Volume 16, Issue 1 , Pages 14-21, January 2012
Understanding gait control in post-stroke: Implications for management
Article Outline
- Summary
- Introduction
- Neurophysiology of gait
- Neurophysiological reasoning for gait dysfunction in stroke
- Biomechanics of gait
- Pathomechanics of gait dysfunction in stroke
- Walking speed
- Conventional management
- Contemporary management
- Implications for management
- Conclusion
- References
- Copyright
Summary
The role of the brain in post-stroke gait is not understood properly, although the ability to walk becomes impaired in more than 80% of post-stroke patients. Most, however, regain some ability to walk with either limited mobility or inefficient, asymmetrical or unsafe gait. Conventional intervention focuses on support of weak muscles or body part by use of foot orthosis and walking aids. This review provides an overview of available evidence of neuro-kinesiology & neurophysiology of normal and post-stroke gait. The role of the spinal cord has been explored, more in animals than humans. Mammalian locomotion is based on a rhythmic, “pacemaker” activity of the spinal stepping generators. Bipedal human locomotion is different from quadripedal animal locomotion. However, knowledge derived from the spinal cord investigation of animals, is being applied for management of human gait dysfunction. The potential role of the brain is now recognized in the independent activation of muscles during walking. The brain modifies the gait pattern during the complex demands of daily activities. Though the exact role of the motor cortex in control of gait is unclear, available evidence may be applied to gait rehabilitation of post-stroke patients.
Keywords: Gait, Locomotion, Stroke, Hemiparesis, Rehabilitation
Introduction
Stroke is the second leading cause of death and one of the leading causes of adult disability in the world today (Gresham et al., 1997). Ability to walk gets impaired in more than 80% of post-stroke patients (Duncan et al., 2005, Wevers et al., 2009). Most of them regain some ability to walk, 40% require assistance with walking and 60% are limited in community ambulation (Jorgensen et al., 1995), an ability to move and negotiate independently outside the home (Lord et al., 2004).
In spite of rehabilitative efforts, approximately 35% of survivors with initial paralysis of the lower extremity do not regain useful walking function, and 25% of all survivors are unable to walk without full physical assistance before hospital discharge (Hendricks et al., 2002).
Post-stroke gait dysfunction is among the most investigated neurological gait disorders. The dysfunction is typically manifested by a pronounced asymmetrical deficit (Mayer, 2002). Restoration of gait is one of the major goals in post-stroke rehabilitation (Lindquist et al., 2007).
Traditionally various methods have been developed to restore walking ability. This includes compensatory methods such as use of Ankle foot orthosis (AFO) and walkers or canes (Beauchamp et al., 2009, Chu, 2001). These methods are based on the concept of providing support to the impaired body parts to perform an activity. Over the last decade, rehabilitative methods acting on the brain and associated areas to improve gait in post-stroke patients have been studied (Enzinger et al., 2009). However, the exact role of the central nervous system in normal as well as in post-stroke gait is still not understood.
This review focuses on the underlying mechanisms responsible for the control and disturbance of gait in post-stroke patients. Further, commonly used traditional and emerging treatment methods are discussed.
Neurophysiology of gait
The basic motor pattern for stepping is generated in the spinal cord, while fine control of walking involves various brain regions, including motor cortex, cerebellum, and brain stem (Dietz, 1996). Human infants exhibit the stepping pattern even before birth and this primitive ability continues throughout life to enhance mobility (Yang and Gorassini, 2006). The spinal cord is found to have Central Pattern Generators (CPGs) which are responsible for hard wired-synergy. The synergies produce and coordinate locomotion in quadruped animals. CPGs are networks of nerve cells producing specific, rhythmic movements such as walking, without conscious effort and without the aid of peripheral afferent feedback. Mammalian locomotion is based on a rhythmic, “pacemaker” activity of these spinal stepping generators (CPGs). The motor cortex modifies these synergies during complex demand of daily gait related activities. However, evidence of CPGs for humans is still indirect, based on animal studies (Beloozerova and Sirota, 1998, Drew et al., 2008, MacKay-Lyons, 2002). The available evidence suggests that humans like other animals possess CPGs. However, their activities depend much more on supraspinal influences than those in other animals. CPGs activity has been importantly modified to meet the functional requirements of bipedal walking (Nielsen, 2003). The proposed role of the central nervous system in walking is summarized in Fig. 1.
