The Relationship Between Joint Kinetic Factors and the Walk Run Gait Transition Speed During Human Locomotion

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1 Journal of Applied Biomechanics, 2008, 24, Human Kinetics, Inc. The Relationship Between Joint Kinetic Factors and the Walk Run Gait Transition Speed During Human Locomotion Alan Hreljac, 1 Rodney T. Imamura, 1 Rafael F. Escamilla, 1 W. Brent Edwards, 2 and Toran MacLeod 1 1 California State University Sacramento and 2 Iowa State University The primary purpose of this project was to examine whether lower extremity joint kinetic factors are related to the walk run gait transition during human locomotion. Following determination of the preferred transition speed (PTS), each of the 16 subjects walked down a 25-m runway, and over a floor-mounted force platform at five speeds (70, 80, 90, 100, and 110% of the PTS), and ran over the force platform at three speeds (80, 100, and 120% of the PTS) while being videotaped (240 Hz) from the right sagittal plane. Two-dimensional kinematic data were synchronized with ground reaction force data (960 Hz). After smoothing, ankle and knee joint moments and powers were calculated using standard inverse dynamics calculations. The maximum dorsiflexor moment was the only variable tested that increased as walking speed increased and then decreased when gait changed to a run at the PTS, meeting the criteria set to indicate that this variable influences the walk run gait transition during human locomotion. This supports previous research suggesting that an important factor in changing gaits at the PTS is the prevention of undue stress in the dorsiflexor muscles. Keywords: walking, running, inverse dynamics There is evidence to suggest that the gait transitions of some quadrupeds are triggered by joint kinetic factors. Several researchers (Argue & Clayton, 1993; Biewener et al., 1983; Biewener & Taylor, 1986; Blickhan et al., Hreljac, Imamura, and MacLeod are with the Department of Kinesiology & Health Science, California State University, Sacramento; Escamilla is with the Department of Physical Therapy, California State University, Sacramento; and W. Brent Edwards is with the Department of Health and Human Performance, Iowa State University. 1993; Farley & Taylor, 1991; Vilensky et al., 1991) have hypothesized that a variety of quadrupeds change gaits to prevent musculoskeletal stresses, particularly at joints, from exceeding critical levels, thereby reducing the risk of injury. Using invasive techniques (which could not be used ethically in humans), it has been demonstrated (Biewener et al., 1983; Biewener & Taylor, 1986; Rubin & Lanyon, 1982) that bone and joint stresses are reduced in small horses, dogs, and goats when changing gait from a trot to a gallop. Using noninvasive techniques (measurement of ground reaction forces), other researchers (Farley & Taylor, 1991) reached similar conclusions regarding a group of large horses. It should be noted, however, that similar results were not found to occur in the walk trot transition of the same animals, and that no more than three test animals were used in any of these studies. Owing to the small sample sizes, inherent dissimilarities between quadrupedal and bipedal gaits, and the fact that inconsistent results were obtained between the walk trot and the trot gallop gait transitions of animals, it is difficult to determine whether these results could be generalized to the walk run gait transition of humans. In an effort to determine whether kinetic factors are determinants of the walk run gait transition in humans, two studies (Hreljac, 1993; Raynor et al., 2002) have applied the methodology of Farley and Taylor (1991) as closely as possible to human subjects. Although Raynor et al. (2002) noted a weak association between the preferred transition speed (PTS) and loading rate, neither of these studies produced convincing evidence to suggest that ground reaction force (GRF) variables are related to the walk run gait transition during human locomotion. Although these external kinetic factors were not found to be triggers of the walk run gait transition in humans, it is possible that joint kinetic factors, similar to those determined in various animal studies, may be associated with the walk run gait transition in humans. 149

2 150 Hreljac et al. Owing to ethical concerns, the invasive techniques used in the previously cited animal studies cannot be applied to human subjects. The technique of inverse dynamics, however, has been developed to quantify joint moments and forces noninvasively (Glitsch & Baumann, 1997). Two recent studies that have utilized this technique suggest that lower extremity joint kinetics during the swing phase of gait are possible triggers of the walk run gait transition. Prilutsky and Gregor (2001) determined that during the swing phase, dorsiflexor muscles are stressed to unacceptably high levels when walking at speeds near the PTS, and these stresses are subsequently reduced when gait changes to a run. Similarly, when examining lower extremity joint kinetics during the swing phase of gait, McLeod et al. (2006) concluded that the PTS appears to occur at critical levels of ankle dorsiflexor moments and power, suggesting that the ankle kinetics