Background Objective gait analysis that fully captures the multi-segmental foot movement of a clubfoot may help in early identification of a relapse clubfoot. Unfortunately, this type of objective measure is still lacking in a clinical setting and it is unknown how it relates to clinical assessment. Research question The aim of this study was to identify differences in total gait and foot deviations between clubfoot patients with and without a relapse clubfoot and to evaluate their relationship with clinical status. Methods In this study, Ponseti-treated idiopathic clubfoot patients were included and divided into clubfoot patients with and without a relapse. Objective gait analysis was done resulting in total gait and foot scores and clinical assessment was performed using the Clubfoot Assessment Protocol (CAP). Additionally, a new clubfoot specific foot score, the clubFoot Deviation Index (cFDI*), was calculated to better capture foot kinematics of clubfoot patients. Results Clubfoot patients with a relapse show lower total gait quality (GDI*) and lower clinical status defined by the CAP than clubfoot patients without a relapse. Abnormal cFDI* was found in relapse patients, reflected by differences in corresponding variable scores. Moderate relationships were found for the subdomains of the CAP and total gait and foot quality in all clubfoot patients. Significance A new total foot score was introduced in this study, which was more relevant for the clubfoot population. The use of this new foot score (cFDI*) besides the GDI*, is recommended to identify gait and foot motion deviations. Along with clinical assessment, this will give an overview of the overall status of the complex, multi-segmental aspects of a (relapsed) clubfoot. The relationships found in this study suggest that clinical assessment might be indicative of a deviation in total gait and foot pattern, therefore hinting towards personalised screening for better treatment decision making.
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Background: A significant part of neurological rehabilitation focuses on facilitating the learning of motor skills. Training can adopt either (more) explicit or (more) implicit forms of motor learning. Gait is one of the most practiced motor skills within rehabilitation in people after stroke because it is an important criterion for discharge and requirement for functioning at home. Objective: The aim of this study was to describe the design of a randomized controlled study assessing the effects of implicit motor learning compared with the explicit motor learning in gait rehabilitation of people suffering from stroke. Methods: The study adopts a randomized, controlled, single-blinded study design. People after stroke will be eligible for participation when they are in the chronic stage of recovery (>6 months after stroke), would like to improve walking performance, have a slow walking speed (<1 m/s), can communicate in Dutch, and complete a 3-stage command. People will be excluded if they cannot walk a minimum of 10 m or have other additional impairments that (severely) influence gait. Participants will receive 9 gait-training sessions over a 3-week period and will be randomly allocated to an implicit or explicit group. Therapists are aware of the intervention they provide, and the assessors are blind to the intervention participants receive. Outcome will be assessed at baseline (T0), directly after the intervention (T1), and after 1 month (T2). The primary outcome parameter is walking velocity. Walking performance will be assessed with the 10-meter walking test, Dynamic Gait Index, and while performing a secondary task (dual task). Self-reported measures are the Movement Specific Reinvestment Scale, verbal protocol, Stroke and Aphasia Quality of Life Scale, and the Global Perceived Effect scale. A process evaluation will take place to identify how the therapy was perceived and identify factors that may have influenced the effectiveness of the intervention. Repeated measures analyses will be conducted to determine significant and clinical relevant differences between groups and over time. Results: Data collection is currently ongoing and results are expected in 2019. Conclusions: The relevance of the study as well as the advantages and disadvantages of several aspects of the chosen design are discussed, for example, the personalized approach and choice of measurements.
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In order to achieve a level of community involvement and physical independence, being able to walk is the primary aim of many stroke survivors. It is therefore one of the most important goals during rehabilitation. Falls are common in all stages after stroke. Reported fall rates in the chronic stage after stroke range from 43 to 70% during one year follow up. Moreover, stroke survivors are more likely to become repeated fallers as compared to healthy older adults. Considering the devastating effects of falls in stroke survivors, adequate fall risk assessment is of paramount importance, as it is a first step in targeted fall prevention. As the majority of all falls occur during dynamic activities such as walking, fall risk could be assessed using gait analysis. It is only recent that technology enables us to monitor gait over several consecutive days, thereby allowing us to assess quality of gait in daily life. This thesis studies a variety of gait assessments with respect to their ability to assess fall risk in ambulatory chronic stroke survivors, and explores whether stroke survivors can improve their gait stability through PBT.