Figure 1
Role of brain & spinal cord in walking.
The difference in the control of walking in man and animals needs to be understood. This would provide a sound basis for gait rehabilitation of post-stroke patients.
Further, the pattern generating networks for each leg are autonomous and can operate independently. The neural correlates of gait asymmetry may provide prognostic markers for future persistent gait dysfunction in post-stroke patients (Yang and Gorassini, 2006). To know the specific association between the location of brain lesions and the control of walking post-stroke, Alexander et al., 2009 investigated subtraction lesion analysis to distinguish brain regions associated with persisting temporal gait asymmetry in 37 chronic ambulatory stroke patients (17 symmetrical gait, 20 asymmetrical gait). Spatiotemporal gait parameters were measured using an instrumented walking surface. Lesions were scanned and analyzed from 3D T1-MRI. The lesion overlay of patients with symmetrical gait was subtracted from patients with asymmetrical gait to highlight voxels more frequently lesioned in asymmetrical patients and relatively spared in symmetrical patients. The results indicated that damage to the posterolateral putamen was associated with temporal gait asymmetry (Alexander et al., 2009). The putamen receives projections from various brain areas such as the primary motor cortex, premotor areas and supplementary motor area and projects to subcortical areas such as the thalamus (Alexander et al., 1990). Thus, injury to the putamen could disrupt communication between cortical and subcortical motor areas. Functional MRI (fMRI) studies have also reported the role of the putamen during active ankle dorsiflexion, which is supposed to be an important component of the gait cycle (Dobkin et al., 2004).
Neurophysiological reasoning for gait dysfunction in stroke
Post-stroke patients walk with synergistic mass patterns of the affected lower extremity rather than selective control of individual joint movements. Two types of synergistic patterns occur during walking. Synergistic contractions of the quadriceps and the gluteus maximus cause a mass extension pattern during the stance phase while the hip flexors, knee flexors, and ankle dorsiflexors cause the mass flexion pattern during the swing phase (Chen et al., 2003).
Clinically, it is assumed that spasticity of the lower extremity muscles affects the gait of post-stroke patients. However, clinical and physiological (resting and action stretch reflexes) aspects of spasticity were not found to be related to the walking of stroke patients when compared with neurologically normal control subjects. Spasticity of the gastrocnemius did not resist dorsiflexion due to exaggerated action tonic stretch reflexes (Ada et al., 1998).
Further, post-stroke patients show more co-contractions of agonist and antagonist muscles at the ankle and knee joints during the stance phase. These adaptations may allow the individual to have a safer and more stable gait pattern to compensate for diminished sensory information from the ankle (Corrêa et al., 2005).
Balance dysfunction is another neurophysiological issue seen among the ambulatory post-stroke patients. It is caused by disturbance in various physiological systems concerned with postural control. This includes sensory afferents, movement strategies, biomechanical constraints, cognitive processing, and perception of verticality (de Oliveira et al., 2008). Balance is an essential part of ambulation. Post-stroke patients do not walk safely and have increased risk of falling toward the paretic side. They have four times the risk of falls and ten times the risk of hip fractures of healthy people (Dobkin, 2005).
Biomechanics of gait
Gait is also a complex interaction between the CNS and peripheral musculoskeletal systems. CNS dysfunction results into musculoskeletal adaptation to carry out gait related tasks in the absence of normal musculoskeletal coordination. Hence, it is imperative to understand normal human gait kinematics. The important kinematic features of human walking, comprises-
Further, to quantify gait various spatial (related to distancing) and temporal (related to timing) variables have been defined. For example, step length, which is the linear distance between two successive points of contact of the right and left lower extremity while stride length is the linear distance between two successive points of contact of the same foot. Similarly, stance time is the amount of time during the gait cycle that the foot is in contact with the ground while swing time is the amount of time during the gait cycle that the foot is off the ground (Norkin and Olney, 2007). There would be symmetry in gait when spatial (spatial symmetry) and temporal (temporal symmetry) variables are equal in both right and left lower extremities.
Although most of the recent methods for post-stroke gait rehabilitation are based on the evidence of animal studies, the above biomechanical features are absent in animals. Evolutionary change of human walking from quadripedal to bipedal have led to neurophysiological changes in human CNS. Human gait is biomechanically and neurophysiologically different from animals. Hence, the evidence of animal studies needs to be applied with caution evolving therapeutic protocols (Yang and Gorassini, 2006).
