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Research Reports |
CM Said, BAppSci (Physio), PhD, is Senior Physiotherapist, Physiotherapy Department, Allied Health Treatment Centre, Level 3, Flanders Wing, Heidelberg Repatriation Hospital, Austin Health, PO Box 5444, Heidelberg West, 3084 Victoria, Australia (Cathy.Said{at}austin.org.au)
PA Goldie, BAppSci (Physio), MAppSci, PhD, is Adjunct Associate Professor, School of Physiotherapy, La Trobe University, Bundoora, Victoria, Australia
E Culham, Dip PT/OT, MClinSci (Physio), PhD, is Associate Professor and Chair, School of Rehabilitation Therapy, Queens University, Kingston, Ontario, Canada
WA Sparrow, PhD, is Senior Lecturer, School of Health Sciences, Deakin University, Burwood, Victoria, Australia
AE Patla, BTech (Hons), MScEng, PhD, is Professor, Department of Kinesiology, University of Waterloo, Waterloo, Ontario, Canada
ME Morris, PT, PhD, FACP, is Professor and Head of School of Physiotherapy, La Trobe University
Address all correspondence to Dr Said
Submitted April 28, 2004;
Accepted November 23, 2004
 | Abstract |
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Key Words: Biomechanics • Cerebrovascular accident • Gait disorders: neurologic
| Introduction |
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 TopAbstract Introduction MethodResultsDiscussionConclusionReferences |
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Obstacle crossing has 3 phases: approach to the obstacle, obstacle crossing, and landing after the obstacle. Lead- and trail-limb trajectories during each of these phases can be measured using spatial and temporal variables. Limb placement before the obstacle provides insight into modifications during the approach phase.5–8 Lead- and trail-limb obstacle clearance are examined during the crossing phase because inadequate clearance may lead to a trip and subsequent fall. Placement of the limb after the obstacle also is crucial because poor limb placement may increase the risk of contact with the obstacle. Temporal variables provide information about the time required to modify limb trajectories. Pre-obstacle swing time, from toe-off to obstacle clearance, provides insight into the time required to prepare the limb for clearance. Post-obstacle swing time, from obstacle clearance to foot contact, provides information about the time required to prepare the limb for landing. Consideration of spatial and temporal variables from each of these phases is required to fully describe obstacle clearance.
Analysis of lower-limb joint angles provides further insight into this complex task. For example, lead-limb clearance over an obstacle in subjects without stroke is achieved by a combination of swing-limb flexion and "hip hiking" on the stance limb.9 Swing-limb hip flexion and abduction, knee flexion, and ankle dorsiflexion describe the swing limb's contribution to lead-limb clearance.7,9–12 The contribution of the stance (trail) limb to clearance can be evaluated by examining pelvic obliquity and stance hip height, which can be further explored by examining stance-limb hip, knee, and ankle angles. Examination of kinematic variables before, during, and after obstacle crossing in both the stance and swing limbs, therefore, provides information about the control of lead- and trail-limb trajectory following stroke.
Because stroke is frequently a unilateral disorder, we predicted that the limb with which subjects first stepped over the obstacle would influence limb trajectory during obstacle crossing. The current study aimed to maximize chances that subjects with stroke would lead with both the affected and unaffected limbs (in different trials). This allowed the movement patterns of the affected and unaffected limbs to be compared with performance of people without stroke.
Reduced gait speed following stroke also may influence limb control during obstacle crossing. The relationship between the spatial and temporal characteristics of obstacle crossing and walking speed during obstacle crossing has not been explored. Given the established relationship between spatial and temporal variables and gait speed,13,14 we expected that reduced speed would alter limb placement before and after the obstacle (Fig. 1). To determine the impact of slower gait speed on obstacle crossing, subjects with stroke were compared with subjects without stroke walking at both a self-selected speed and at a speed matched to that of the subjects with stroke. We predicted that fewer differences in the movement patterns would be detected when walking speed was matched between groups.
