3 0.1 a 1.1 b 4.3 c EMG peak 50.6 15.8 38.2 16.4 34.2 7.5* 60.7 64.8 0.1 a midstance 0.5 b temg peak midstance RMS loading response IEMG terminal stance 3.5 c 47.6 1.2y 45.4 0.9 46.4 1.1 45.4 0.7* 0.1 a 12.3 b 0.2 c 41.5 28.4 38.4 16.7 34.9 25.1y 47.7 25.5 0.07 a 1.0 b 6.1 c 38.4 15.3yy 26.1 11.6 26.7 18.7* 42.7 39.6 0.1 a 0.2 b 6.1 c <0.05 0.40 <0.1 0.26 <0.01 0.47 <0.1 0.26 <0.1 <0.1 0.25 0.30 <0.1 0.29 <0.05 <0.01 <0.05 <0.1 <0.05 0.36 0.48 0.42 0.27 0.37 <0.05 0.31 <0.05 0.28 <0.1 0.24 <0.01 0.53 <0.05 0.36 <0.05 0.36, not statistically significant. Results are expressed as percentage mean SD. F and p values are presented for two-way (2 2) ANOVA. *p<0.05, **p<0.01, ***p<0.001. Different from pre-test. yp<0.05, zp<0.01. Different from conventional shoe. a Main effect time. b Main effect shoe. c Time shoe interactive effect. post-test, but cycle time was globally attenuated (p < 0.05) from pre- to post-test, especially with MBT shoes (p < 0.01). At both pre- and post-test, the duration of loading response and terminal stance was shorter (both, p < 0.001), the duration of midstance and swing phase longer (p < 0.01 and p < 0.001) and the ground contact time shorter (p < 0.1) with MBT shoes compared with conventional shoes. At pre-test, ground contact time was shorter with MBT shoes (p < 0.01) and decreased for both MBT and conventional shoes (p < 0.01) towards similar values between the shoe conditions at post-test. Mean knee angle flexion velocity during loading response was globally increased over the training period for both shoe

Footwear Science 137 Table 3. Variables relating to cycle characteristics with MBT and conventional shoes (CS), before (PRE) and after (POST) the training intervention. PRE POST Variable MBT CS MBT CS F 1,11 p value p 2 Duration of loading response (ms) 136 13yyy 146 16 133 13yyy 142 15 0.7 a 26 b 0.8 c Duration of midstance (ms) 293 26y 282 25 292 27yy 277 22 2.7 a 10.7 b 1.6 c Duration of terminal stance 211 13yy 223 14 207 10yy 221 11 2.4 a (ms) 13.9 b 0.6 c Ground contact time (ms) 640 32yy 651 33 632 32* 639 28* 11.6 a 4.8 b 1.3 c Swing time (ms) 408 22yyy 386 24 398 23*yy 385 19 1.6 a 40 b 3.8 c Cycle time (s) 1.05 0.05 1.04 0.05 1.03 0.05** 1.02 0.04 6.1 a 2.1 b 0.5 c Mean knee flexion velocity 96 16 96 24 109 12* 101 24 5.4 a loading response ( /s) 0.5 b Mean knee extension velocity midstance ( /s) Mean knee flexion velocity terminal stance ( /s) Knee flexion range of motion terminal stance ( ) Mean vertical COM position during stance (mm) conditions (p < 0.05). During midstance, a trend towards a global higher knee angle extension velocity was observed for the conventional shoe (p < 0.1), which was significant at pre-test (p < 0.05). Both knee flexion range of motion and angular velocity during terminal stance were globally greater in the conventional shoe situation compared with MBT (p < 0.001 and p < 0.05), especially at pre-test. The mean vertical position of the centre of mass during the stance phase was globally greater with MBT shoes (p < 0.001), especially at pre-test, and globally increased during the adaptation period (p < 0.05), with a trend towards greater increase in the conventional shoes compared with MBT shoes (p < 0.l). 2.7 c 60 13y 65 15 63 11 66 13 6.1 a 2.1 b 0.4 c 177 22yy 196 21 197 8 199 24 2.4 a 7.2 b 3.1 c 37 5yyy 43 6 41 6 44 5 1.3 a 23.1 b 1.3 c 992 55yy 960 47 1003 58***y 978 47*** 21 a COM, centre of mass;, not statistically significant. Results are expressed as mean SD. F and p values are presented for two-way (2 2) ANOVA. *p<0.05, **p<0.01. Different from pre-test. yp<0.05, zp<0.01, yyyp<0.001. Different from conventional shoe. a Main effect time. b Main effect shoe. c Time shoe interactive effect. 8.8 b 4.0 c < 0.001 <0.01 <0.001 <0.01 <0.1 <0.001 <0.1 <0.05 < 0.05 <0.1 <0.5 <0.001 <0.001 <0.05 <0.1 0.72 0.50 0.57 0.50 0.31 0.79 0.25 0.37 0.41 0.30 0.39 0.68 0.65 0.46 0.27 Mean EMG values of all measured muscles in the single phases of the gait cycle at pre- and post-test when walking with MBT shoes and conventional shoes are presented in Table 4. EMG activity during loading response at pre-test was lower with MBT shoes when compared with conventional shoes (p < 0.05). This was especially true for the tibialis anterior (p < 0.001) and peroneus longus (p < 0.05), while for the other muscles no differences were observed. The training intervention led to a greater decrease in muscle activity in the conventional shoe situation to similar EMG levels between shoe conditions at post-test during loading response (interaction time shoe p < 0.01). EMG activity was equal between shoe conditions in the