Pathomechanics of gait dysfunction in stroke
Poor single limb support and uncontrolled forward movement are basic impairments leading to asymmetry. The asymmetry is comprised of decreased stance time and prolonged swing period of the involved side (Perry et al., 1978). The consistent pattern of symmetrical step length during the gait cycle is missing, with longer step length on the paretic side (Dettmann et al., 1987, Hsu et al., 2003, Kim and Eng, 2003). However, it has also been reported that post-stroke patients walk with either relatively longer paretic or non-paretic step length. The reasons for the this have not been explained (Dettmann et al., 1987, Hsu et al., 2003).
Further, there is a slower walking speed, shorter stride length and cycle duration. Stance phase is shortened and the swing phase lengthened in the paretic limb compared to healthy individuals. To compensate for these changes, the non-paretic limb has an increased stance and decreased swing phase.
Time duration of double-limb support and stance phase of both lower extremities (particularly of the unaffected lower extremity), are longer in the post-stroke client than normal (Brandstater et al., 1983; Olney et al., 1994, Roth et al., 1997, Olney and Richards, 1996, Ozrigin et al., 1993). Asymmetry on the non-affected side occurs out of compensation and adaptation (Gaviria et al., 1996). These asymmetries lead to inefficient energy expenditure, falls, abnormal joint loading, joint damage, deformity and pain (Forster and Young, 1995, Morris et al., 1992, Olney et al., 1986).
There are various methods described in the literature to measure such asymmetries. A temporal symmetry ratio (TSR) for gait can be calculated using the following equation:
TSR = paretic swing time/stance time divided by non-paretic swing time/stance time (Patterson et al., 2010).
Similarly, step length asymmetry can also be quantified by using a step length ratio (SLR), which is defined as the paretic step length (in meters) divided by the non-paretic step length (in meters) (Balasubramanian et al., 2007).
Another way to quantify the extent of the temporal and spatial asymmetry of gait pattern, is, as follows:
Single-support time asymmetry ratio = 1 − Single-support time (affected)/Single-support time (unaffected).
Step length asymmetry ratio = 1 − Step length (affected)/Step length (unaffected).
The greater ratio indicates significant asymmetry (Hsu et al., 2003).
Walking speed
Walking speed is an important indicator of post-stroke gait performance. A different level of walking speed is required to explore the environment such as home and community. Ambulation is required to perform various activities of daily living, for example, going to a bathroom from a bedroom. Post-stroke patients with severe impairment do not achieve this level of ambulation. Community ambulation, which is an ability to integrate walking with other tasks in a complex environment, also becomes impaired in post-stroke patients. The presence of impaired physical performance and possible cognitive and behavioral factors interact with the performance of gait (Lord and Rochester, 2005). Although gait speed does not consistently reflect the level of community ambulation attained, it is frequently used as a proxy measure for community ambulation. Its use needs to be considered for assessing broader dimensions of community ambulation.
Decreased walking speed is a commonly observed impairment in stroke populations. Normal walking speed for healthy individual is about 1.3 m/s (Bohannon, 1997), while the average walking speed of people with hemiparesis ranges from 0.23 to 0.73 m/s (Olney and Richards, 1996). Perry et al. classified post-stroke gait ambulation as household ambulation (severe impairment), speed of 0.4 m/s; limited community ambulation (moderate impairment), speed between 0.4 and 0.8 m/s; and full community ambulation (mild impairment), speed of 0.8 m/s. Unlimited community ambulation is possible if an individual walks at a speed of 0.8 m/s or greater (Perry et al., 1995). However, it has also been reported that only 60% of the healthy adults walk with this speed (Perry, 1992).
In addition to this, lower extremity strength is considered to be a significant predictor for gait speed, gait endurance, physical performance and functional balance (Bale and Strand, 2008, Kluding and Gajewski, 2009). Inability to carry out voluntary movements is the direct manifestation of stroke rather than muscle weakness. Muscle weakness occurs as a secondary manifestation out of disuse, spasticity, shortening and imbalance between agonist and antagonist (Bohannon, 2007).