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| Method |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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Apparatus
A 6-camera Vicon 512 3-dimensional motion analysis system* and a Kistler forceplate (Performance System 9281B
), positioned in the middle of the walkway, were used to obtain kinematic and kinetic data. Only kinematic data will be reported. The mean error using the Vicon system has been estimated to be less than 1 mm.15
Two red balsa wood obstacles measuring 4 cm x 1.5 mm thick x 60 cm long were used for data collection. One obstacle was positioned after the forceplate, approximately 5 m from the start of the walkway. A "4-cm-high" obstacle was created by securing the obstacle vertically to the floor with a small amount of adhesive gum; a "4-cm-wide" obstacle was created by placing the obstacle flat on the ground perpendicular to the path of progression. The second obstacle was used for demonstration. Subjects wore a lightweight safety belt around the waist and were accompanied by a physical therapist.
Twenty-one 2.5-cm reflective markers identified various landmarks on the subject and the obstacle. The 2 thigh and 2 tibia markers were on short "wands" to enhance visibility. A triangular device with 3 markers positioned on it and a known endpoint was used to identify the sole of the shoe. Two knee alignment devices (KADs) were required during the static trials to identify the flexion-extension axis of the knee. BodyBuilder Version 3.5* and Vicon Clinical Manager Version 1.37 (VCM)* software packages were used to process the data. Additional equipment required for clinical tests to provide descriptive data about subjects included a stopwatch, a 14-m walkway, a flight of 4 steps, and a small beanbag.16–18
Procedure
Informed consent was obtained from all subjects. To provide descriptive information about the subjects with stroke, data such as the lesion site, Functional Independence Measure (FIM) score,18 unobstructed gait speed, score on the walk section of the Motor Assessment Scale (MAS),16 and sensory loss or neglect were collected by the primary investigator (CMS).19 The presence of spatial neglect, perceptual disorders, or cognitive deficits were obtained from neuropsychology reports, in conjunction with written notes from treating therapists. Results are presented in Table 1.
An orthoptist examined all subjects for visual acuity, field defects, diplopia, and any other visual deficits. Two subjects with stroke (subjects 7 and 10) had reduced acuity in one eye, but were included because all subjects had corrected binocular visual acuity greater than 20/40).
Subjects wore loose-fitting shorts, their own walking shoes, and any prescription eyewear usually worn during ambulation. Anthropometric measurements were obtained as outlined in the VCM manual to calculate hip, knee, and ankle joint locations.20,21 Reflective markers were attached using double-sided adhesive tape. Lower-limb markers were placed as described in the VCM manual. Additional markers were placed on the fifth proximal phalanx on the right and left feet to allow the most distal point of the toe of the shoe to be identified. Markers also were placed on the right and left acromions to identify the position of the trunk. Two markers were placed on either end of the obstacle.
A static trial was performed prior to data collection to provide a reference point for markers. Briefly, 2 to 3 seconds of data were collected with subjects standing in a stationary position. For this trial, only the knee markers were replaced with the KADs. A second static trial identified the edges of the shoes. A triangular device with a known endpoint was used to identify the most distal point of the toe, the edge of the heel, and the widest medial and lateral points of the shoe. BodyBuilder software used this information to create a virtual marker at each point, identifying the edges of the shoe.
Subjects performed 4 unobstructed trials walking at a comfortable speed to familiarize themselves with the experimental setting. They then performed 8 trials on each of 2 obstacle conditions: 4 cm high and 4 cm wide. This procedure provided sufficient trials on each condition to maximize the chances of subjects leading with both limbs, while limiting fatigue. Order of obstacle presentation was counterbalanced and randomly allocated. Following a minimum 10-minute rest, subjects without stroke repeated the test at a speed matched to that of the person with stroke to whom they were matched. The unobstructed trials provided practice. Other than being asked to walk slower, subjects without stroke were provided no additional instructions regarding obstacle crossing. Subjects with stroke performed a maximum number of 20 trials. Subjects without stroke performed a total of 40 trials: 20 at a self-selected speed and 20 at the speed of the person with stroke.
Subjects were instructed to walk at a comfortable speed and step over the obstacle without contacting it or overbalancing. Prior to the trials, subjects inspected the demonstration obstacle visually and manually. The therapist demonstrated one walk with the obstacle in place. Subjects were reminded to perform the task within their limits of safety and to stop if they felt at risk. A therapist walked to the side and slightly behind the subject and held the safety belt lightly to provide assistance, if required. Subjects received a minimum of 1 minute of rest between trials and a minimum of 10 minutes of rest after the unobstructed gait trials and after the first series of obstructed trials. To maximize chances of obtaining data for both the affected and unaffected lead limbs, subjects were instructed to alternate the limb with which they commenced walking.
