INDIVIDUALS WITH STROKE, cerebral palsy, and acquired

123 ORIGINAL ARTICLE The Influence of Mechanically and Physiologically Imposed Stiff-Knee Gait Patterns on the Energy Cost of Walking Michael D. Lewek, PT, PhD, Abigail J. Osborn, BS, Clinton J. Wutzke, MS ABSTRACT. Lewek MD, Osborn AJ, Wutzke CJ. The influence of mechanically and physiologically imposed stiffknee gait patterns on the energy cost of walking. Arch Phys Med Rehabil 2012;93:123-8. Objective: To investigate the relative roles of mechanically imposed and physiologically imposed stiff-knee gait (SKG) patterns on energy cost. Design: Repeated-measures, within-subjects design. Setting: Research laboratory. Participants: Individuals (N 20) without musculoskeletal, neuromuscular, or cardiorespiratory limitations. Interventions: Participants walked on an instrumented treadmill at their self-selected overground gait speed for 3 randomly ordered conditions: (1) control, (2) mechanically imposed stiffknee gait (SKG-M) using a lockable knee brace, and (3) physiologically imposed stiff-knee gait (SKG-P) using electrical stimulation to the quadriceps. Each condition was performed with 0% and 20% body weight support. Indirect calorimetry determined net metabolic power, and motion capture measured lower extremity joint kinematics and kinetics. Main Outcome Measures: Net metabolic power, knee flexion angle, circumduction, hip hiking, and hip flexion and ankle plantarflexion moments. Results: Participants walked at 1.25.09m/s. Net metabolic power was significantly increased by 17% in SKG-M and 37% in SKG-P compared with control (mean increase:.66.60w/kg for SKG-M; 1.39.79W/kg for SKG-P; both P.001). Furthermore, SKG-P required greater net metabolic power than SKG-M (P.001). Simulated SKG was associated with increased circumduction and hip hiking. Despite no change in ankle plantarflexion moments (P.280), the hip flexion moment was increased during SKG-P (.43.15Nm/kg m) compared with control (.31.08Nm/kg m; P.001). Conclusions: The increase in energy cost associated with simulated SKG was due in part to abnormal mechanical compensations, and in part to an increase in quadriceps activity. Understanding the mechanisms underlying the increase in quadriceps activity will enable a reduction in the energy cost of walking with SKG. Key Words: Biomechanics; Gait; Oxygen consumption; Rehabilitation. 2012 by the American Congress of Rehabilitation Medicine INDIVIDUALS WITH STROKE, cerebral palsy, and acquired brain injury often exhibit deficits in hip, knee, and ankle flexion during swing. 1-3 This movement pattern, termed spastic paretic stiff knee gait pattern, is among the most common types of abnormal gait patterns, presenting in approximately 25% to 30% of individuals after stroke. 3,4 The presence of a stiff-knee gait (SKG) pattern is purported to require a greater energy cost, 5-7 with evidence from unimpaired subjects to support this contention. 8-10 If walking with SKG is energy inefficient, it would be prudent to determine the underlying cause of the increase in energy cost. The abnormal mechanics associated with SKG are often assumed to contribute to the greater energy cost. 11 For instance, with the knee extended, the swinging limb has a greater moment of inertia, 7,12 requiring greater hip moments that can increase energy cost. In addition, concomitant compensatory limb movements (eg, hip circumduction, hip hiking, lateral trunk lean, and contralateral vaulting) are commonly adopted to overcome the increased length of the swinging limb and reduce the risk of tripping. 13 That a contralateral shoe lift, intended to counteract these compensatory movements, reduces the energy cost associated with simulated SKG 8 provides evidence that abnormal mechanics may impact the energy cost during walking. The presence of abnormal compensatory movements requires additional hip or ankle muscle activity, or both, which can further elevate energy cost. More importantly, perhaps, from a muscle perspective is that the SKG pattern itself has been attributed to inappropriate muscle activity during late stance/early swing. 1,14-16 Inappropriate thigh (eg, quadriceps) and shank (eg, soleus) muscle activity during late stance is purported to reduce knee flexion velocity, subsequently limiting knee flexion during swing. 