Conventional management
Ankle foot orthosis (AFO) is the most common and traditional method used for the management of gait dysfunction in post-stroke patients. It is an assistive device that is used to maintain ankle joint stability in the anterior–posterior and medial–lateral directions and also to permit and stabilize motions at the subtalar joint. It is made of plastic and/or metal. Its use is solely based on biomechanical principles, and is typically prescribed for foot drop during the swing phase of the gait cycle, mediolateral instability and insufficient push off during the stance phase of the gait cycle. Foot drop is the common indication for post-stroke patients. Walking aids such as walkers and canes may be used along with AFO. Further, use of AFO has been reported to improve step length and stride length of lower extremities, step width, cadence, walking speed and functional ambulation (Abe et al., 2009, Chu, 2001).
Post-stroke patients commonly use walking aids to achieve independent gait. Although more than 75% of patients use at least one gait aid three-month post-stroke, there is no evidence-based guideline for the prescription of these aids. However, they are widely used to improve symmetry, provide stability and balance (Beauchamp et al., 2009).
Contemporary management
Body weight support treadmill training
Initially developed for people with spinal cord injuries, Body weight support treadmill training (BWSTT) is now also becoming a promising approach for gait rehabilitation in stroke aftercare (Hicks and Ginis, 2008). In this approach, body weight support is provided by a harness that reduces biomechanical and equilibrium walking constraints. The treadmill thus facilitates a normal walking pattern. Consequently, the individual can practice repetitive training without abnormal deviations. The training has been found to activate CPGs in animal studies (MacKay-Lyons, 2002, Norton and Mushahwar, 2010).
Studies have also shown that CPGs have independent control of both the lower extremities (Nielsen, 2003). This may have implications for gait rehabilitation, post-stroke, by body weight support treadmill training, with two different speeds, faster for the affected leg and slower for the unaffected one. The leg on the fast belt would take more steps than the leg on the slow belt. However, most of the studies done so far using BWSTT have not used the variable speed for both legs.
A study was conducted to investigate whether cerebral damage from stroke impairs fast reactive (e.g. changing step height to a clear obstacle) or slow adaptive changes (e.g. changing walking pattern in response to new shoes). Split-belt treadmill training was given to improve interlimb (right and left limb) coordination. The after-effects from a 15-min adaptation session could temporarily induce symmetry in subjects who demonstrated baseline asymmetry of spatiotemporal gait parameters. The findings indicate that cerebral stroke survivors are indeed able to adapt interlimb coordination. This raises the possibility that asymmetric walking pattern post-stroke could be corrected utilizing the split-belt treadmill as a long-term rehabilitation strategy (Reisman et al., 2007).
The concept of BWSTT is more applicable to the paraplegic as neither limb can take the body weight during walking. In post-stroke patients, there is a hemiparesis, with abnormal control of one lower limb producing asymmetrical gait deviations. The partial unloading of the lower extremities by the body weight support system, results in a straighter trunk and knee alignment during the loading phase. It also leads to decrease in double-limb support time, and increase in single limb support time, stride length, and speed. This provides an environment for specific and repetitive training for walking (Lindquist et al., 2007). The specificity of learning is hypothesized to induce neuroplasticity and associated motor recovery (Schmidt, 2005). Thus, BWSTT can be used to manage post-stroke gait dysfunction by normal gait programming generated by this novel approach.
Randomized trials of BWSTT have shown improvement in gait parameters such as stride length and single limb support in chronic stroke patients (Laufer et al., 2001, Werner et al., 2002). The studies suggested that treadmill training might be more effective than conventional gait training for improving gait parameters such as functional ambulation, stride length, percentage of the paretic single stance period, and muscular activity. BWSTT may have a greater effect in patients with more chronic hemiparesis who walk with a poor gait pattern and walk slowly (less than 80 cm/s) (Dobkin, 2004). A Cochrane review of 11 trials with a total of 458 participants concluded that a well-designed large-scale study to assess BWSTT after stroke is needed (Moseley et al., 2005).
Enzinger et al. (2009) investigated walking ability and cortical reorganization after four weeks of BWSTT in 18 chronic patients (mean age, 59.9 ± 13.5 years) with mild to moderate paresis and functional ambulation category range, 3–5. Walking endurance improved after training (2-min timed walking distance: 121.5 ± 39.0 versus pre: 105.1 ± 38.1 m; p < 0.0001). For active movement of the paretic foot versus rest, greater walking endurance correlated with increased brain activity in the bilateral primary sensorimotor cortices, the cingulate motor areas, and the caudate nuclei bilaterally and in the thalamus of the affected hemisphere (Enzinger et al., 2009).