Data Processing
Data were reconstructed and labeled in the Vicon 512 workstation. The first trial in each condition with adequate data (minimal marker loss during the strides of interest and a clean forceplate strike, if available) was selected for further processing.
Data were filtered using a 3-point weighted average procedure provided by the BodyBuilder software. Virtual markers were created at the most distal point of the toe and heel and at the most medial and lateral points of the foot, using the data obtained from the static trial. The VCM software was used to obtain lower-limb kinematic data. Hip joint centers were calculated using the model developed by Davis et al.20 Data from both BodyBuilder and VCM software were exported to Microsoft Excel
for data reduction.
Dependent Variables
Measurements of lead- and trail-limb pre-obstacle distance, toe clearance, and post-obstacle distance were obtained as illustrated in Figure 1. Measurements of foot contact and toe-off were obtained, using BodyBuilder software, by visually inspecting the position of the virtual markers on the heel and the toe. Pre-obstacle swing time (from toe-off to toe clearance) and post-obstacle swing time (from toe clearance to foot contact) were calculated for the lead and trail limbs. BodyBuilder software was used to calculate horizontal foot-contact velocity and the angle of the foot with respect to the floor at foot contact.
Measurements of hip flexion, hip abduction, knee flexion, and ankle dorsiflexion on the lead and trail limbs were obtained using VCM software. Measurements of pelvic obliquity, pelvic rotation, and pelvic tilt also were obtained. Average crossing gait speed was calculated by averaging the speed for the lead and trail crossing strides. The height of the stance-limb hip joint was measured as an indication of the stance-limb contribution to swing-limb elevation.
Data Analysis
The majority of data did not differ significantly from a normal distribution (P>.05), as determined by the Shapiro-Wilks test22; therefore, parametric analysis was used. Independent t tests were used to determine whether gait speed differed between subjects with stroke and subjects without stroke. Because groups were matched for age, sex, and height, they were treated as related samples for all other comparisons.23
The primary purpose of the study was to document differences between the movement patterns used by subjects with stroke and subjects without stroke, so a limited number of planned comparisons were performed.24 Subjects without stroke were assigned an "affected" limb and an "unaffected" limb, in accordance with the matched subject with stroke. Comparisons between groups at self-selected speed then were made separately for the affected and unaffected limbs. Based on the previous study,2 directional hypotheses for lead-limb post-obstacle distance, lead-limb toe clearance, and trail-limb pre-obstacle distance between groups were analyzed using one-tailed matched-pairs t tests. No data supported directional hypotheses for lead-limb pre-obstacle distance, trail-limb clearance, trail-limb post-obstacle distance, or lead- or trail-limb pre-obstacle or post-obstacle swing time. Two-tailed matched-pairs t tests were used for these variables. Data obtained for the affected and unaffected limbs of the subjects with stroke were then compared with data from subjects without stroke at matched speed using 2-tailed matched-pairs t tests for all comparisons.
Interpretation of results required an approach that balanced the risk of type I and type II errors. To reduce the risk of a type I error, a Bonferroni correction was used to correct for the 4 comparisons for each variable, resulting in a significance level of .0125. This increased the risk of type II error, which is of concern, given the novelty of this research area. To reduce risk of type II errors, results between the corrected and uncorrected significance levels were interpreted as "suggestive of significance, but not definitive,"25(p7) thereby identifying areas that may require future investigation.24
Lower-limb kinematic data were examined visually to provide insight into the way in which movements were performed. Due to the small numbers of subjects and the large number of potential comparisons, these data were not analyzed statistically.
To determine whether the contribution of the stance limb to clearance differed between the groups, the height of the stance-limb hip joint was compared between groups using a repeated-measures analysis of covariance.26 Because we expected that hip joint height varied with leg length, the difference in leg length between groups was used as a covariate.
| Results |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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As predicted, self-selected gait speed was reduced following stroke (Tab. 2) compared with subjects without stroke (P<.01). No differences in gait speed were detected between groups when subjects without stroke walked at a speed matched to that of the subjects with stroke (P>.05).
