Difficulties with walking can severely affect many activities essential to daily life. In recent years, there has been a surge in research on rehabilitation approaches to improve walking in people who have experienced a neurological insult such as stroke. Effective rehabilitation strategies to promote the recovery of walking are those that provide explicit practice of gait and are based on the principles of the neural control of walking and the capacity for the nervous system to reorganize itself after injury.1
Treadmill-based locomotor training is based on the premise that locomotor output from spinal centers and residual descending pathways can be enhanced by appropriate sensory cues during movement. Body weight may be partially supported by an overhead harness, whereas stepping is facilitated by the movement of the treadmill belt. Leg movements are assisted by therapists, and, if necessary, the amount of body weight support is adjusted so that the person bears as much body weight as possible without compromising posture.2 This loading of the legs during stance is a potent sensory signal to the nervous system, and the cyclic loading and unloading of the legs through the gait cycle is believed to be a key component to the success of gait retraining.3 During the stance (support) phase of walking, the leg extensor muscles must work against gravity to help maintain the body’s upright posture. It has been demonstrated that sensory input related to the amount of load experienced by the extensor muscles strongly influences the activity of these muscles during the stance phase of human walking.4 In this way, treadmill-based locomotor training can target appropriate activation of leg extensor muscle activity by maximizing weight-bearing and ensuring proper posture and limb kinematics through the stance phase.
Although recovery of walking is possible after stroke, deficits such as decreased hip, knee, and/or ankle flexion during the swing phase remain.5 Individuals after stroke have also reported or demonstrated difficulties in more complex walking tasks that require adequate leg flexion and foot clearance during the swing phase, such as climbing stairs6 or obstacle crossing.7,8 Mechanical supports such as ankle-foot orthoses9,10 or functional electrical stimulation (FES) systems have been developed to facilitate foot clearance during the swing phase for people with neurological injuries.11–13 Indeed, there has been much research on the use of FES of the common peroneal nerve to enhance ankle dorsiflexion and foot clearance during the swing phase of walking.14,15 Studies that have combined treadmill-based locomotor training with FES indicate positive effects for individuals with neurological gait disorders. Lindquist et al16 reported that gait speed and symmetry improved after combined FES and body weight-supported treadmill training in chronic stroke. Benefits of FES combined with body weight-supported treadmill training on walking speed and other gait characteristics have also been shown in individuals with incomplete spinal cord injury.17–19 Others have shown that FES combined with physiotherapy during subacute stroke rehabilitation yields better outcomes in overground walking speed compared with therapy without FES.20,21
Although the use of FES as an adjunct to gait rehabilitation is promising, there are some disadvantages of FES that may make it inappropriate for some individuals with stroke. These include pain because of the high levels of electrical stimulation required and difficulties with electrode placement11,22,23 or habituation of flexion reflexes.24,25 To date, there has been little exploration of alternatives to the use of external devices (ie, electrical stimulation or braces) during gait training to enhance the recovery of leg movements during the swing phase of walking. One alternative approach could be to load the flexor muscles during the swing phase. Loading, or resisting, limb flexion during the swing phase has previously been shown to enhance ongoing flexor muscle activity in human infants,26 able-bodied adults,27–29 and individuals with incomplete spinal cord injury.30 Estimates of muscle torque generated at the hip and knee joints in human infants who stepped with leg weights indicated that greater flexor motor activity was produced in response to this type of perturbation.26 Analogous results have also been reported in adults in whom reflex increases in lower limb flexor muscles were observed in response to unexpected mechanical disturbances that slowed or obstructed the motion of the swinging limb.28,29,31,32 The addition of leg weights during walking in able-bodied individuals has also been shown to elicit an increase in hip flexor moment during initial swing.33
The effects of loading the leg in this way was previously examined in a small group (n = 3) of individuals with stroke.34 No significant changes in walking speed were noted, but this may have been related to the low training intensity (30-50 m per day for five days) and/or the low amount of added weight (2-6 lb) that was used. In addition, possible improvements in other walking tasks or gait parameters (besides walking speed) may have been missed. Other studies of lower limb resistive strength training have shown conflicting results with respect to gait outcomes of walking speed or stair climbing ability.35,36 No studies to date have examined the effects of repeated loading of leg flexor muscles during a treadmill-based locomotor training program. Thus, the objective of this study was to evaluate a gait training strategy using leg weights to load the leg during the swing phase. It was hypothesized that treadmill-based locomotor training combined with leg weights in people with chronic stroke would improve overground walking speed and performance in tasks requiring appropriate leg flexion movements, such as stair climbing and obstacle avoidance. Two additional research questions were examined. First, does training with leg weights have an effect on temporal gait parameters during the swing phase? Second, is there a relationship between training duration and physical impairment due to stroke on these functional ambulation measures?