Though gait control has been attributed to more of a subcortical contribution, BWSTT training is associated with bilateral cortical activation changes in chronic stroke. Further, BWSTT is developed from studies of animals with transected spinal cords (Barbeau, 2003). The theoretical basis of this training evolved from studies on quadruped animals. The theory is less applicable to bipedal humans. Bipedal walking requires various neuromusculoskeletal adaptations and linkages (Dobkin, 2004). For example, bipedal human gait has heel strike and push off phase for greater energy efficiency; quadrupeds do not.
In summary, BWSTT can be used in post-stroke patients to induce reorganization at the spinal and supraspinal level, reduce asymmetries of gait parameters and increase walking speed. Further, among all the recent therapeutic methods, BWSTT can act on the various issues of gait dysfunction in post-stroke patients. However, its evidence at the neural level is based on animal studies.
Mental imaging
Mental imagery is a cognitive process of creating any mental experience (auditory, visual, tactile, and kinesthetic) without its actual presence (Dickstein and Deutsch, 2007). The concept of mental imagery has been evolved from sports medicine where it is used to maintain the performance level of athletes during recovery from injury. The rationale behind this technique is the activation of same brain areas and pathways that are used in actual movement, even in the absence of real movement performance.
Mental imagery has been found to increase activation of cerebellar, premotor, primary motor cortex and striatal sensorimotor networks. The changes correlated with motor and functional recovery (Lacourse et al., 2004, Page et al., 2009). However, most of the evidence of mental imagery is either from upper extremity trials or from randomized controlled trials (RCT) for gait improvement with inadequate sample size (Dickstein et al., 2004, Hwang et al., 2010). In a very recent RCT with 24 chronic stroke patients using locomotor imagery training, Hwang et al. (2010) found clinical improvement in functional ambulation, balance, walking speed and stride length of both limbs. More trials with large samples are needed to confirm the effectiveness of mental imagery for improving gait in post-stroke patients.
Mirror therapy
Ramachandran and Roger-Ramachandran to treat phantom pain after amputation by means of mirror therapy. In stroke rehabilitation, it focuses on moving the unimpaired limb while watching its mirror reflection superimposed over the (unseen) impaired limb. This creates a visual illusion of enhanced movement capability of the impaired limb (Sütbeyaz et al., 2007). Both ipsilateral limb movement and passive observation of movement of the contralateral limb have been found to modulate functional reorganization of the motor cortex (Muellbacher et al., 2000). Sütbeyaz et al. (2007) in their RCT that evaluated the effects of mirror therapy on lower extremity motor recovery and motor functioning of 40 patients with subacute stroke (mean age, 63.5 year). The mean change score and 95% confidence interval (CI) of the Brunnstrom stages (mean, 1.7; 95% CI, 1.2–2.1; versus mean, 0.8; 95% CI, 0.5–1.2; P = 0.002) showed significantly more improvement at follow-up in the mirror group compared with the control group. The improved Brunnstrom stage suggests its use to reduce synergestic movements affecting gait, apart from neural reorganization.
Balance training
Improvement in standing balance control is more important than improvement in leg strength or synergism to achieve improvement in walking ability. In an RCT effect of balance training involved the use of biofeedback on 41 subjects (six months post-stroke). The experimental group showed significant improvement for postural control (p < 0.039) and weight-bearing (p < 0.03) on the paretic side during walking (Yavuzer et al., 2006). No additional benefit was seen for motor recovery, mobility and activity levels (Eser et al., 2008).
Strength training
Bale and Strand (2008) in their pilot RCT, studied the effect of functional strength training on 18 subacute stroke patients. Though the results were not statistically significant, more patients in the functional strength training group (57%) could bear weight on the affected leg while stepping forward as compared to the usualcare group (17%). Improvement was also clinically significant in 7 of 9 outcome measures in the functional strength training group (effect size > or = 0.80, large), but in only 3 of 9 in the training-as-usual group.
Further, strengthening of lower extremity muscles such as the gluteus maximus, quadriceps, ankle plantar flexors is indicated. These muscles are important motors for walking.
Early intensive gait training
Early intensive gait training is effective in management of post-stroke gait. An RCT of 56 acute stroke patients with a mean of 8-day post-stroke was conducted to analyze the effect of the gait trainer, over ground walking and conventional treatment.