138 T. Sto ggl and E. Mu ller Table 4. Magnitude of electromyographic variables analysed with MBT and conventional shoes (CS), before (PRE) and after (POST) the training intervention. PRE POST Variable MBT CS MBT CS F 1,11 p value p 2 Loading response IEMG 0.11 0.09y 0.16 0.14 0.07 0.04 0.07 0.05 2.9 a 6.7 b 9.7 c RMS 0.24 0.17y 0.32 0.26 0.16 0.09 0.15 0.11 4.2 a 2.7 b 9.5 c EMG peak 0.48 0.33y 0.63 0.52 0.32 0.17 0.30 0.21 3.2 a 3.2 b 9.4 c MPF 66 14 65 17 78 14* 82 9** 0.2 a 7.1 b 3.2 c Midstance IEMG 0.19 0.07 0.20 0.09 0.17 0.10y 0.15 0.10 1.9 a 0.4 b 2.7 c MPF 74 12y 64 13 79 13 76 10* 12.9 a <0.01 6.9 b <0.05 1.7 c Terminal stance IEMG 0.11 0.05 0.14 0.07 0.09 0.06 0.10 0.06 3.1 a 3.4 b <0.1 0.6 c MPF 70 12y 63 13 78 14* 76 9* 6.5 a <0.05 7.6 b <0.05 1.5 c Swing phase IEMG 0.22 0.12 0.23 0.11 0.16 0.08y 0.15 0.08 2.7 a 0.04 b 1.6 c MPF 65 12 64 13 80 10** 79 10** 9.0 a <0.05, not statistically significant. Results are expressed as mean SD. F and p values are presented for two-way (2 2) ANOVA. *p<0.05, **p<0.01. Different from pre-test. ydifferent from conventional shoe. a Main effect time. b Main effect shoe. c Time shoe interactive effect. remaining phases of the stance at pre-test. At post-test IEMG activity was higher with MBT shoes compared with conventional shoes during midstance and in the swing phase (p < 0.05), which was especially true of the gastrocnemius and peroneus longus (both p < 0.05) with tendencies for the tibialis anterior. MPF was higher with MBT shoes during midstance and terminal stance for all measured muscles except for the biceps femoris. Furthermore, MBT shoes demonstrated an increase in MPF from pre- to post-test during all phases of the stance for both shoe conditions [loading response, midstance, terminal stance (all p < 0.05), swing phase (p < 0.01)]. Discussion The main findings were that the first exposure to the unstable MBT shoe in subjects who had no prior MBT 1.0 b 0.1 c <0.05 0.38 <0.01 0.47 <0.1 0.27 <0.01 0.46 <0.01 0.46 <0.05 0.39 0.54 0.39 0.24 0.37 0.41 0.45 experience followed by a 10-week accommodation period with MBT resulted in (a) trends towards higher variability in MBT shoes compared with conventional shoes at pre-test concerning selected kinematic and EMG variables; (b) a global attenuation from pre- to post-test in the variability of kinematic variables in both shoe conditions, with greater reduction in the MBT situation (interaction effect); (c) a global reduction in variability of EMG variables in both shoes or an increase in the variability with conventional shoes (interaction effect) to a higher variability at post-test in conventional shoes compared with MBT; (d) equal cycle times but differences in the durations of the defined phases within the cycle between shoe conditions at both pre- and post-test and a reduction in cycle and ground contact time following the training period; (e) a greater mean

Footwear Science 139 vertical position of the centre of mass during stance phase with MBT shoes, with an increase following the training period in both shoe conditions; (f) lower EMG activity with MBT shoes during loading response at pre-test, with greater reduction in EMG activity for the conventional shoes to equal levels at post-test (interaction effect) and higher EMG activity for MBT shoes in midstance and swing phase at post-test when compared with conventional shoes; and (g) increased MPF at midstance and terminal stance with MBT shoes and a global increase in MPF for all phases of the stance for both shoe conditions. EMG activity during walking with unstable shoes The results of this study indicated no clear pattern for increased muscle activity during walking with MBT shoes compared with conventional shoes. At pre-test, during loading response, there was lower EMG activity with MBT shoes compared with conventional shoes, which was especially true for the tibialis anterior and peroneus longus. The result for the tibialis anterior is in agreement with Romkes et al. (2006), who demonstrated that muscle activity in the tibialis anterior was lower with MBT compared with conventional shoes especially in the first part of the stance. This difference was attributed to an increased dorsiflexion angle at initial contact. However, the aspect about increased cocontraction between tibialis anterior and gastrocnemius muscles to compensate for greater instability with MBT shoes cannot be supported by the current study. For all other phases of the gait cycle, no differences between shoe conditions were observed with regard to EMG variables. The training period led to a reduction in EMG activity that was more pronounced in the conventional shoe condition. In addition, at post-test, higher EMG activity in midstance and swing phases for MBT shoes was observed. This result may be considered from different standpoints: (a) the MBT training intervention led to increased efficiency, as the wearer was able to better control the degrees of freedom, relying on more passive mechanics as a result; (b) the MBT shoe might assist the wearer in finding a more optimal (less