17 Inappropriate quadriceps activity is most commonly believed to cause SKG, 1,14-16 and thus may further elevate energy cost. Therefore, the elevated energy cost may be due to the presence of (1) abnormal compensatory limb mechanics (ie, mechanical cause) and/or (2) the under- From the Department of Allied Health Sciences, Division of Physical Therapy (Lewek, Osborn), and the Human Movement Science Program (Lewek, Wutzke), University of North Carolina, Chapel Hill, NC. Presented to the Gait and Clinical Movement Analysis Society, April 26-29, 2011, Bethesda, MD. Supported in part by the University of North Carolina s Division of Physical Therapy and the University of North Carolina Summer Undergraduate Research Fellowship program. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit on the authors or on any organization with which the authors are associated. Correspondence to Michael Lewek, PT, PhD, 3043 Bondurant Hall, CB#7135, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7135, e-mail: mlewek@med.unc.edu. Reprints are not available from the authors. 0003-9993/12/9301-00581$36.00/0 doi:10.1016/j.apmr.2011.08.019 ANOVA BWS GRF NMP SKG SKG-M SKG-P V CO2 V O2 List of Abbreviations analysis of variance body weight support ground reaction force net metabolic power stiff-knee gait mechanically imposed stiff-knee gait physiologically imposed stiff-knee gait carbon dioxide production oxygen consumption

124 ENERGY COST AND STIFF-KNEE GAIT, Lewek lying increase in knee extensor muscle activity (ie, physiologic cause). Reducing elevated energy costs during walking may be accomplished with the use of body weight support (BWS), which is used clinically to assist with locomotor training. 18,19 Greater amounts of BWS are known to reduce the energy costs associated with normal walking. 20,21 If BWS can reduce energy costs associated with SKG, then patients with SKG might have the ability to walk further, faster, or longer during training to enhance rehabilitation practice. The purpose of this study was to determine the influence of both mechanically imposed and physiologically imposed SKG patterns on energy cost. Based on previous work, 8-10 it was hypothesized that walking with a simulated SKG pattern would increase energy costs. Furthermore, we hypothesized that energy cost would be even greater if the simulated SKG pattern was imposed with an increase in quadriceps activity, compared with mechanically imposed, without an increase in quadriceps activity. In addition, we hypothesized that the use of BWS would reduce metabolic costs while walking both with and without simulated SKG. Finally, a determination of the compensations created in response to the simulated SKG patterns will provide guidance for treatment planning. METHODS Participants Twenty unimpaired individuals (10 males, 10 females; mean age SD, 21.7 1.4y; mean height SD, 1.74.10m; mean weight SD, 70.5 15.6kg; 19 right-leg dominant) were recruited to undergo testing. Participants were not included if they were pregnant, had a history of ligament deficiency, cardiovascular disease, neurologic impairment, impaired balance or history of unexplained falls, or other orthopedic problems in the lower extremities or spine. All subjects gave informed consent that was approved by the Human Subjects Review Board of UNC-Chapel Hill before participation. Data Collection All subjects underwent a single gait analysis to evaluate metabolic, limb kinematic, kinetic, and spatiotemporal measures. Subjects walked on a dual-belt treadmill a with two 6-component forceplates to collect ground reaction force (GRF) data. The treadmill speed was set individually for each subject to match the subject s self-selected overground gait speed, which was calculated as the average speed from 3 passes across a 14-ft pressure mat. b While walking on the treadmill, all participants wore a safety harness, c which did not restrict lower extremity movements. The harness was attached overhead to a custom-designed unweighting system (similar to that used in the study by Donelan and Kram 22 ). Each subject participated in 3 walking conditions (control, mechanically imposed SKG [SKG-M], and physiologically imposed SKG [SKG-P]), which were each performed at 2 BWS conditions (0%BWS and 20%BWS). These 6 trials were block randomized by walking condition, such that both randomly ordered BWS conditions were completed for a particular walking condition before performing the next randomly selected walking condition. SKG-M was achieved with an adjustable knee brace d placed on the dominant leg. The leg brace was worn for all trials: fixed at full extension for SKG-M, but left unlocked to allow unrestricted sagittal plane knee motion during the control and SKG-P conditions. A Grass S48 electrical stimulator e applied trains of electrical pulses (75 pulses/s, 400- s pulse duration, 33-pulse tetanic train) to the dominant quadriceps to achieve the SKG-P condition. Large pregelled, self-adhesive 3 5-inch electrodes f were applied superficial to the proximal vastus lateralis and the distal vastus medialis muscles. Voltage amplitude during walking was sufficient to fully extend the knee against gravity while sitting. During walking, the stimulation was applied during each step, beginning during late stance (ie, the peak of anteriorly directed GRF) and persisting for 400 to 450msec. During all trials, the rates of oxygen consumption (V O2 ; ml kg 1 min 1 ) and carbon dioxide production (V CO2 ) were collected with a portable metabolic cart. g Before each data collection, the system was calibrated using known concentrations of gas. In addition to the walking trials, all subjects began testing with 5 minutes of quiet standing without BWS to measure baseline energy cost. While walking, an 8-camera passive motion analysis system, h sampling at 120Hz, tracked 14-mm retroreflective markers attached to the lower extremities and pelvis. Bilaterally, markers were placed on the iliac crests, greater trochanters, lateral and medial femoral condyles, lateral and medial malleoli, dorsal surface of the foot (over the second metatarsal head), the posterior heel counters of the shoe, and the first and fifth metatarsal heads. Rigid thermoplastic shells were attached to the posterior pelvis (3 markers), and bilateral thighs and shanks posterolaterally (4 markers each). Each shell was attached firmly with elastic bandages to reduce movement between the bone and marker. Importantly, the shells on the dominant limb were placed under the knee brace to appropriately track the motion of the thigh and shank within the brace. After a static standing calibration to locate joint centers with respect to each segment coordinate system, all joint markers were removed. Metabolic data were collected continuously on a breath-bybreath basis as subjects walked on the treadmill for approximately 4 or 5 minutes, to achieve steady state. Once at metabolic steady state, subjects continued to walk for an additional 30 seconds, while kinematic and kinetic data were recorded. Steady state was determined visually during testing and later confirmed with techniques described previously. 23,24 Between conditions, subjects remained standing until metabolic rates returned to resting values. Data Management Measurements of V O2 and V CO2 were averaged over the 30 seconds that coincided with motion capture collection (ie, after 4 5 min of walking) and used to calculate metabolic power. 25 Net metabolic power (NMP) was determined by subtracting the baseline standing metabolic measures from the walking data and normalizing to body mass. Data analysis software (Vicon Nexus) h was used to identify the locations of the markers in the lab coordinate system. The markers defined a 7-segment kinematic model for tracking the 3-dimensional motion of the pelvis and lower limb segments. All segment coordinate systems were defined with the positive x-axis to the right, positive y-axis facing anteriorly, and positive z-axis pointing superiorly. Visual3D software i estimated segment properties from measured anthropometric values. 26 All segments were modeled as a frustra of right cones, except for the pelvis, which was modeled as a cylinder. Although kinematic and kinetic data were collected bilaterally, only data from the dominant side were analyzed. Marker trajectory and GRF data were filtered with 6- and 20-Hz low pass filters, respectively. Joint angles were calculated using Euler angles. Sagittal plane internal joint moments were calculated using an inverse dynamics approach and normalized to body mass and height. Limb circumduction was defined as the peak lateral excursion of the foot during swing relative to the