Individuals with chronic stroke (>six months) were recruited from the community to participate in this study. They were not paid to participate in the study but were reimbursed for their travel costs (ie, gas mileage and parking). For inclusion in the study, participants had to be able to stand and be able to walk at least 10 m overground (with or without orthoses and assistive devices), and the participants were excluded if they had uncontrolled spasticity, cardiovascular, or musculoskeletal condition that precluded treadmill exercise. Participants gave written informed consent before entry into the study. All procedures were approved by the University of British Columbia Clinical Research Ethics Board.
Each participant was assessed with the Chedoke-McMaster Stroke Assessment impairment inventory for the foot and leg, which has been shown to be a reliable and valid tool to assess physical impairment after stroke.37 This assessment rates the degree of physical impairment in the paretic foot and leg on a scale ranging from 1 (flaccid paralysis) to 7 (normal movement patterns).
An overhead suspension system (Biodex, Shirley, NY) positioned over a treadmill was used for the training intervention. Treadmill speed of each training session was set to the maximum tolerated by the participant while ensuring maintenance of upright posture throughout the gait cycle (ie, the legs do not lag behind the rest of the body). Leg weights were attached around the mid-shank in all participants. The weights were secured using Velcro straps and tensor bandages. The amount of added weight was 5% of body weight, which was based on previous work30 demonstrating that this amount of added weight could be effective in enhancing flexor muscle activity. Only the paretic leg was loaded. None of the participants required body-weight support to produce proper stance limb kinematics during walking. Nevertheless, all participants were attached to the harness system to guard against falling during treadmill walking. Training occurred three times per week for four to 12 weeks. During each session, participants completed 30 minutes of walking. Participants were encouraged to walk without holding onto the handrails. Rest breaks were provided as needed, but participants had to complete 30 minutes of walking per session. The Borg rating of perceived exertion,38 a 15-point self-report scale of perceived level of effort, was monitored throughout training.
The effects of this experimental therapy were assessed by overground gait velocity and functional ambulatory capacity. Overground gait velocity was measured with the 10-m walk test (10MWT). Participants walked along a 14-m walkway and were asked to walk as fast as they could within their comfort level, using their usual walking aids. Gait velocity was calculated by the time taken to traverse the middle 10 m, as measured by a stopwatch. The average velocity was calculated from three trials. Force sensitive resistors (Interlink Electronics, Inc., Camarillo, CA) positioned under the sole of each foot also allowed for detection of foot contact and toe-off during straight-ahead walking.
The modified Emory Functional Ambulation Profile (mEFAP) was used as a measure of functional ambulatory capacity.39 This is a test that measures the time required to complete five different walking tasks: (1) walking on a smooth floor surface for 5 m; (2) walking on a low-pile carpet for 5 m; (3) rising from a chair, walking 3 m, and returning to sit in the chair (Timed Up and Go); (4) obstacle avoidance; and (5) stair climbing (five steps up and down). The use of assistive devices and the level of manual assistance are also recorded. The time required to complete each subtask is then multiplied by a factor corresponding to the assistive device or level of manual assistance. The five subscores are then summed to provide a total score. The mEFAP has been shown to be a valid and reliable measure of functional ambulation after stroke.40 All measures were recorded within one week before the start of training (baseline) and within five days of training completion (posttraining).
The step cycle duration was defined by the time between consecutive foot contacts (as indicated by the signals from the force-sensitive resistors positioned under each foot). The swing phase duration was defined by the time between toe-off and subsequent foot contact and expressed as a percentage of step cycle duration (%swing). This variable was calculated for both the paretic and nonparetic sides.
A commercially available software package (SPSS 8.0, SPSS, Inc., Chicago, IL) was used to conduct the statistical analysis. For all statistical evaluations, the level of significance was set at an α value of 0.05. Because of the small sample size, nonparametric statistical tests were used.41 The effect of treadmill-based locomotor training with leg weights on functional ambulation was assessed with the Wilcoxon signed rank test to compare baseline versus posttraining for the 10MWT, mEFAP scores and %swing. To determine whether there was any effect of training duration or the level of physical impairment on training outcomes, we used the Spearman’s correlation coefficient to determine the relationship between the number of training sessions and the 10MWT and mEFAP. The same was performed to determine the relationship between the Chedoke-McMaster foot and leg scores and the 10MWT and mEFAP.
Six participants (S1-S6) with chronic stroke were recruited to participate in this study. Participant characteristics are summarized in Table 1. All participants tolerated the addition of leg weights during the treadmill-based locomotor training. Only one participant (S6) needed to use an ankle-foot orthosis during the training sessions. Participants were able to tolerate the treadmill walking without needing to hold onto the handrails, particularly after they became accustomed to the program. Only participant S6 used the rails during the training sessions. The median Borg PE across participants was 13 (somewhat hard). Participants gradually increased their training speed during the course of the program, which ranged from 11 to 36 training sessions (Table 2). The disparity in the number of training sessions between participants arose from a variety of situations, such as scheduling difficulties (2 participants). One participant felt that the training was not benefiting her and completed only 11 sessions. Despite the disparity in the number of training sessions, we did not find a relationship between any training effects and the duration of training.