are associated with the PTS. These conclusions are consistent with the results of previously conducted kinematic and neuromuscular-based studies (Hreljac, 1995; Hreljac et al., 2001; Segers et al., 2007), which established that the high dorsiflexor activation levels when walking at speeds near the PTS may be a determinant of the walk run gait transition in humans. It should be noted that lower extremity joint moments and forces found during the swing phase of walking and running are considerably less than the joint moments and forces during the stance phase of the corresponding gait (Frigo et al., 1996; Manal et al., 2002; Swanson & Caldwell, 2000). No published human studies to date have examined joint kinetic variables during the stance phase as possible determinants of the walk run gait transition, even though it is these variables that are most closely related to variables that have been found to be determinants of the trot gallop gait transitions of quadrupeds. In previous studies related to the walk run gait transition (Brisswalter & Mottet, 1996; Diedrich & Warren, 1995, 1998; Hreljac, 1993, 1995; Hreljac et al., 2001; Mercier et al., 1994; Raynor et al., 2002; Segers et al., 2006), one criterion established to identify whether a variable was a determinant of the gait transition was that the variable must exhibit an abrupt change in its value as gait is changed. This is consistent with the definition that a gait is a pattern of locomotion characteristic of a limited range of speeds described by quantities of which one or more change discontinuously at transitions to other gaits (Alexander, 1989, p. 1200). In addition to merely changing abruptly, the direction of the change must be considered. If the value of a variable increases as speed increases during walking, the variable must suddenly decrease in value when gait is changed to a run. The second criterion established to examine whether a variable was a determinant of the walk run gait transition (Hreljac, 1993, 1995; Hreljac et al., 2001) was that the value of the variable at the PTS during running must return to a level noted at lower speeds during walking. In the current study, a variable was considered to be a determinant of the walk run transition only if these two criteria were met. The primary purpose of this study was to examine whether lower extremity joint kinetic factors during the stance phase of gait trigger the walk run gait transition during human locomotion, as has been suggested to be the case for animals. An understanding of whether similar mechanisms trigger gait transitions could enhance our comprehension of the control of human gait. Today, there is still controversy in the biomechanics community regarding the factors that trigger the walk run gait transition in humans. The results of this study may help to resolve this contentious issue. Methods The subjects in this study were 16 young, healthy, college students (eight males, eight females) who were free from musculoskeletal injury or disease at the time of participation in the study. Prior to participation, subjects signed informed consent forms, reiterating the basic procedures and intent of the study, as well as warning of potential risks involved as a result of participation. Subjects who were unfamiliar with treadmill locomotion were habituated ahead of the first testing session by walking and running at a variety of speeds on the treadmill for a period of approximately 15 min (more if requested). This time period has been shown to be sufficient to allow for accommodation to treadmill locomotion (Charteris & Taves, 1978; Schieb, 1986; Wall & Charteris, 1980). On the first of two testing sessions, the PTS of each subject was determined. This session occurred on a day prior to the collection of kinetic data to ensure that fatigue was not a factor during the experimental testing. To determine the PTS for each subject, the treadmill speed, which was controlled by an experimenter (controller unseen by subject), was initially set to a speed at which subjects would be able to walk comfortably (approximately 1.4 m s 1 ). Subjects were instructed to mount the treadmill and utilize the gait that felt most natural. If the subject indicated that walking was the preferred gait at that speed (as was the case for all subjects at the initial speed), the treadmill was stopped, and the subject dismounted. The treadmill speed was then increased by about m s 1 before the subject remounted. Again, after a 30-s decision period, subjects were instructed to indicate the gait that felt most natural at the new speed. If the subject indicated that walking was the most natural gait at the new speed, the procedure was repeated. This process continued until a speed was reached at which the subject determined that running was the most natural gait at the particular speed. This speed was defined as the walk run transition speed. Thus, by starting the treadmill at a high enough speed to ensure that subjects ran (>3.0 m s 1 ) and then decreasing the treadmill speed incrementally, the run walk transition speed was determined. The entire process was repeated three times in random order. In order to obtain a single value, the average of the walk run and run walk transition speeds was defined as the PTS.