ENERGY COST AND STIFF-KNEE GAIT, Lewek 125 Fig 2. NMP for control, SKG-M, and SKG-P conditions. Data from no BWS conditions are in white, and the 20%BWS condition is in black. Data represent means and SDs. Fig 1. Knee flexion angles throughout the gait cycle for control (thick red line), SKG-M (thin blue line), and SKG-P (dashed green line) for the 0%BWS condition. The gray shaded portion around the control data represents 1 SD. foot position during the previous stance phase. Stance time was calculated as the time that the vertical GRF exceeded 20N. Step length was calculated as the anterior-posterior distance between the feet at heel strike for the dominant foot. 27,28 Stance time and step length asymmetries were calculated as the ratio of the dominant limb to the nondominant limb, and inverted if necessary, to ensure all values were 1.0 or greater. 29 For all variables, outcome measures were calculated for each step using custom written LabVIEW software j and then averaged for each condition. Data Analysis Within-subject statistical analyses were performed with SPSS. k Separate 2-way, repeated-measures analyses of variances (ANOVAs) (repeated for condition and BWS) were performed for each outcome variable (peak knee flexion, NMP, circumduction, hip hiking, stance time and step length asymmetries, and the peak hip flexion and ankle plantarflexion moments). To account for multiple comparisons, the level to determine statistical significance of main and interaction effects was reduced to.006 (.05/8). All post hoc testing was performed with Bonferroni corrected, paired t tests with equal to.05. Linear regression analysis was used to determine the relationship between joint kinetics and energy cost. RESULTS Subjects walked at 1.25.09m/s (range, 1.10 1.50m/s) on the treadmill for testing. Swing phase knee flexion was significantly altered by the brace (SKG-M) and electrical stimulation protocol (SKG-P) (fig 1). Specifically, subjects flexed their knee to 64.8 4.4 during control walking, whereas only 26.7 6.1 was achieved during SKG-M (t test, P.001) and 29.7 10.5 during SKG-P (t test, P.001). No difference in swing phase knee flexion was observed between SKG-M and SKG-P (t test, P.349). Both the SKG-M (1.06.04; P.001) and SKG-P (1.06.04; P.001) conditions produced significantly greater stance time asymmetry compared with the control condition (1.02.03). Stance time asymmetry during SKG-M and SKG-P was attributed to decreased stance time on the dominant (eg, simulated stiff-knee) limb compared with the nondominant limb. No change in step length asymmetry was noted, however (ANOVA, P.760; control, 1.04.02; SKG-M, 1.05.04; SKG-P, 1.05.04). Metabolic Data NMP was significantly different between walking conditions (ANOVA, P.001) (table 1, fig 2). Specifically, NMP was greater during both SKG-M (17% increase) and SKG-P (37% increase) compared with the control condition (mean increase:.66.60w/kg for SKG-M; 1.39.79W/kg for SKG-P; t test, both P.001), and SKG-P required greater NMP than SKG-M (t test, P.001). No main effect of BWS was observed (ANOVA, P.319), and no interaction effect existed Table 1: Kinematic and Kinetic Compensations to SKG Pattern Control SKG-M SKG-P Main Effect: Condition Main Effect: BWS Interaction Effect Variable 0%BWS 20%BWS 0%BWS 20%BWS 0%BWS 20%BWS P P P NMP (W/kg) 3.8 0.5 3.8 0.6 4.5 0.8 4.4 0.8 5.2 1.2 5.2 1.2.001*.319.403 Hip hiking (deg) 0.4 2.3 0.3 1.9 3.9 2.7 3.5 2.5 4.3 3.2 3.9 2.8.001*.747.025 Circumduction (cm) 2.4 0.8 2.0 0.8 3.1 2.0 2.8 1.4 4.0 1.9 3.8 2.0.001*.049.867 Peak PF moment (Nm/kg m) 0.91 0.11 0.83 0.10 0.91 0.10 0.81 0.10 0.91 0.11 0.81 0.10.280.001*.135 Peak hip flexion moment (Nm/kg m) 0.32 0.08 0.29 0.07 0.36 0.07 0.33 0.08 0.46 0.14 0.41 0.15.001*.001*.432 NOTE. Values are mean SD unless otherwise indicated. Abbreviation: PF, plantarflexion. *Indicates significant P values.

