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Trunk control and sitting balance, 2 of the key predictors for functional outcome and hospital stay, (1-4) are often impaired after stroke. (5,6) Patients who are able to sit independently [...], Objective. Trunk training after stroke is an effective method for improving mobility, yet underlying associations leading to the observed mobility carryover effects are unknown. The purposes of this study were to investigate the effectiveness of trunk training for gait and trunk kinematics and to find explanatory variables for the mobility carryover effects. Methods. This study was an assessor-masked, randomized controlled trial. Participants received either additional trunk training (n = 19) or cognitive training (n = 20) after subacute stroke. Outcome measures were the Tinetti Performance-Oriented Mobility Assessment (POMA), the Trunk Impairment Scale, spatiotemporal gait parameters, center-of-mass excursions, and trunk and lower limb kinematics during walking. Multivariate analysis with post hoc analysis was performed to observe treatment effects. Correlation and an exploratory regression analysis were used to examine associations with the mobility carryover effects. Results. Significant improvements after trunk training, compared with the findings for the control group, were found for the Trunk Impairment Scale, Tinetti POMA, walking speed, step length, step width, horizontal/vertical center-of-mass excursions, and trunk kinematics. No significant differences were observed in lower limb kinematics. Anteroposterior excursions of the trunk were associated with 30% of the variability in the mobility carryover effects. Conclusions. Carryover effects of trunk control were present during ambulation. Decreased anteroposterior movements of the thorax were the main variable explaining higher scores on the Tinetti POMA Gait subscale. However, the implementation and generalizability of this treatment approach in a clinical setting are laborious and limited, necessitating further research. Impact. Trunk training is an effective strategy for improving mobility after stroke. Regaining trunk control should be considered an important treatment goal early after stroke to adequately prepare patients for walking.

The Dynamic Gait Index (DGI) is an outcome measure used to characterize mobility performance, specifically the ability to adapt gait to complex walking tasks associated with walking in community environments. [...], Background. In the original and modified Dynamic Gait Index (mDGI), 8 tasks are used to measure mobility; however, disagreement exists regarding whether all tasks are necessary. The relationship between mDGI scores and Centers for Medicare & Medicaid Services (CMS) severity indicators in the mobility domain has not been explored. Objective. The study objectives were to examine the relationship between medical diagnoses and mDGI scores, to determine whether administration of the mDGI can be shortened on the basis of expected diagnostic patterns of performance, and to create a model in which mDGI scores are mapped to CMS severity modifiers. Design. This was a cross-sectional, descriptive study. Methods. The 794 participants included 140 people without impairments (control cohort) and 239 people with stroke, 140 with vestibular dysfunction, 100 with traumatic brain injury, 91 with gait abnormality, and 84 with Parkinson disease. Scores on the mDGI (total, performance facet, and task) for the control cohort were compared with those for the 5 diagnostic groups by use of an analysis of variance. For mapping mDGI scores to 7 CMS impairment categories, an underlying Rasch scale was used to convert raw scores to an interval scale. Results. There was a main effect of mDGI total, time, and gait pattern scores for the groups. Task-specific score patterns based on medical diagnosis were found, but the range of performance within each group was large. A framework for mapping mDGI total, performance facet, and task scores to 7 CMS impairment categories on the basis of Rasch analysis was created. Limitations. Limitations included uneven sample sizes in the 6 groups. Conclusions. Results supported retaining all 8 tasks for the assessment of mobility function in older people and people with neurologic conditions. Mapping mDGI scores to CMS severity indicators should assist clinicians in interpreting mobility performance, including changes in function over time.

Community ambulation requires not only the ability to walk at a minimum gait speed but also the ability to adapt gait to diverse and complex task demands. (1-2) The Dynamic [...], Background. The modified Dynamic Gait Index (mDGI), developed from a person-environment model of mobility disability, measures mobility function relative to specific environmental demands. The framework for interpreting mDGI scores relative to specific environmental dimensions has not been investigated. Objective. The aim of this study was to examine the person-environmental model underlying the development and interpretation of mDGI scores. Design. This was a cross-sectional, descriptive study. Methods. There were 794 participants in the study, including 140 controls. Out of the total study population, 239 had sustained a stroke, 140 had vestibular dysfunction, 100 had sustained a traumatic brain injury, 91 had gait abnormality, and 84 had Parkinson disease. Exploratory factor analysis was used to investigate whether mDGI scores supported the 4 environmental dimensions. Results. Factor analysis showed that, with some exceptions, tasks loaded on 4 underlying factors, partially supporting the underlying environmental model. Limitations. Limitations of this study included the uneven sample sizes in the 6 groups. Conclusions. Support for the environmental framework underlying the mDGI extends its usefulness as a clinical measure of functional mobility by providing a rationale for interpretation of scores that can be used to direct treatment and infer change in mobility function.