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Lead-Limb Contact After the Obstacle
Figure 4 illustrates that lead-limb post-obstacle distance was reduced for both limbs following stroke compared with subjects without stroke walking at self-selected speed (affected limb: t(11)=3.79, P=.003; unaffected limb: t(10)=6.89, P=.000). Unaffected lead-limb post-obstacle distance approached a significant reduction when compared at matched speed (t(10)=2.96, P=.014).
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Inspection of lead-limb joint angles at foot contact suggested that movement patterns used by the 2 groups were similar. Three variables appeared to differ between the groups, as illustrated in Figure 5. There was a trend for subjects with stroke to have greater knee flexion at foot contact in both the affected and unaffected limbs. Compared with subjects without stroke at matched speed, subjects with stroke appeared to have a pelvis that was tilted more anteriorly, particularly as the unaffected limb contacted the ground. The hip also appeared more flexed in subjects with stroke at matched speed.
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Trail-Limb Obstacle Clearance
Toe clearance in the affected trail limb, illustrated in Figure 6, was reduced compared with that of subjects without stroke walking at self-selected speed (t(10)=3.17, P=.010). No differences between groups were detected as the unaffected trail-limb toe cleared the obstacle (P>.05).
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Trail-Limb Foot Contact After the Obstacle
As demonstrated in Figure 7, trail-limb post-obstacle distance following stroke was reduced in the affected and unaffected limbs compared with subjects without stroke walking at both speeds (affected-limb at self-selected speed: t(10)=5.69, P=.000; unaffected limb at self-selected speed: t(11)=5.77, P=.000; affected limb at matched speed: t(10)=3.15, P=.010; unaffected limb at matched speed: t(11)=3.03, P=.011). The reduction in trail-limb post-obstacle distance was not solely due to reduced lead-limb post-obstacle distance because trail-limb step length also was decreased (affected limb at self-selected speed: t(10)=4.32, P=.002; unaffected limb at self-selected speed: t(11)=6.00, P=.000; affected limb at matched speed: t(10)=2.39, P=.038; unaffected limb at matched speed: t(11)=3.46, P=.005).
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Inspection of lower-limb kinematics suggested that subjects with stroke appeared more flexed on the affected and unaffected trail-limb knees at foot contact, as illustrated in Figure 7. Subjects with stroke were more anteriorly tilted at the pelvis, particularly as the unaffected trail limb contacted the ground. No other differences between groups were observed.
Temporal Variables
As illustrated in Figure 8, unaffected lead-limb pre-obstacle and post-obstacle swing time were not altered following stroke. Affected lead-limb pre-obstacle swing time also was not altered. Post-obstacle swing time on the affected lead limb, however, was increased in subjects with stroke compared with subjects without stroke at self-selected speed (t(11)=4.88, P=.000), and there was a trend for an increased post-obstacle swing time when compared at matched speed (t(11)=2.74, P=.019).
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| Discussion |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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Adaptive Modifications to the Movement Pattern of Subjects With Stroke During Obstacle Crossing
Some modifications to the movement patterns of the subjects with stroke may have increased safety during obstacle crossing. Subjects with stroke placed the lead limb closer to the obstacle before crossing, but did not modify trail-limb pre-obstacle placement. Chou and Draganich6,7 demonstrated that if the trail limb was positioned too close to the obstacle, trail-limb clearance was reduced and moments of force around the trail ankle during stance increased. This strategy may be difficult to control following stroke. Placing the lead limb closer to the obstacle may have contributed to safe obstacle crossing following stroke by assisting with more optimal placement of the trail limb in front the obstacle.
Modifications during landing also may have increased safety of obstacle crossing. Unaffected-limb foot-contact velocity was reduced and the angle between the foot and floor was reduced on both lead and trail limbs, compared with subjects without stroke walking at self-selected speed. These modifications could enhance safety by reducing the risk of a slip on landing.