variable and less active) solution for certain muscles by reducing the amount of redundant activity in some muscles by optimizing others; and (c) the MBT shoe training led to less muscle activity based on some sort of deconditioning with reduced function of the muscles. However, future studies are needed to gain more insight into this issue. The findings at pre-test are partially in line with the study of Nigg et al. (2006a), reporting non-significant trends towards higher and lower muscle activities in selected lower extremity muscles determined for the time interval from 200 ms before heel strike to 500 ms after heel strike during walking with MBT shoes compared with conventional shoes. By contrast, higher muscle activity during walking with MBT shoes (Romkes et al. 2006, Buchecker et al. 2010) and walking with a sandal with an integrated unstable element (Granacher et al. 2011) has been reported. The differences from these three studies might be based on the recruited participants in the current study, as all of them were Sport Science students who might have had the ability to handle unstable situations more easily because of their additional movement experiences. To the best of our knowledge, this study is the first to analyse the effects of a 10-week training period with MBT shoes on the magnitude of muscle activity and kinematics during walking. The results indicate that the MBT training intervention led to destabilizing effects of certain subcomponents of the gait with interaction effects towards a greater reduction in muscle activity with conventional shoes to, in part, significantly lower levels when compared with the MBT shoe condition, but also a shift towards higher EMG activity for MBT shoes in midstance and swing phase in the post-test situation. Of note, MPF was greater with MBT shoes in midstance and terminal stance, and MPF globally increased from pre- to posttest in all subphases of the cycle and in both shoe conditions. This might indicate a slight change in the fibre type recruitment, conduction velocity and/or firing behaviour (e.g. Fuglsang-Frederiksen and Ronager 1988, Gerdle et al. 1991) when using MBT shoes and that the adaptation period leads to a further increase in both shoe conditions. Based on these results it might be speculated that the rounded sole of the MBT shoe alters gait towards increased recruitment of faster fibre types and/or increased firing behaviour during the second half of stance. This effect seems to be even more pronounced following the training period and also demonstrates transfer effects to walking with conventional shoes. Differences and changes in kinematics with MBT shoes The initial application of MBT shoes did not result in changes in cycle time when compared with the conventional shoes. This is somewhat different from the findings of Romkes et al. (2006), who demonstrated that increased cycle time and reduced cycle length when walking at self-selected speeds were lower for the MBT situation. The differences in our study might be related to the treadmill walking situation and

140 T. Sto ggl and E. Mu ller the fixed treadmill speed for both shoe conditions. Of note, following the 10-week adaptation period, even cycle time was globally reduced. The subphases of the cycle were characterized by reduced duration of loading response, terminal stance and ground contact, and increased duration of midstance and swing phase in the MBT shoe condition when compared with walking in conventional shoes. The reduced duration of loading response with MBT shoes was not paralleled by increased mean knee angle flexion velocities. However, the training adaptation led to an increase in mean knee flexion velocity from pre- to post-test, which might be attributed to a greater knee flexion range of motion but was only significant for the MBT situation. In opposition, knee angle extension velocity during midstance was greater for the conventional shoe, which was mainly coupled to the shorter duration of midstance with conventional shoes. Even though the duration of terminal stance was globally lower for MBT shoes, both knee flexion range of motion and angular velocity during terminal stance were globally greater in the conventional shoe situation compared with MBT. Hence, the use of MBT shoes leads to a shortened terminal stance with lower knee angle flexion range of motion and angular velocity. It is noteworthy that the mean vertical position of the centre of mass during stance phase was globally approximately 3 cm greater with MBT shoes, especially at pre-test, and globally increased during the adaptation period with a trend towards greater increase in the conventional shoes compared with MBT shoes. This result might be based, in part, on the greater height of the sole of the MBT shoes (unloaded sole thickness of MBT was 4 cm, compared with 1.9 cm of