MCID of the FGA Measurement of change is the cornerstone of assessing patient progress and outcome. Change scores on outcome measures presumably reflect improvement or decline in the patient's status [...], Background. The Functional Gait Assessment (FGA) is commonly used to measure walking balance. The minimal clinically important difference (MCID) has yet to be determined for the FGA. Objective. The purposes of this study were to determine: (1) the MCID in the FGA for older community-dwelling adults relative to patients' and physical therapists' estimates of change and (2) the extent of agreement between patients' and physical therapists' estimates of change. Design. This study was a prospective case series. Methods. Patients and physical therapists rated the amount of change in balance while walking after an episode of physical therapy for balance retraining on a 15-point global rating of change (GROC) scale. Weighted kappa statistics were calculated to express agreement between patients' and physical therapists' GROC ratings. Functional Gait Assessment change scores were plotted on receiver operating characteristic curves. A cutoff of +3 on the GROC was the criterion used for important change. The optimal FGA change cutoff score for MCID was determined, and sensitivity (SN), specificity (SP), and likelihood ratios (LRs) were calculated. Results. One hundred thirty-five community-dwelling older adults (average age = 78.8 years) and 14 physical therapists participated. There was poor agreement between the patients' and therapists' ratings of change (weighted kappa = .163). The estimated MCID value for the FGA using physical therapists' ratings of change as an anchor was 4 points (SN=0.66, SP=0.84, LR+ =4.07, LR- =0.40). No accurate value for the FGA MCID could be determined based on the patients' ratings of change. Limitations. The small sample size was a limitation. Conclusion. Poor agreement between therapists' and patients' ratings indicate the need for further communication relative to patient goals. The 4-point MCID value for the FGA can be used for goal setting, tracking patient progress, and program evaluation.

Stroke affects almost 1 person every 40 seconds and is the leading cause of serious, long-term disability in the United States. (1) Although physical therapists intervene with many facets of [...], Background. Task-specific training programs after stroke improve walking function, but it is not clear which biomechanical parameters of gait are most associated with improved walking speed. Objective. The purpose of this study was to identify gait parameters associated with improved walking speed after a locomotor training program that included body-weight-supported treadmill training (BWSTT). Design, A prospective, between-subjects design was used. Methods. Fifteen people, ranging from approximately 9 months to 5 years after stroke, completed 1 of 3 different 6-week training regimens. These regimens consisted of 12 sessions of BWSTT alternated with 12 sessions of: lower-extremity resistive cycling; lower-extremity progressive, resistive strengthening; or a sham condition of arm ergometry. Gait analysis was conducted before and after the 6-week intervention program. Kinematics, kinetics, and electromyographic (EMG) activity were recorded from the hemiparetic lower extremity while participants walked at a self-selected pace. Changes in gait parameters were compared in participants who showed an increase in self-selected walking speed of greater than 0.08 m/s (high-response group) and in those with less improvement (low-response group). Results. Compared with participants in the low-response group, those in the high-response group displayed greater increases in terminal stance hip extension angle and hip flexion power (product of net joint moment and angular velocity) after the intervention. The intensity of soleus muscle EMG activity during walking also was significantly higher in participants in the high-response group after the intervention. Limitations. only sagittal-plane parameters were assessed, and the sample size was small. Conclusions. Task-specific locomotor training alternated with strength training resulted in kinematic, kinetic, and muscle activation adaptations that were strongly associated with improved walking speed. Changes in both hip and ankle biomechanics during late stance were associated with greater increases in gait speed.