3 Joint Kinetics and the Walk Run Transition 151 During the second test session, subjects walked down a 25-m runway, and over a floor mounted force platform (Advance Mechanical Technology, Inc.) at five speeds (70%, 80%, 90%, 100%, and 110% of the PTS), and ran over the force platform at three speeds (80%, 100%, and 120% of the PTS). Three sets of infrared photocell timing lights, connected to a digital timer, located 2 m apart, and centered at the force platform, were utilized to monitor walking or running speed during each trial. Reflective markers were placed on four anatomical landmarks on the right side of the subject, including the greater trochanter, knee joint center, lateral malleolus, and head of the fifth metatarsal. These markers were videotaped by a single digital video camera (240 Hz), in the sagittal plane. Three successful trials were performed for each of the randomly ordered conditions. A trial was considered successful only if the speed was within ±3% of the target speed, if the landing foot completely contacted the force platform, and if there was no visible change in stride length as the subject approached the force platform. The two-dimensional (2-D) kinematic data obtained during the videotaping process were synchronized with GRF data (960 Hz) collected in the horizontal (F x ) and vertical (F y ) directions. The raw 2-D coordinate data were smoothed using a fourth-order, zero-lag, Butterworth filter. Optimal cutoff frequencies were uniquely determined for each coordinate of each marker for both walking and running, using the residual method (Wells & Winter, 1980). Ankle and knee joint velocities were calculated from the smoothed data using a finite difference method. Joint reaction forces and moments were determined using a standard inverse dynamics approach, applying the de Leva (1996) model for necessary anthropometric data. Joint powers were calculated as the product of the respective joint moment and angular velocity. Before analysis, all variables were normalized by dividing by body mass. Dependent variables (DVs) analyzed included maximum ankle dorsi- and plantar flexor moments, maximum knee extensor moment, and maximum power absorption and generation at the ankle and knee. A repeatedmeasures MANOVA was used to compare average values of all DVs between speed and gait conditions. If the hypothesis tested was to be accepted for a variable, the value of the variable would increase as walking speed increased, and then exhibit a decrease when gait changes to a run (at the PTS). Specific preplanned single-degreeof-freedom contrasts were set up to make comparisons between the values of the DVs at adjacent levels of the speed/gait conditions. This included a comparison between the W100 and R100 conditions. For all comparisons, the level of significance was set at α = Results The average PTS of all subjects was 1.96 ± 0.15 m s 1. To illustrate the general pattern of ankle and knee joint moments and power during the stance phase of walking and running at the PTS, sample graphs of these variables are shown in Figures 1 and 2. A representative graph of ankle joint angular velocity is shown for the stance phase of both walking and running at the PTS in Figure 3. All DVs showed some significant increases in value as speed increased within each gait condition, although changes were not always noted between each adjacent speed level of walking and running (Figures 4 6). The maximum ankle plantar flexor moment, knee extensor moment (Figure 4), ankle power absorption, knee power absorption (Figure 5), and knee power generation (Figure 6) all increased significantly as gait changed from a walk to a run at the PTS (W100 vs. R100 conditions). Maximum ankle power generation did not differ significantly between the W100 and the R100 conditions (Figure 6). Thus, none of these variables met the second criterion established for determining whether a variable was a determinant of the walk run gait transition. The maximum ankle dorsiflexor moment (Figure 4) was the only variable that increased as walking speed increased, and then decreased significantly as gait changed from a walk to a run at the PTS (W100 > R100), thereby returning to a level noted at lower speeds of walking. In this study, maximum ankle dorsiflexion moment, which always occurred within the first 20% of the stance phase during both walking and running (Figure 1, top), was the only variable that met both criteria established for a variable to be considered a determinant of the walk run gait transition. Discussion The PTS found in the current study (1.96 ± 0.15 m s 1 ) was well within the range of values that have been reported previously (from 1.89 m s 1 to 2.16 m s 1 ) by other researchers (Beuter & Lefebvre, 1988; Brisswalter & Mottet, 1996; Diedrich & Warren, 1995, 1998; Hreljac, 1993, 1995; Hreljac et al., 2001; Mercier et al., 1994; Minetti et al., 1994; Rotstein et al., 2005; Thorstensson & Roberthson, 1987; Turvey et al., 1999). Because all variables analyzed during this study displayed some level of speed dependence during both walking and running, it is important that the speed ranges used were similar to other studies if results are to be generalized to a larger population. Peak knee power generation increased more than twofold when gait was changed from a walk to run at the PTS (Figure 6). Similarly, peak knee extensor moments were significantly greater when running than walking at the PTS (Figure 4). Both of these variables also increased with increasing speed during both walking and running, indicating a greater reliance upon the knee extensor muscles during the push-off portion of the stance phase as speed increases. These results appear to agree with previous EMG studies (Hreljac et al., 2001; Prilutsky & Gregor, 2001), which have shown that there is substantially greater knee extensor muscle activation during running than walking at speeds near the