The gait trainer is an electromechanical device on which the patient is supported with a harness and his or her feet are placed on motor-driven footplates. It is used to provide intensive gait training. Walking ability improved more with intensive walk training compared with conventional treatment (Functional Ambulation Category changed from 0 to 3 in the experimental group as compared to 0–0.5 in the conventional group). The study focused on early intervention with the help of electromechanical devices. The intervention led to improvement in speed and functional ambulation (Peurala et al., 2009).
Over ground training
Over ground gait training has been defined as therapists’ observation and cueing of the patient’s walking pattern, but does not include high-technology aids such as body weight support. It is hypothesized that over ground gait training helps in educating patients about ways to maintain safety, and it improves strength, cardiovascular fitness, agility and gait efficiency (States et al., 2009). Although such training is assumed to improve functional and community ambulation performance, there is insufficient evidence for its effectiveness.
Implications for management
Traditionally, therapists are taught that benefits of gait training are achieved primarily through compensation for impairments. Further, post-stroke neurological recovery is predominantly spontaneous in nature. However, recent findings on gait control of post-stroke patients indicate that the adult brain is capable of reorganization. It has also been shown that the reorganization is experience-dependent and can be manipulated via appropriate movement stimuli involving the lower limbs. This has resulted in new clinical implications for therapists to provide post-stroke gait training. For example, the role of CPGs indicated the use of stepping pattern training either through the BWSTT or simple treadmill or over ground walking. During such a training therapist should provide appropriate assistance, guidance and feedback for normal and symmetrical lower extremity movements. Similarly, therapists should utilize the role of mental imaging and mirror therapy of specific gait movements by the patient to activate the related neural areas and pathways. This would provide a good neuromuscular background for manual training of the related musculoskeletal structures involved in walking. The tole of a realistic environment should be considered when gait training is initiated. Thus, the focus of the contemporary therapy for post-stroke gait would be on reorganizing the brain through movement therapy of peripheral body parts.
Conclusion
Walking is an important activity of life. Inability to walk properly may lead to dependency as well as reduced participation in society. Post-stroke gait rehabilitation is still a challenge. The mechanism of gait control should be understood both neurophysiologically and biomechanically. It is only through a thorough understanding of normal as well as pathological movement that we can maximize gait related functions in post-stroke patients.
The spinal cord generates human walking, and the cerebral cortex makes a significant contribution in relation to voluntary modifications of the gait pattern. Such contributions are the basis for the unique walking pattern in humans. The resultant neural information generated at the spinal cord and processed at the cerebral cortex, filters through the meticulously designed musculoskeletal system. The movements required for walking are then produced and modulated in response to the environment.
In post-stroke patients, the function of the cerebral cortex becomes impaired while that of the spinal cord is preserved. Hence, the information generation ability of the spinal cord required for walking can be utilized through specific movements to reorganize the cortex for walking. The cerebral cortex can also be reorganized directly for walking through techniques such as mental imaging and mirror therapy.
Thus, the complex interactions of the neuromusculoskeletal system should be considered when selecting and developing treatment methods. The methods should act on the underlying patho-mechanisms causing the disturbances. The application of specific movement therapy will invariably have positive effects on post-stroke gait.