Lead-limb clearance, however, was not modified to increase safety following stroke. This finding differs from reported results in the previous study,2 in which subjects with stroke tended to have increased lead-limb clearance. The lead (swing)-limb movement patterns in the subjects with stroke in the current study were remarkably similar to the patterns used by subjects without stroke. Figure 3 illustrates, however, that subjects with stroke were more flexed in the stance limb, although the vertical height of the hip joint was not altered. Similar patterns were observed in both the affected and unaffected stance limbs. Therefore, it does not appear that the pattern can be completely attributed to the unilateral sequelae of a stroke, such as loss of muscle force or sensory disturbance. Post hoc analysis of the lower-limb kinematics during unobstructed gait confirmed a trend for subjects with stroke to be more flexed at the hip and knee during affected- and unaffected-limb stance compared with subjects without stroke. This finding suggests that people with stroke may generally adopt a more flexed posture in the stance phase during walking. We hypothesize that stance-limb flexion may have assisted in balance control. Further examination of the balance-control mechanisms during obstacle crossing is warranted.
Some temporal modifications also may have enhanced safety following stroke. Subjects with stroke increased affected lead-limb post-obstacle swing time compared with subjects without stroke walking at both self-selected and matched speeds. The increased swing time might provide more time to modify placement of the affected leading limb after the obstacle. Control of the affected limb during the landing phase appears to be impaired.
Maladaptive Modifications to the Movement Pattern of Subjects With Stroke During Obstacle Crossing
Safety during obstacle crossing following stroke was compromised by the reduction in post-obstacle distance of the affected and unaffected lead limbs (Fig. 4). Placing the limb closer to the obstacle at landing places a person at risk of actual contact with the obstacle on landing. This behavior was seen in this study and in the previous experiment.2,3 This was only partly related to reduced speed following stroke. Increased stance (trail)-limb flexion, which effectively "shortens" the trail limb, combined with increased lead-limb knee flexion at foot contact, which reduces the "reach" of the lead limb may account for some of the reduction in post-obstacle distance.
Safety also may be compromised by the reduction in toe clearance when the affected limb trails the unaffected limb. This pattern may place subjects with stroke at increased risk for a trip, although no subject in this study contacted the obstacle with the trail limb. There was a trend for affected-limb knee flexion to be reduced following stroke, which could result in reduced clearance. Further examination of knee flexion in a larger sample and examination of lower-limb kinetics may be useful in determining whether the reduction in toe clearance was due to reduced or altered power generation following stroke.
Clinical Implications and Future Directions
The results of our study, we believe, have important clinical implications for physical therapists. The findings of this study and the previous study2,3 highlight that obstacle crossing is abnormal for many people with stroke, whether they lead with the affected limb or the unaffected limb. Difficulty with obstacle crossing may contribute to increased risk for falls following stroke. The results highlight the importance of considering gait speed when analyzing movement disorders. Understanding movement deficits also may provide the basis for training to improve obstacle crossing following stroke. For example, the results indicate that physical therapists do not need to retrain lead-limb clearance following stroke, but lead-limb placement and affected trail-limb clearance may need attention. This study provides a scientific basis for future clinical investigations.
This study is the first to document affected and unaffected lower-limb kinematics during lead- and trail-limb obstacle clearance following stroke; however, there are limitations. Only a small number of subjects were recruited, and all subjects were able to ambulate without physical assistance or a gait aid. The results, therefore, can be generalized only to this population. The findings are pertinent, however, because this group is most likely to return to community ambulation. The sample was heterogeneous in nature, including 2 subjects with sensory loss, 2 subjects with spatial or sensory neglect, and 2 subjects with visual field deficits. Because this was a preliminary study, we decided to include all subjects with stroke, irrespective of impairments. Future studies with larger subject samples would allow further analysis of various impairments, to provide further insight into the impact of specific deficits on obstacle crossing.
| Conclusion |
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TopAbstractIntroductionMethodResultsDiscussionConclusionReferences |
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| Footnotes |
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The institutional ethics committees of Austin Health and La Trobe University approved the testing procedure.
This research, in part, was presented at the Conference for the International Society for Postural and Gait Research; March 23–27, 2003; Sydney, New South Wales, Australia, and at the First National Neurology Conference of the Australian Physiotherapy Association; November 2003; Sydney, New South Wales, Australia.
* Oxford Metrics Ltd, 14 Minns Estate, West Way, Oxford, OX2OJB, United Kingdom. 
Kistler Instrumente AG, Eulachstrasse 22, Postfach, CH-8408 Winterthur, Switzerland.
Microsoft Corporation, One Microsoft Way, Redmond, WA 98052-6399.
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