Recovery of walking ability is the most frequently stated goal for patients after stroke. (1) In the first week poststroke, 63% of patients are unable to walk independently and 50% [...], Background. When people with stroke recover gait speed, they report improved function and reduced disability. However, the minimal amount of change in gait speed that is clinically meaningful and associated with an important difference in function for people poststroke has not been determined. Objective. The purpose of this study was to determine the minimal clinically important difference (MCID) for comfortable gait speed (CGS) associated with an improvement in the modified Rankin Scale (mRS) score for people between 20 to 60 days poststroke. Design. This was a prospective, longitudinal, cohort study. Methods. The participants in this study were 283 people with first-time stroke prospectively enrolled in the ongoing Locomotor Experience Applied Post Stroke (LEAPS) multi-site randomized clinical trial. Comfortable gait speed was measured and mRS scores were obtained at 20 and 60 days poststroke. Improvement of ≥ 1 on the mRS was used to detect meaningful change in disability level. Results. Mean (SD) CGS was 0.18 (0.16) m/s at 20 days and 0.39 (0.22) m/s at 60 days poststroke. Among all participants, 47.3% experienced an improvement in disability level ≥ 1. The MCID was estimated as an improvement in CGS of 0.16 m/s anchored to the mRS. Limitations. Because the mRS is not a gait-specific measure of disability, the estimated MCID for CGS was only 73.9% sensitive and 57.0% specific for detecting improvement in mRS scores. Conclusions. We estimate that the MCID for gait speed among patients with subacute stroke and severe gait speed impairments is 0.16 m/s. Patients with subacute stroke who increase gait speed ≥0.16 m/s are more likely to experience a meaningful improvement in disability level than those who do not. Clinicians can use this reference value to develop goals and interpret progress in patients with subacute stroke.

Humans must precisely coordinate the activities of many muscles to control everyday movements such as walking. This is done in the face of a constantly changing environment--we hold full coffee [...], Locomotion is incredibly flexible. Humans are able to stay uptight and navigate long distances in the face of ever-changing environments and varied task demands, such as walking while carrying a heavy object or in thick mud. The focus of this review is a behavior that is critical for this flexibility: motor adaptation. Adaptation is defined here as the process of adjusting a movement to new demands through trial-and-error practice. A key feature of adaptation is that more practice without the new demand is required to return the movement to its original state. Thus, motor adaptation is a short-term motor learning process. Several studies have been undertaken to determine how humans adapt walking to novel circumstances. Many of these studies have examined locomotor adaptation using a split-belt treadmill. The results of these studies of people who were healthy and people with neurologic damage suggest that the cerebellum is required for normal adaptation of walking and that the role of cerebral structures may be less critical. They also suggest that intersegmental and interlimb coordination is critical but readily adaptable to accommodate changes in the environment. Locomotor adaptation also can be used to determine the walking potential of people with specific neurologic deficits. For instance, split-belt and limb-weighting locomotor adaptation studies show that adults with chronic stroke are capable of improving weight-bearing and spatiotemporal symmetry, at least temporarily. Our challenge as rehabilitation specialists is to intervene in ways that maximize this capacity.

Although walking poses little challenge to individuals who are healthy, those with gait pathologies such as hemiparesis, spinal cord injury, or amputation can find it tiring and difficult. Pathological gait, [...], A healthy gait pattern depends on an array of biomechanical features, orchestrated by the central nervous system for economy and stability. Injuries and other pathologies can alter these features and result in substantial gait deficits, often with detrimental consequences for energy expenditure and balance. An understanding of the role of biomechanics in the generation of healthy gait, therefore, can provide insight into these deficits. This article examines the basic principles of gait from the standpoint of dynamic walking, an approach that combines an inverted pendulum model of the stance leg with a pendulum model of the swing leg and its impact with the ground. The heel-strike at the end of each step has dynamic effects that can contribute to a periodic gait and its passive stability. Biomechanics, therefore, can account for much of the gait pattern, with additional motor inputs that are important for improving economy and stability. The dynamic walking approach can predict the consequences of disruptions to normal biomechanics, and the associated observations can help explain some aspects of impaired gait. This article reviews the basic principles of dynamic walking and the associated experimental evidence for healthy gait and then considers how the principles may be applied to clinical gait pathologies.

The effectiveness of gait training using body-weight support on a treadmill (BWST) compared with conventional gait training for people with subacute stroke who were unable to walk has been demonstrated [...]