Effect of Training on Measures of Functional Ambulation
The change in overground gait velocity, as measured by the 10MWT, and ambulatory capacity, measured by the mEFAP, is displayed in Table 3. All participants except S4 exhibited an improvement in gait velocity posttraining compared with baseline, but there was no overall significant change in gait velocity (Z = −1.78, P = 0.08). There was also no overall significant change in ambulatory capacity (lower mEFAP scores indicate better performance; Z = 0.94, P = 0.35). However, improvements in functional ambulation were evident in the mEFAP components of most participants, except S4 (Fig. 1). The most prominent improvement was in the time required to ascend and descend five stairs. All participants except one (S4) exhibited improved stair climbing ability, but there was no overall significant improvement across the participants (Z = −1.57, P = 0.12).
Changes in the temporal measures of swing phase duration also showed an improvement posttraining. Signals from the force-sensitive resistors were not available from S3 posttraining due to technical difficulties. There was a general trend for an increase in %swing on both the paretic and nonparetic side (Table 4), but this was not statistically significant (Z = −1.46, P = 0.14).
Relationship of Training Outcomes with Training Duration and Physical Impairment
Because of the range in the number of training sessions that were completed by the participants, we examined whether there was a relationship between the 10MWT or mEFAP scores and the number of training sessions (Fig. 2). The duration of training (number of training sessions) was not significantly related to changes in the gait velocity (r = 0.52, P = 0.29), mEFAP scores (r = 0.32, P = 0.54), and no clear trends could be discerned. There was also no significant relationship between the Chedoke-McMaster foot or leg scores and functional ambulation outcomes, although there is a slight trend for participants with more physical impairment (ie, lower Chedoke-McMaster scores) to have greater percent improvement in functional ambulation (Fig. 2).
This study examined the effect of a treadmill-based locomotor training protocol using leg weights on functional ambulatory capacity. Although the sample size of this pilot study is small, the results indicate that treadmill-based locomotor training with leg weights is feasible and could be an effective strategy to improve functional ambulation in people with chronic stroke. Most participants showed an improvement in functional gait parameters, such as gait velocity and the ability to climb stairs, and an increase in the proportion of the step cycle spent in swing on the paretic side.
Treadmill-based locomotor training with partial body weight support has gained much attention as a promising approach to improve ambulation among people with incomplete spinal cord injury.42–46 However, there are mixed results about the efficacy of treadmill-based locomotor training in the chronic stroke population.47–49 The results of some clinical studies have suggested that strategies that provide a more challenging training environment, such as progressively increasing the treadmill speed50 or explicit practice of a variety of functional tasks,51,52 may be the key to producing functional improvements in ambulatory individuals after stroke. Although these reports have raised the issue of the clinical efficacy of treadmill-based locomotor training compared with other rehabilitation approaches, improved understanding of the neural and sensory control of walking is essential to ensure continued advances in gait rehabilitation strategies. We provided a more challenging training environment by affixing weights, scaled to body weight, around participants’ lower leg. The strategy of loading the flexor muscles by using leg weights was based on the concept that feedback during the swing phase can positively enhance ongoing flexor muscle activity, a finding that has been confirmed in both animal and human studies.26–29,53 Sensory feedback mediated by spinal reflex pathways from length- and load-sensitive afferents in flexor muscle have been shown to have an excitatory effect on ongoing flexor muscle activity in decerebrate cats.53,54 Rapid feedback-mediated facilitation of lower limb flexor muscles after mechanical swing phase perturbations has also been shown in adult humans.28,29,31,32 More recent studies have also shown that with repeated exposure to mechanical swing phase perturbations (eg, leg weights or resistance from robot-applied forces), humans develop anticipatory locomotor commands. Evidence for such anticipatory locomotor commands are revealed when the perturbation is unexpectedly removed and an aftereffect (eg, high stepping after swing phase resistance) is generated.26,29,30,33,55 Interestingly, one of our participants made a habit of walking around the laboratory at the end of each training session. He stated that he enjoyed the light feeling in his legs and that it seemed to be easier to walk after the weights were removed. In most participants, we observed that the proportion of the step cycle devoted to the swing phase increased toward normal expected values (40% of the step cycle),56,57 indicating that training with leg weights could have positively affected swing phase activity. The proportion of the step cycle devoted to the swing phase on the nonparetic limb also tended to increase but largely remained below normal expected values. Such minimal effects on nonparetic swing values (paretic limb stance) after treadmill-based locomotor training are consistent with previous reports.58
Recent evidence suggests that improvements in walking function posttraining could be attributed to changes in cortical drive during locomotion. Studies using transcranial magnetic stimulation or functional magnetic resonance imaging have indicated that there are increases in descending motor excitability and increases in the size of the cortical representation of lower limb muscles after single59 or repeated60–62 bouts of treadmill-based locomotor training in individuals with stroke. Enhanced cortical excitability and representation of the tibialis anterior muscle was also recently shown to be correlated to improved balance and step length following treadmill-based locomotor training.60 Improvements in functional ambulation were also shown to be associated with increased activation of cerebellar and midbrain areas after a six-month treadmill exercise program in individuals with chronic stroke.62 Considering that there is a particular contribution of cortical input to lower limb flexor muscles during walking,63–66 it is quite possible that changes in supraspinal input could have contributed to the changes in functional ambulation that we observed here after treadmill-based locomotor training with leg weights.