the conventional shoe); however, the change and interaction effect from pre- to post-test might indicate a more upright gait in the MBT and particularly in the conventional shoes. This finding is in accordance with a previous study of New and Pearce (2007), demonstrating changes in upright posture during walking with MBT shoes. In addition, it seems that the MBT training period allows for transfer effects to a more upright posture when walking with conventional shoes. These results demonstrate that, although walking with MBT shoes does not alter the gait on a macroscopic level, on a microscopic level distinct differences to walking with conventional shoes are apparent. In this context, walking is a highly automated routine movement with high stability. The new inputs by altered timing pattern of subphases of the gait cycle might allow for changes in sensory information, enabling changes in the gait pattern (Bertenthal, 1999, Davids et al. 2003, Waddington and Adams 2003). Evidence for that might be the fact that, together with the above-mentioned changes in EMG activity, both cycle time and ground contact time were reduced and the vertical position of the centre of mass was increased in both shoe conditions following the accommodation period. Variability in kinematic data during gait Several studies have analysed the variability of step length, step width and step time during walking using conventional shoes (Maki 1997, Owings and Grabiner 2004a,b). In contrast to conventional training shoes that aim to support, guide and/or cushion the foot, the MBT shoe was designed to be unstable. In this context, it was recently demonstrated that an unstable sandal construction (Granacher et al. 2011) and the MBT shoe (Nigg et al. 2006a, b, Landry et al. 2010) led to greater postural sway. In addition, the unstable sandal construction revealed greater step width variability during walking when compared to barefoot walking, but with no difference compared with the control sandal (Granacher et al. 2011). In the current study, with the exception of higher variability in the duration of the terminal stance with MBT shoes, no differences between shoe conditions at pre-test were observed. These findings are in line with previous observations of Sto ggl et al. (2010), demonstrating no differences between shoe conditions in the variability of variables related to a higher macroscopic observation level (e.g. cycle time, cycle rate, EMG variables during ground contact). However, the training period led to a global reduction of the variability in variables describing the subphases of a gait cycle (more microscopic observation level), with greater reduction in variability in the MBT shoe situation. The adaptation of the subjects to the less stable shoe condition, leading to a global reduction in movement repeatability, is an effect with positive implications. The decreased variability might contribute to a lower risk of patients falling or sustaining injuries (e.g. Wegener et al. 1997, Jadelis et al. 2001, Owings and Grabiner 2004a, b) despite wearing unstable shoes, and therefore deriving the advantages when using MBT shoes as described above. Variability in EMG activity Granata et al. (2005) reported that, in a population of normally developing children, within-session variability of the EMG waveforms during a freely selected walking speed was approximately twice the level of healthy adults. Sto ggl et al. (2010) observed greater variability in the majority of kinetic and kinematic variables with MBT shoes, but were not able to detect

Footwear Science 141 greater variability in the EMG parameters analysed (IEMG, RMS, MPF) over the ground contact phase with MBT shoes compared with conventional shoes, displaying no differences between shoes and no change over time. One explanation was that the variables were calculated over the entire ground contact phase and that possible effects in the subphases of the ground contact might then be nullified. Therefore, time-related variables and maximal EMG values during the ground contact and the subphases of the stance might be more sensitive towards variability. In the current study, higher variability in muscular activity at pre-test was found, part, for MBT when compared with conventional shoes. In addition, in several variables the adaptation period resulted in interaction effects described by a reduction in variability with MBT shoes and increases in variability with the conventional shoes. As discussed earlier, these results are evidence that long-term application of MBT shoes might change sensory information, enabling changes in the gait pattern. Some of the functional relevance might be seen in adaptations in posture towards a more upright position during walking, higher variability during walking, especially on even surfaces, and changes in gait towards diminished