4 152 Hreljac et al. Figure 1 Top: Representative graph of ankle moment during the stance phase of walking (solid line) and running (interrupted line) at the PTS. Positive values represent dorsiflexion moments. Bottom: Representative graph of knee moment during the stance phase of walking (solid line) and running (interrupted line) at the PTS. Positive values represent knee extensor moments. PTS. Biewener et al. (2004) attributed the greater knee moments and power during running to decreases in the effective moment arm, primarily owing to greater knee flexion during running. Near the beginning of the stance phase during both walking and running, the muscles of the knee contract eccentrically, primarily to absorb energy (Figure 2, bottom). The rate of energy absorbed (peak knee power absorption) increases with speed during both walking and running (Figure 5), with a greater amount of energy absorbed during running at the PTS than walking at the PTS. It has been suggested (Gunther & Blickhan, 2002; Hamill et al., 2000; Kulas et al., 2006) that greater energy absorption may be indicative of greater joint stiffness or impedance. From this, it could be deduced that

5 Joint Kinetics and the Walk Run Transition 153 Figure 2 Top: Representative graph of ankle power during the stance phase of walking (solid line) and running (interrupted line) at the PTS. Positive values represent energy generation. Bottom: Representative graph of knee power during the stance phase of walking (solid line) and running (interrupted line) at the PTS. Positive values represent energy generation. in the present study, the knee was stiffer during running compared with walking at speeds near the PTS, possibly owing to greater levels of co-contraction between the quadriceps and hamstrings. This seems to also be consistent with the observations of Biewener et al. (2004). As gait changes from a walk to a run at the PTS, the ankle plantar flexors do not generate a significantly greater amount of energy (Figure 6) and exhibit only a slightly greater moment (Figure 4). Similar observations were made by Biewener et al. (2004). Power generation of the ankle (Figure 2a) and plantar flexor moment (Figure 1a) both reach a maximum during the second half of stance during both walking and running. Although the timing differs slightly between walking and running, the

6 154 Hreljac et al. Figure 3 Representative graph of ankle joint angular velocity during the stance phase of walking (solid line) and running (interrupted line) at the PTS. Positive values represent dorsiflexion. Figure 4 Maximum ankle plantar flexor moment (squares), dorsiflexor moment (triangles), and knee extensor moment (circles) for all conditions. Error bars for dorsiflexor moments represent ±1 SD. Error bars for plantar flexor moments represent +1 SD. Error bars for knee extensor moments represent 1 SD. ankle reaches its maximum plantar flexing during the second half of stance in both the walking and running conditions (Figure 3), so it is not surprising that the role of the ankle muscles changes relatively little between walking and running at this time. During the early stages of stance, however, the ankle often behaves quite differently in walking compared with slow running. During walking, the ankle is always plantar flexing immediately after heel strike (Figure 3), with the plantar flexion being controlled by the dorsiflexors (Figure 1, top), which are

7 Joint Kinetics and the Walk Run Transition 155 Figure 5 Maximum knee (circles) and ankle (squares) power absorption for all conditions. Error bars for knee power absorption represent +1 SD. Error bars for ankle power absorption represent 1 SD. Figure 6 Maximum knee (circles) and ankle (squares) power generation for all conditions. Error bars for knee power generation represent 1 SD. Error bars for ankle power generation represent +1 SD. acting eccentrically at this time. There is a similar pattern of initial dorsiflexion displayed during heel strike running. When running slowly (at speeds near the PTS), however, many subjects, even those who are normally heel strikers at slightly greater speeds, utilize a midfoot or a rear-foot landing (Hreljac et al., 2002). When using a mid-foot or forefoot landing, the ankle begins to dorsiflex immediately after foot contact (Figure 3), with the dorsiflexion being controlled by the plantar flexors (Figure 1, top) which are acting eccentrically.