References
- . Improving gait stability in stroke hemiplegic patients with a plastic ankle-foot orthosis. Tohoku Journal of Experimental Medicine. 2009;218(3):193–199
- . Does spasticity contribute to walking dysfunction after stroke?. Journal of Neurology Neurosurgery & Psychiatry. 1998;64(5):628–635
- . Basal ganglia-thalamocortical circuits: parallel substrates for motor, oculomotor, “prefrontal” and “limbic” functions. Progress in Brain Research. 1990;85:119–146
- . Association between gait asymmetry and brain lesion location in stroke patients. Stroke. 2009;40(2):537–544
- . Relationship between step length asymmetry and walking performance in subjects with chronic hemiparesis. Archives of Physical Medicine & Rehabilitation. 2007;88(1):43–49
- . Does functional strength training of the leg in subacute stroke improve physical performance? A pilot randomized controlled trial. Clinical Rehabilitation. 2008;22(10–11):911–921
- . Locomotor training in neurorehabilitation: emerging rehabilitation concepts. Neurorehabilitation & Neural Repair. 2003;17(1):3–11
- . Immediate effects of cane use on gait symmetry in individuals with subacute stroke. Physiotherapy Canada. 2009;61(3):154–160
- . Cortically controlled gait adjustments in the cat. Annals of the New York Academy of Sciences. 1998;16(860):550–553
- . Comfortable and maximum walking speed of adults aged 20 to 79 years: reference values and determinants. Age Ageing. 1997;26:15–19
- . Muscle strength and muscle training after stroke. Journal of Rehabilitation Medicine. 2007;39(1):14–20
- . Hemiplegic gait: analysis of temporal variables. Archives of Physical Medicine & Rehabilitation. 1983;64:583–587
- . Gait performance with compensatory adaptations in stroke patients with different degrees of motor recovery. American Journal of Physical Medicine & Rehabilitation. 2003;82:925–935
- . Biomechanics of ankle-foot orthoses: past, present, and future. Topics in Stroke Rehabilitation. 2001;7(4):19–28
- . Muscle activity during gait following stroke. Arquivos de neuro-psiquiatria. 2005;63(3B):847–851
- . Balance control in hemiparetic stroke patients: main tools for evaluation. Journal of Rehabilitation Research & Development. 2008;45(8):1215–1226
- . Relationships among walking performance, postural stability, and functional assessments of the hemiplegic patient. American Journal of Physical Medicine. 1987;66:77–90
- . Motor imagery in physical therapist practice. Physical Therapy. 2007;87(7):942–953
- . Motor imagery for gait rehabilitation in post-stroke hemiparesis. Physical Therapy. 2004;84(12):1167–1177
- . Interaction between central programs and afferent input in the control of posture and locomotion. Journal of Biomechanics. 1996;29:841–844
- . Strategies for stroke rehabilitation. Lancet Neurology. 2004;3(9):528–536
- . Clinical practice. Rehabilitation after stroke. New England Journal of Medicine. 2005;352(16):1677–1684
- . Ankle dorsiflexion as an fMRI paradigm to assay motor control for walking during rehabilitation. Neuroimage. 2004;23:370–381
- . Muscle synergies during locomotion in the cat: a model for motor cortex control. Journal of Physiology. 2008;586(5):1239–1245
- . Management of adult stroke rehabilitation care: a clinical practice guideline. Stroke. 2005;36(9):e100–e143
- . Brain activity changes associated with treadmill training after stroke. Stroke. 2009;40(7):2460–2467
- . The effect of balance training on motor recovery and ambulation after stroke: a randomized controlled trial. European Journal of Physical Rehabilitation Medicine. 2008;44(1):19–25
- . Incidence and consequences of falls due to stroke: a systematic inquiry. British Medical Journal. 1995;311:83–86
- . Plantar dynamics of hemiplegic gait: a methodological approach. Gait Posture. 1996;4:297–305
- . American Heart Association Prevention Conference. IV. Prevention and rehabilitation of stroke. Rehabilitation Stroke. 1997;28(7):1522–1526
- . Motor recovery after stroke: a systematic review of the literature. Archives of Physical Medicine & Rehabilitation. 2002;83:1629–1637
- . Treadmill training after spinal cord injury: it’s not just about the walking. Journal of Rehabilitation Research & Development. 2008;45(2):241–248
- . Analysis of impairments influencing gait velocity and asymmetry of hemiplegic patients after mild to moderate stroke. Archives of Physical Medicine & Rehabilitation. 2003;84:1185–1193
- . Locomotor imagery training improves gait performance in people with chronic hemiparetic stroke: a controlled clinical trial. Clinical Rehabilitation. 2010;24(6):514–522
- . Recovery of walking function in stroke patients: the Copenhagen stroke study. Archives of Physical Medicine & Rehabilitation. 1995;76:27–32