126 ENERGY COST AND STIFF-KNEE GAIT, Lewek (ANOVA, P.403). The difference in NMP between control and SKG-M conditions (ie, energy cost resulting from mechanical compensations) represented 50% of the difference in NMP between the control and SKG-P conditions (ie, energy cost resulting from mechanical compensations and quadriceps overactivity). Kinematic Compensations A significant main effect for condition was observed for circumduction (ANOVA, P.001). Limb circumduction was significantly greater during SKG-P (3.9 1.9cm) compared with both control (2.2 0.8cm; t test, P.002) and SKG-M (2.9 1.7cm; t test, P.009) conditions. The use of BWS appeared to reduce limb circumduction from 3.2 1.5cm to 2.9 1.5cm across all conditions, although this change was not statistically significant (ANOVA, P.049). No interaction between BWS and condition was observed (ANOVA, P.867). Furthermore, the extent of hip hiking was significantly different between conditions (ANOVA, P.001). Specifically, we observed significantly greater hip hiking in the SKG-M (3.7 2.6 ) and SKG-P (4.1 3.0 ) compared with the control condition (0.1 2.1 ; t test, both P.001). Joint Kinetics The use of BWS significantly reduced the peak plantarflexor moment (0%BWS,.91.11Nm/kg m; 20%BWS,.82.10Nm/kg m) and hip flexion moment (0%BWS,.38.12Nm/kg m; 20%BWS,.35.12Nm/kg m) (ANOVA, both P.001). Whereas the peak ankle plantarflexion moment was unaffected by condition (ANOVA, P.280), the peak hip flexion moment was increased during SKG-P, compared with the control (t test, P.003) and SKG-M (t test, P.016) conditions (see table 1). The hip flexion moment explained 33% of the variance of the NMP across the 0%BWS conditions (R 2.334, P.001) (fig 3). Fig 3. Relationship between peak hip flexion moment during preswing and NMP is displayed for the no BWS control (red squares), SKG-M (green triangles), and SKG-P (blue circles) conditions. DISCUSSION These data confirm our hypothesis that simulated SKG has a greater energy cost than control walking, and extends the work of others 8-10 by demonstrating that approximately half of the increased energy cost arises from the abnormal mechanics (SKG-M), with the remaining increase in energy cost attributable to a combination of abnormal quadriceps activity during the late stance/early swing phase of gait and abnormal mechanics (SKG-P). The compensatory movements in our intact subjects are consistent with the compensations commonly observed in a neurologically impaired population, 13 suggesting that these movement patterns are not due to neural constraints, but rather biomechanical constraints. The increased energy costs associated with simulated SKG appeared to be due, in part, to increased hip flexor moments during preswing. The necessary increase in joint moments from less efficient musculature is well known to increase energy costs. 30 Interestingly, the more efficient ankle plantarflexors did not alter their moment production during push-off, presumably because the brace or stimulation limited their ability to adequately propel the tibia. While we acknowledge that the underlying cause of SKG remains unknown, most authors attribute the loss of knee flexion to inappropriate quadriceps activity. 1,14-16,31 Inappropriate activation of the rectus femoris, in particular, is the most frequently cited cause for SKG, and thus is most often targeted for correction. Surgical correction via a rectus femoris transfer is common in children with cerebral palsy, and while outcomes are variable, can increase swing phase knee flexion by up to 10 to 25. 32,33 Likewise Botox injections or a block to the motor branch of the rectus femoris have been shown to increase swing phase knee flexion by approximately 5 to 10. 34-36 Because such approaches do not typically restore full swing phase knee flexion, we believe that the rectus femoris is not the only muscle contributing to SKG. 1,16,32 Our approach to mimicking SKG was therefore to stimulate the entire quadriceps, rather than selectively isolating the rectus femoris. 15 While we recognize that this is a potential limitation, our approach is consistent with work that supports inappropriate vasti activation in individuals poststroke. 1,14,37,38 Regardless of the underlying mechanism for SKG, it is interesting to note that the compensations observed (ie, hip hiking, circumduction) in our intact individuals are strikingly similar to those of individuals with neurological disorders. 