One previous study investigated the effect of leg weights in a small group (n = 3) of stroke survivors over a five-day training period.34 No significant effects on gait velocity were noted. In this study, participants underwent more intensive treadmill-based locomotor training with leg weights for a minimum of four weeks, three times per week. In addition, the amount of weight added to the legs was adjusted as a proportion of body weight and was based on previous findings about the relationship between added weight and level of flexor muscle activation during swing.30 However, we found no significant effects on overground gait velocity. Given that most of our participants’ initial gait velocity was in the range associated with the least-limited to full community ambulators,67 it may not be surprising that further improvements in gait velocity were not seen. Indeed, it was the participant who had the lowest initial gait velocity (S6) who showed the most marked improvements. In addition, we also note that four of our participants (S1, S3, S5, and S6) demonstrated a change in gait velocity of >0.10 m/sec. The standard error of measurement of the 10MWT has been reported to be 0.04 m/sec, and a change of 0.10 m/sec has been determined to be the threshold for determining substantial meaningful change in functional mobility.68
Although we did not observe significant improvements in overground gait velocity, other notable changes were observed, in particular, the improvements in stair climbing ability in most of the participants. Stair climbing is noted to be one of the most difficult mobility tasks among the poststroke69 and elderly70 population. Curiously, we did not observe a consistent improvement in the mEFAP subscore for obstacle crossing, another task that we expected would be particularly influenced by the hypothesized improvements in swing phase movement afforded by treadmill-based locomotor training with leg weights. Recent studies have described the gait characteristics of steps over obstacles in people with stroke.7,71 Reduced toe clearance and diminished knee flexion during the swing phase were suggested as contributing factors to the difficulties with obstacle clearance in people with stroke.7 However, the mEFAP subscore for obstacle avoidance is determined mainly by the time to completion. We did not conduct a kinematic analysis of obstacle crossing and therefore could have missed other qualities that might have improved, such as clearance height over the obstacles. Further studies are needed to determine whether the effects of this form of treadmill-based locomotor training with leg weights generalize to biomechanical improvements in gait characteristics during tasks such as obstacle crossing or stair climbing.
This was a pilot study that used a small sample of community-dwelling participants with mild stroke. Functional improvements in gait after treadmill-based locomotor training in these populations have been observed previously,48,49 so we cannot rule out the possibility that the positive effects that we observed could be attributable just to the training and not to a specific effect of the leg weights. Future studies stemming from this research are planned to include a larger sample of participants and the inclusion of a control intervention.
The amount of added weight around the leg was standardized at 5% of body weight. It is possible that this may not have provided enough of a training effect to significantly improve walking speed, stair climbing, or obstacle-crossing ability. Considering that many of our participants already had initial overground gait velocities more than 0.90 m/sec, modest improvements in this variable may not be surprising. Nevertheless, we still observed an overall mean improvement in gait velocity of 19% as well as promising results in the more difficult task of stair climbing, which improved in almost all participants. Further studies should determine whether this protocol may be improved by standardizing the amount of added weight according to the lower limb strength or ambulatory capacity rather than to body weight. This protocol was otherwise found to be safe and feasible with median Borg ratings of somewhat hard across all participants.
This pilot study demonstrates that treadmill-based locomotor training combined with leg weights could be a feasible approach for improving the ability to perform complex walking tasks, such as stair climbing, in individuals with chronic stroke. Further work must be conducted to differentiate the specific benefit of adding leg weights versus the effect of treadmill-based locomotor training alone.
The authors thank A. Burke, B. Cowie, F. Lam, S. Liu, S. Hua, J. Shcherbakova, and T.D. Wingson for their valuable assistance and to all the participants who took part in this study. Tania Lam is a Canadian Institutes of Health Research New Investigator.
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