8 156 Hreljac et al. Although the dorsiflexors play only a minimal role during the stance phase of slow running, this muscle group has an important role during the early stages of stance in fast walking (Figure 1, top). There is a fairly large dorsiflexor moment during the first 10 15% of stance during fast walking (at speeds near the PTS). In addition, there is a small amount of energy absorbed at the ankle during the early stance phase of walking (Figure 5). This energy absorption is due to eccentric contractions of the dorsiflexors, contributing further to the stress placed upon the dorsiflexors when walking at relatively fast speeds. Although eccentric contractions do not contribute a large amount to the energy consumption of the muscles, these contractions may contribute to the overall feeling of fatigue perceived by subjects. In previous studies that examined EMG activation at or near the PTS during walking and running (Hreljac et al., 2001; Nilsson et al., 1985; Prilutsky & Gregor, 2001; Segers et al., 2007), it has been established that the dorsiflexors are very active during the latter stages of swing in walking, as the toes are lifted rapidly to avoid ground contact. The dorsiflexor fatigue resulting from this high level of activation has been hypothesized to be associated with the gait transition speed (Hreljac et al., 2001; Segers et al., 2007). The results of the current study indicate that the dorsiflexors continue to play an important role during the early stance phase of walking. The peak dorsiflexor moments found during the early stance phase of walking at the PTS (Figure 4) may not be enough on their own to trigger a gait transition, but when combined with the high levels of dorsiflexor activity during the late stages of swing, it is clear that the dorsiflexors could reach a state of fatigue in which changing gaits would be the best option for reducing this localized fatigue. By changing gait, the fatigue and stress that impacts the relatively small dorsiflexor group could be reduced to a more acceptable level. Although other lower extremity muscle groups, such as the ankle plantar flexors and knee extensors, exhibit greater muscle moments when gait changes from a walk to a run at the PTS (Figure 4), the amount of activation of these muscles when running at the PTS is not close to maximal levels, as shown by earlier researchers (Hreljac et al., 2001). Thus, making a gait change at the PTS may allow all muscles involved to be functioning within physiologically acceptable levels. The only variable that increased during walking, and subsequently decreased when gait was changed to a run, thereby meeting both criteria established for a variable to be considered a determinant of the walk run gait transition, was the peak ankle dorsiflexor moment. Combined with the findings of previous studies, these results suggest that changing gait from a walk to a run at the PTS may prevent excessive stress from being placed on the dorsiflexor muscles. At the same time, more stress is placed on other muscles of the lower extremity, but levels of stress for all involved muscles are all within acceptable limits. References Alexander, R.M. (1989). Optimization and gaits in the locomotion of vertebrates. Physiological Reviews, 69, Argue, C.K., & Clayton, H.M. (1993). A preliminary study of transitions between the walk and trot in dressage horses. 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Energy cost and stride duration variability at preferred transition gait speed between walking and running. Canadian Journal of Applied Physiology, 21, Charteris, J., & Taves, C. (1978). The process of habituation to treadmill walking: A kinematic analysis. Perceptual and Motor Skills, 47, De Leva, P. (1996). Adjustments to Zatsiorsky Seluyanov s segment inertia parameters. Journal of Biomechanics, 29, Diedrich, F.J., & Warren, W.H. (1995). Why change gaits? Dynamics of the walk-run transition. Journal of Experimental Psychology: Human Perception and Performance, 21, Diedrich, F.J., & Warren, W.H. (1998). The dynamics of gait transitions: effects of grade and load. Journal of Motor Behavior, 30, Farley, C.T., & Taylor, C.R. (1991). A mechanical trigger for the trot gallop transition in horses. Science, 253, Frigo, C., Crenna, P., & Jensen, L.M. (1996). Moment-angle relationship at lower limb joints during human walking at different velocities. Journal of Electromyography and Kinesiology, 6, Glitsch, U., & Baumann, W. (1997). The three-dimensional determination of internal loads in the lower extremity. Journal of Biomechanics, 30, Gunther, M., & Blickhan, R. (2002). Joint stiffness of the ankle and the knee in running. Journal of Biomechanics, 35, Hamill, J., Derrick, T.R., & McClay, I. (2000). Joint stiffness during running with different footfall patterns. Archives of Physiology and Biochemistry, 108, 47. Hreljac, A. (1993). Determinants of the gait transition speed during human locomotion: kinetic factors. Gait & Posture, 1,