13,39 Thus the compensations observed in individuals with an upper motor neuron lesion appear to be a direct response to the increased limb length during swing (ie, altered mechanical environment), 13,39 and should not be viewed as a result of an altered neural template (ie, consequence of the lesion). This suggests that rehabilitation directed at remediating compensatory movements alone will be ineffective, but rather treatments that address the underlying cause (eg, inappropriate quadriceps activity) must be developed. That reductions in limb length during swing cause a concomitant reduction in compensatory movements in individuals poststroke 39 suggests that an approach which targets the cause of the altered mechanical environment will have success at altering movement patterns (see, however, Sulzer et al 40 ). Unfortunately, treatments that only address the mechanical compensations (eg, contralateral shoe lifts) do not completely restore energy cost. 8 In order for energy costs associated with SKG to be reduced, the underlying muscular cause of the diminished knee flexion must also be addressed. The changes in energy cost from our subjects with simulated SKG are consistent with others who have used limb immobilizers (20% 23% increase) 8,9 to simulate SKG. Unfortunately, previous work in this area has used plaster casts 10 or braces 8,9 without documentation of true limitations in knee flexion. We were able to place markers directly on the limb to measure limb motion within the brace, confirming that subjects continued to obtain some flexion of the dominant knee within the brace (SKG-M) and despite the electrical stimulation (SKG-P). Notably, the resulting flexion yielded similar knee excursions among the SKG-M and SKG-P conditions, and appeared re-

ENERGY COST AND STIFF-KNEE GAIT, Lewek 127 markably similar to patterns observed in individuals with upper motor neuron lesions. Although the swing phase knee kinematics in the SKG-P and SKG-M conditions matched those produced by individuals with upper motor neuron lesions, the stance phase kinematics appeared qualitatively normal. In contrast, it is common to observe excessive knee flexion (ie, crouch gait) or extension (ie, genu recurvatum) during stance after upper motor neuron damage. 2-4,6 Such stance phase knee abnormalities can also increase mechanical work cost 41 and metabolic demands. 11 Because of the potential for stance phase knee abnormalities to increase metabolic cost, it is important that our simulated SKG patterns only altered swing phase kinematics. Our approach, therefore, provides clear evidence of the role of swing phase SKG, without confounding stance phase abnormalities, on metabolic cost and the concomitant compensations. We had hypothesized that 20%BWS would be sufficient to reduce the energy cost of walking for simulated SKG. Given the robust changes to joint kinetics with BWS, we were confident that the BWS system worked correctly. We were surprised, therefore, that the inclusion of BWS did not alter energy cost. Prior work, however, demonstrates that energy costs do not decrease in direct proportion to the amount of BWS provided, suggesting that 20%BWS was not enough to alter energy costs. 42 An examination of previous work supports this contention, as 20% to 25%BWS has previously failed to reduce NMP. 20,21,42 We suspect that a decrease in NMP would have occurred if we had used increased BWS, although future work is needed to confirm this. We can further speculate that BWS failed to alter energy cost associated with simulated SKG because the movement compensations occur primarily during swing. The use of BWS is believed to have its greatest effect on stance phase gait abnormalities. 42 Once the limb is off the ground for swing, there is little that BWS can do to make the movement easier. 43 Because the compensatory movements involved with SKG (circumduction and hip hiking) occur during the swing phase of gait, it is reasonable that BWS did not alter energy costs in our subjects. Study Limitations A potential limitation of this work is that we did not obtain usable electromyographic data during the collection. While we attempted to record electromyographic data, the SKG-P trials were unusable because of the electrical stimulation artifact, while the remaining trials also yielded unusable data, presumably because of motion artifact from the brace rubbing on the electrodes. As a result, we are unable to confirm that the quadriceps were quiescent during preswing of the SKG-M condition compared with control. These data would have helped us to ensure that the quadriceps muscles were no more active in the SKG-M condition than the control condition to ensure that changes in NMP were due solely to compensations and not to increased quadriceps activity. CONCLUSIONS In summary, we observed that the increase in energy cost associated with simulated SKG is due in part to the abnormal mechanical compensations, and in part to an increase in quadriceps muscle activity. The use of 20%BWS did not alter the energy cost associated with simulated SKG. Understanding the mechanisms underlying the increase in knee extension activity for remediation will enable a reduction in the energy cost of walking associated with SKG. References 1. Kerrigan DC, Gronley J, Perry J. Stiff-legged gait in spastic paresis. A study of quadriceps and hamstrings muscle activity. Am J Phys Med Rehabil 1991;70:294-300. 2. Wren TA, Rethlefsen S, Kay RM. 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