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BackgroundGait analysis has been used for decades to quantify knee function in patients with knee osteoarthritis; however, it is unknown whether and to what extent inter-laboratory differences affect the comparison of gait data between studies. Therefore, the aim of this study was to perform an inter-laboratory comparison of knee biomechanics and muscle activation patterns during gait of patients with knee osteoarthritis.MethodsKnee biomechanics and muscle activation patterns from patients with knee osteoarthritis were analyzed, previously collected at Dalhousie University (DAL: n = 55) and Amsterdam UMC, VU medical center (VUmc: n = 39), using their in-house protocols. Additionally, one healthy male was measured at both locations. Both direct comparisons and after harmonization of components of the protocols were made. Inter-laboratory comparisons were quantified using statistical parametric mapping analysis and discrete gait parameters.ResultsThe inter-laboratory comparison showed offsets in the sagittal plane angles, moments and frontal plane angles, and phase shifts in the muscle activation patterns. Filter characteristics, initial contact identification and thigh anatomical frame definitions were harmonized between the laboratories. After this first step in protocol harmonization, the offsets in knee angles and sagittal plane moments remained, but the inter-laboratory comparison of the muscle activation patterns improved.ConclusionsInter-laboratory differences obstruct valid comparisons of gait datasets from patients with knee osteoarthritis between gait laboratories. A first step in harmonization of gait analysis protocols improved the inter-laboratory comparison. Further protocol harmonization is recommended to enable valid comparisons between labs, data-sharing and multicenter trials to investigate knee function in patients with knee osteoarthritis.
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Background The gait modification strategies Trunk Lean and Medial Thrust have been shown to reduce the external knee adduction moment (EKAM) in patients with knee osteoarthritis which could contribute to reduced progression of the disease. Which strategy is most optimal differs between individuals, but the underlying mechanism that causes this remains unknown. Research question Which gait parameters determine the optimal gait modification strategy for individual patients with knee osteoarthritis? Methods Forty-seven participants with symptomatic medial knee osteoarthritis underwent 3-dimensional motion analysis during comfortable gait and with two gait modification strategies: Medial Thrust and Trunk Lean. Kinematic and kinetic variables were calculated. Participants were then categorized into one of the two subgroups, based on the modification strategy that reduced the EKAM the most for them. Multiple logistic regression analysis with backward elimination was used to investigate the predictive nature of dynamic parameters obtained during comfortable walking on the optimal modification gait strategy. Results For 68.1 % of the participants, Trunk Lean was the optimal strategy in reducing the EKAM. Baseline characteristics, kinematics and kinetics did not differ significantly between subgroups during comfortable walking. Changes to frontal trunk and tibia angles correlated significantly with EKAM reduction during the Trunk Lean and Medial Thrust strategies, respectively. Regression analysis showed that MT is likely optimal when the frontal tibia angle range of motion and peak knee flexion angle in early stance during comfortable walking are high (R2Nagelkerke = 0.12). Significance Our regression model based solely on kinematic parameters from comfortable walking contained characteristics of the frontal tibia angle and knee flexion angle. As the model explains only 12.3 % of variance, clinical application does not seem feasible. Direct assessment of kinetics seems to be the most optimal strategy for selecting the most optimal gait modification strategy for individual patients with knee osteoarthritis.
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The purpose of the study was to assess the accuracy of estimates of step frequency from trunk acceleration data analyzed with commonly used algorithms and time window lengths, at a wide range of gait speeds. Twenty healthy young subjects performed an incremental treadmill protocol from 1 km/h up to 6 km/h, with steps of 1 km/h. Each speed condition was maintained for two minutes. A waist worn accelerometer recorded trunk accelerations, while video analysis provided the correct number of steps taken during each gait speed condition. Accuracy of two commonly used signal analysis methods was examined with several different time windows.
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Introduction: Falling causes long term disability and can even lead to death. Most falls occur during gait. Therefore improving gait stability might be beneficial for people at risk of falling. Recently arm swing has been shown to influence gait stability. However at present it remains unknown which mode of arm swing creates the most stable gait. Aim: To examine how different modes of arm swing affect gait stability. Method: Ten healthy young male subjects volunteered for this study. All subjects walked with four different arm swing instructions at seven different gait speeds. The Xsens motion capture suit was used to capture gait kinematics. Basic gait parameters, variability and stability measures were calculated. Results: We found an increased stability in the medio-lateral direction with excessive arm swing in comparison to normal arm swing at all gait speeds. Moreover, excessive arm swing increased stability in the anterior–posterior and vertical direction at low gait speeds. Ipsilateral and inphase arm swing did not differ compared to a normal arm swing. Discussion: Excessive arm swing is a promising gait manipulation to improve local dynamic stability. For excessive arm swing in the ML direction there appears to be converging evidence. The effect of excessive arm swing on more clinically relevant groups like the more fall prone elderly or stroke survivors is worth further investigating. Conclusion: Excessive arm swing significantly increases local dynamic stability of human gait.