9 Joint Kinetics and the Walk Run Transition 157 Hreljac, A. (1995). Determinants of the gait transition speed during human locomotion: kinematic factors. Journal of Biomechanics, 28, Hreljac, A., Arata, A., Ferber, R., Mercer, J.A., & Row, B.S. (2001). An electromyographical analysis of the role of dorsiflexors on the gait transition during human locomotion. Journal of Applied Biomechanics, 17, Kulas, A.S., Schmitz, R.J., Shultz, S.J., Watson, M.A., & Perrin, D.H. (2006). Energy absorption as a predictor of leg impedance in highly trained females. Journal of Applied Biomechanics, 22, MacLeod, T.D., Hreljac, A., & Imamura, R. (2006). Internal kinetic factors and the preferred transition speed in humans. Proceedings of the 30th Annual Meeting of the American Society of Biomechanics, Blacksburg, VA: Virginia Tech Wake Forest School of Biomedical Engineering and Sciences. Manal, K., McClay, I., Richards, J., Galinat, B., & Stanhope, S. (2002). Knee moment profiles during walking: errors due to soft tissue movement of the shank and the influence of the reference coordinate system. Gait & Posture, 15, Mercier, J., Le Gallais, D., Durand, M., Goudal, C., Micallef, J.P., & Prefaut, C. (1994). Energy expenditure and cardiorespiratory responses of the transition between walking and running. European Journal of Applied Physiology, 69, Minetti, A.E., Ardigo, L.P., & Saibene, F. (1994). The transition between walking and running in humans: metabolic and mechanical aspects at different gradients. Acta Physiologica Scandanavia, 150, Nilsson, J., Thorstensson, A., & Halbertsma, J. (1985). Changes in leg movements and muscle activity with speed of locomotion and mode of progression in humans. Acta Physiologica Scandanavia, 123, Prilutsky, B.I., & Gregor, R.J. (2001). Swing- and supportrelated muscle actions differentially trigger human walk run and run walk transitions. Journal of Experimental Biology, 204, Raynor, A.J., Yi, C.J., Abernethy, B., & Jong, Q.J. (2002). Are transitions in human gait determined by mechanical, kinetic or energetic factors? Human Movement Science, 21, Rotstein, A., Inbar, O., Berginsky, T., & Meckel, Y. (2005). Preferred transition speed between walking and running: effects of training status. Medicine and Science in Sports and Exercise, 37, Rubin, C.T., & Lanyon, L.E. (1982). Limb mechanics as a function of speed and gait: A study of functional strains in the radius and tibia of horse and dog. Journal of Experimental Biology, 101, Schieb, D.A. (1986). Kinematic accommodation of novice treadmill runners. Research Quarterly for Exercise and Sport, 57, 1 7. Segers, V., Aerts, P., Lenoir, M., & De Clercq, D. (2006). Spatiotemporal characteristics of the walk-to-run and run-towalk transition when gradually changing speed. Gait & Posture, 24, Segers, V., Lenoir, M., Aerts, P., & Clercq, D.D. (2007). Influence of M. tibialis anterior fatigue on the walk-to-run and run-to-walk transition in non-steady state locomotion. Gait & Posture, 25, Swanson, S.C., & Caldwell, G.E. (2000). An integrated biomechanical analysis of high speed incline and level treadmill running. Medicine and Science in Sports and Exercise, 32, Thorstensson, A., & Roberthson, H. (1987). Adaptations to changing speed in human locomotion: Speed of transition between walking and running. Acta Physiologica Scandanavia, 131, Turvey, M.T., Holt, K.G., LaFiandra, M.E., & Fonseca, S.T. (1999). Can the transitions to and from running and the metabolic cost of running be determined from the kinetic energy of running? Journal of Motor Behavior, 31, Vilensky, J. A., Libii, J.N., & Moore, A.M. (1991). Trot gallop gait transitions in quadrupeds. Physiology & Behavior, 50, Wall, J.C., & Charteris, J. (1980). The process of habituation to treadmill walking at different velocities. Ergonomics, 23, Wells, R.P., & Winter, D.A. (1980). Assessment of signal and noise in the kinematics of normal, pathological, and sporting gaits. In Human locomotion I: Pathological gait to the elite athlete, pp Proceedings of the special conference of the Canadian Society for Biomechanics. London, Ontario.

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