- . Symmetry in vertical ground reaction force is accompanied by symmetry in temporal but not distance variables of gait in persons with stroke. Gait Posture. 2003;18:23–28
- . Lowerextremity strength differences predict activity limitations in people with chronic stroke. Physical Therapy. 2009;89:73–81
- . Cerebral and cerebellar sensorimotor plasticity following motor imagery-based mental practice of a sequential movement. Journal of Rehabilitation Research & Development. 2004;41(4):505–524
- . The effect of treadmill training on the ambulation of stroke survivors in the early stages of rehabilitation: a randomized study. Journal of Rehabilitation Research & Development. 2001;38(1):69–78
- . Gait training combining partial body-weight support, a treadmill, and functional electrical stimulation: effects on poststroke gait. Physical Therapy. 2007;87(9):1144–1154
- . Community ambulation following stroke: how important and obtainable is it, and what measures appear predictive?. Archives of Physical Medicine & Rehabilitation. 2004;85:234–239
- . Measurement of community ambulation after stroke: current status and future developments. Stroke. 2005;36(7):1457–1461
- . Central pattern generation of locomotion: a review of the evidence. Physical Therapy. 2002;82(1):69–83
- . Clinical neurokinesiology of spastic gait. Bratisl Lek Listy. 2002;103(1):3–11
- . Electrogoniometric feedback: its effect on genu recurvatum in stroke. Archives of Physical Medicine & Rehabilitation. 1992;73:1147–1152
- . Treadmill training and body weight support for walking after stroke. Cochrane Database Systematic Review. 2005;19(4):CD002840
- . Changes in motor cortex excitability during ipsilateral hand muscle activation in humans. Clinical Neurophysiology. 2000;111(2):344–349
- . How we walk: central control of muscle activity during human walking. Neuroscientist. 2003;9(3):195–204
- . Examination of gait. In: O' Sullivan SB, Schmitz TJ editor. Physical Rehabilitation. fourth ed.. New Delhi: Jaypee Publication; 2007;
- . Afferent inputs to mid- and lower-lumbar spinal segments are necessary for stepping in spinal cats. Annals of the New York Academy of Sciences. 2010;1198:10–20
- . Hemiparetic gait following stroke, part I: characteristics. Gait Posture. 1996;4:136–148
- . Mechanical energy of walking of stroke patients. Archives of Physical Medicine & Rehabilitation. 1986;67:92–98
- . Temporal, kinematic and kinetic variables related to gait speed in subjects with hemiplegia: a regression approach. Physical Therapy. 1994;74:872–885
- . Kinematic gait analysis in hemiplegic patients. Scandavian Journal of Rehabilitation Medicine. 1993;25:51–55
- . Cortical plasticity following motor skill learning during mental practice in stroke. Neurorehabilitation & Neural Repair. 2009;23(4):382–388
- . Evaluation of gait symmetry after stroke: a comparison of current methods and recommendations for standardization. Gait Posture. 2010;31(2):241–246
- . Gait Analysis: Normal and Pathologic Function. Thorofare, NJ: Slack, Inc; 1992;
- . The determinants of muscle action in the hemiparetic lower extremity (and their effect on the examination procedure). Clinical Orthopaedic Related Research. 1978;131:71–89
- . Classification of walking handicap in the stroke population. Stroke. 1995;26:982–989
- . Effects of intensive therapy using gait trainer or floor walking exercises early after stroke. Journal of Rehabilitation Medicine. 2009;41(3):166–173
- . Locomotor adaptation on a split-belt treadmill can improve walking symmetry post-stroke. Brain. 2007;130(Pt7):1861–1872
- . Hemiplegic gait. Relationships between walking speed and other temporal parameters. American Journal of Physical Medicine. 1997;76(2):128–133
- . Motor Control and Learning: a Behavioral Emphasis. fourth ed.. Champaign, IL: Human Kinetics, USA; 2005;
- . Overground physical therapy gait training for chronic stroke patients with mobility deficits. Stroke. 2009;40:e627–e628
- . Mirror therapy enhances lower-extremity motor recovery and motor functioning after stroke: a randomized controlled trial. Archives of Physical Medicine & Rehabilitation. 2007;88(5):555–559
- . Treadmill training with partial body weight support and physiotherapy in stroke patients: a preliminary comparison. European Journal of Neurology. 2002;9(6):639–644
- . Effects of task-oriented circuit class training on walking competency after stroke: a systematic review. Stroke. 2009;40(7):2450–2459
- . Spinal and brain control of human walking: implications for retraining of walking. Neuroscientist. 2006;12(5):379–389
- . The effects of balance training on gait late after stroke: a randomized controlled trial. Clinical Rehabilitation. 2006;20:960–969
PII: S1360-8592(10)00189-0
doi:10.1016/j.jbmt.2010.12.005
© 2010 Elsevier Ltd. All rights reserved.
Volume 16, Issue 1 , Pages 14-21, January 2012