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BackgroundExercise-induced fatigue is a common consequence of physical activities. Particularly in older adults, it can affect gait performance. Due to a wide variety in fatiguing protocols and gait parameters used in experimental settings, pooled effects are not yet clear. Furthermore, specific elements of fatiguing protocols (i.e., intensity, duration, and type of activity) might lead to different changes in gait parameters. We aimed to systematically quantify to what extent exercise-induced fatigue alters gait in community-dwelling older adults, and whether specific elements of fatiguing protocols could be identified.MethodsThis systematic review and meta-analysis was conducted in accordance with the PRISMA guidelines. In April 2023, PubMed, Web of Science, Scopus, Cochrane and CINAHL databases were searched. Two independent researchers screened and assessed articles using ASReview, Rayyan, and ROBINS-I. The extracted data related to spatio-temporal, stability, and variability gait parameters of healthy older adults (55 +) before and after a fatiguing protocol or prolonged physical exercise. Random-effects meta-analyses were performed on both absolute and non-absolute effect sizes in RStudio. Moderator analyses were performed on six clusters of gait parameters (Dynamic Balance, Lower Limb Kinematics, Regularity, Spatio-temporal Parameters, Symmetry, Velocity).ResultsWe included 573 effect sizes on gait parameters from 31 studies. The included studies reflected a total population of 761 older adults (57% female), with a mean age of 71 (SD 3) years. Meta-analysis indicated that exercise-induced fatigue affected gait with a standardized mean change of 0.31 (p < .001). Further analyses showed no statistical differences between the different clusters, and within clusters, the effects were non-uniform, resulting in an (indistinguishable from) zero overall effect within all clusters. Elements of fatiguing protocols like duration, (perceived) intensity, or type of activity did not moderate effects.DiscussionDue to the (mainly) low GRADE certainty ratings as a result of the heterogeneity between studies, and possible different strategies to cope with fatigue between participants, the only conclusion that can be drawn is that older adults, therapist, and researchers should be aware of the small to moderate changes in gait parameters as a result of exercise-induced fatigue.
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Background: Currently, the Ponseti method is the gold standard for treatment of clubfeet. For long-term func- tional evaluation of this method, gait analysis can be performed. Previous studies have assessed gait differences between Ponseti treated clubfeet and healthy controls. Research question/purpose: The aims of this systematic review were to compare the gait kinetics of Ponseti treated clubfeet with healthy controls and to compare the gait kinetics between clubfoot patients treated with the Ponseti method or surgically. Methods: A systematic search was performed in Embase, Medline Ovid, Web of Science, Scopus, Cochrane, Cinahl ebsco, and Google scholar, for studies reporting on gait kinetics in children with clubfeet treated with the Ponseti method. Studies were excluded if they only used EMG or pedobarography. Data were extracted and a risk of bias was assessed. Meta-analyses and qualitative analyses were performed. Results: Nine studies were included, of which five were included in the meta-analyses. The meta-analyses showed that ankle plantarflexor moment (95% CI -0.25 to -0.19) and ankle power (95% CI -0.89 to -0.60, were significantly lower in the Ponseti treated clubfeet compared to the healthy controls. No significant difference was found in ankle dorsiflexor and plantarflexor moment, and ankle power between clubfeet treated with surgery compared to the Ponseti method. Significance: Differences in gait kinetics are present when comparing Ponseti treated clubfeet with healthy controls. However, there is no significant difference between surgically and Ponseti treated clubfeet. These results give more insight in the possibilities of improving the gait pattern of patients treated for clubfeet.
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Background: Falls in stroke survivors can lead to serious injuries and medical costs. Fall risk in older adults can be predicted based on gait characteristics measured in daily life. Given the different gait patterns that stroke survivors exhibit it is unclear whether a similar fall-prediction model could be used in this group. Therefore the main purpose of this study was to examine whether fall-prediction models that have been used in older adults can also be used in a population of stroke survivors, or if modifications are needed, either in the cut-off values of such models, or in the gait characteristics of interest. Methods: This study investigated gait characteristics by assessing accelerations of the lower back measured during seven consecutive days in 31 non fall-prone stroke survivors, 25 fall-prone stroke survivors, 20 neurologically intact fall-prone older adults and 30 non fall-prone older adults. We created a binary logistic regression model to assess the ability of predicting falls for each gait characteristic. We included health status and the interaction between health status (stroke survivors versus older adults) and gait characteristic in the model. Results: We found four significant interactions between gait characteristics and health status. Furthermore we found another four gait characteristics that had similar predictive capacity in both stroke survivors and older adults. Conclusion: The interactions between gait characteristics and health status indicate that gait characteristics are differently associated with fall history between stroke survivors and older adults. Thus specific models are needed to predict fall risk in stroke survivors.
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