joint loadings, for example in cohorts suffering from degenerative joint disease (Buchecker et al. 2010). However, caution should be exercised when interpreting variability in EMG data because of the high variability in EMG data per se (Kadaba et al. 1989). This aspect can be seen in the much higher variability in all of the calculated EMG variables when compared with the kinematic variables (compare variability values of Tables 1 and 2). However, Komi and Buskirk (1970) demonstrated that repeatability for surface electrodes was good within an experiment and between different days for testing. Taking the results on variability of kinematic and EMG variables together, the current study supports the idea that the MBT shoe provokes instability during walking leading to an increased variability when compared with conventional shoes. The general pattern in the majority of measured variables is characterized by higher variability of MBT shoes compared with the conventional shoes in the pre-training tests and interaction effects towards a reduction in variability in both shoe conditions or an increase in variability in the conventional shoes following the training period. Glazier and Davids (2009) have demonstrated that constraints can be used to manipulate motor behaviour to develop stability of functional coordination patterns. By application of different constraints, single movement aspects can be increased or weakened. Therefore, in the current study we have demonstrated that the MBT shoe design might serves as a motor constraint applicable during everyday activity. Limitations The EMG signal is highly sensitive to the location of the electrodes, especially when electrodes have to be replaced, for example before and after a training period. Marking the electrode position ensures that the electrodes are located at the same position of the muscle; however, changes in the electrode to-skin impedance by possible changes in skin and subcutaneous fat cannot be ruled out. This variation might have an effect on the magnitude of the EMG signal but should be of minor importance with regard to the calculated variability within the EMG signal. Another limitation of the study might be attributed to the transfer of the results from treadmill to overground gait, although it was recently shown that very few differences were found in temporal gait parameters or leg kinematics between treadmill and overground walking. Nevertheless, differences in muscle activity were observed between the two walking modalities, particularly in the tibialis anterior throughout stance (Lee and Hidler 2008). However, the treadmill situation does allow for the best possible standardization of walking speed for comparison between shoe conditions and also for the pre- and post-training test situation. Conclusions The current study has demonstrated that wearing MBT shoes leads to alterations in the gait pattern on a microscopic level. Analysis of the subphases of the gait cycle (loading response, midstance, terminal stance and swing phase) enables detection of differences between shoe conditions with regard to magnitude and variability of selected kinematic and EMG variables. At pre-test a trend towards higher variability, but equal magnitude of the majority of variables, in the MBT situation compared with conventional shoes was observed. However, the 10-week training period with MBT shoes resulted in a global attenuation in the variability of kinematic variables in both shoe conditions but also interaction effects in variability in selected EMG variables with a reduction with MBT and an increase with conventional shoes to similar variability levels. The application of MBT shoes did not reveal greater muscle activity in lower extremity muscles during walking, but following the 10-week accommodation period an interaction effect towards greater reductions in EMG activity for the conventional shoes to equal or lower levels compared with

142 T. Sto ggl and E. Mu ller MBT shoes were observed. Furthermore, the MBT training period led to changes in cycle characteristics towards shorter cycle and ground contact times and an increase in the vertical position of the centre of mass during the stance phase, indicating a more upright posture during walking in both shoe conditions. The study supports the idea that the MBT shoe provokes alterations in the walking pattern and instability during walking, leading to interaction effects towards walking with conventional shoes. Therefore, we have demonstrated that the MBT shoe design might serve as a motor constraint applicable during everyday activity, applicable, for example, to reaching a more upright posture during walking and inducing changes in gait characteristics towards increased variability especially while walking on even surfaces. 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