Transcranial direct current stimulation facilitates backward walking training.

Backward walking training presents a great challenge to the physical and neural systems, which may result in an improvement in gait performance. Transcranial direct current electrical stimulation (tDCS), which can non-invasively enhance cortical activity, has been reported to strengthen corticomotor plasticity. We investigated whether excitatory tDCS over the primary motor cortex (M1) or the dorsolateral prefrontal cortex (DLPFC) enhances the effects of backward walking training in healthy participants. Thirty-six healthy participants (16 men and 20 women, mean age 21.3 ± 1.4 years) participated in this study. The participants were randomly assigned to one of the three tDCS groups (M1, DLPFC, and sham). They performed 5 min of backward walking training during 15 min of tDCS. We evaluated dual-task forward and backward walking performance before and after training. Both tDCS groups increased walking speed in the backward condition, but the DLPFC group increased the dual-task backward walking speed more than the M1 group. The M1 group showed decreased gait variability in dual-task backward walking, whereas the DLPFC group showed increased gait variability. Backward walking training combined with M1 stimulation may increase the backward walking speed by reducing gait variability. Backward walking training combined with DLPFC stimulation may prioritize walking speed over gait stability. Our results indicate that backward walking training combined with tDCS may be extended to other rehabilitation methods to improve gait performance.

Impact of distinct cognitive domains on gait variability in individuals with mild cognitive impairment and dementia.

BACKGROUND: Gait variability is a common feature in neurodegenerative diseases and has been linked to cognitive impairment. Despite this link, the influence of specific cognitive domains, such as memory, visual spatial skills, executive function, and verbal function on gait variability is not well-understood. OBJECTIVE: To investigate the predictive value of these specific cognitive domains on gait variability in people with mild cognitive impairment (MCI) and dementia during preferred and dual task walking. METHOD: One hundred and two participants with either MCI or dementia underwent a comprehensive cognitive assessment and completed preferred and dual-task walking trials on a pressure-sensing walkway. Gait variability was assessed using the PKMAS software. Lower extremity function was evaluated with a self-reported validated scale. RESULTS: Our findings indicate that only visual spatial abilities had a moderate predictive value on gait variability [F (1, 78) = 17.30, p < 0.01, r = 0.43], both in preferred pace walking (70% direct effect) and dual-task walking (90% direct effect) (p's < 0.05). Additionally, lower extremity functional skills had a significant indirect effect (30%) on gait variability in preferred walking contexts. CONCLUSION: For individuals diagnosed with MCI or dementia, increased gait variability may be driven by deficits in visual spatial processing. An increased understanding of the role of visual spatial processing in gait variability can aid in the assessment and management of individuals with MCI or dementia, potentially leading to targeted interventions to improve mobility and safety.

IMU-Based Real-Time Estimation of Gait Phase Using Multi-Resolution Neural Networks.

This work presents a real-time gait phase estimator using thigh- and shank-mounted inertial measurement units (IMUs). A multi-rate convolutional neural network (CNN) was trained to estimate gait phase for a dataset of 16 participants walking on an instrumented treadmill with speeds varying between 0.1 to 1.9 m/s, and conditions such as asymmetric walking, stop-start, and sudden speed changes. One-subject-out cross-validation was used to assess the robustness of the estimator to the gait patterns of new individuals. The proposed model had a spatial root mean square error of 5.00±1.65%, and a temporal mean absolute error of 2.78±0.97% evaluated at the heel strike. A second cross-validation was performed to show that leaving out any of the walking conditions from the training dataset did not result in significant performance degradation. A 2-sample Kolmogorov-Smirnov test showed that there was no significant increase in spatial or temporal error when testing on the abnormal walking conditions left out of the training set. The results of the two cross-validations demonstrate that the proposed model generalizes well across new participants, various walking speeds, and gait patterns, showcasing its potential for use in investigating patient populations with pathological gaits and facilitating robot-assisted walking.

Adaptive Bayesian sum of trees model for covariate-dependent spectral analysis.

This paper introduces a flexible and adaptive nonparametric method for estimating the association between multiple covariates and power spectra of multiple time series. The proposed approach uses a Bayesian sum of trees model to capture complex dependencies and interactions between covariates and the power spectrum, which are often observed in studies of biomedical time series. Local power spectra corresponding to terminal nodes within trees are estimated nonparametrically using Bayesian penalized linear splines. The trees are considered to be random and fit using a Bayesian backfitting Markov chain Monte Carlo (MCMC) algorithm that sequentially considers tree modifications via reversible-jump MCMC techniques. For high-dimensional covariates, a sparsity-inducing Dirichlet hyperprior on tree splitting proportions is considered, which provides sparse estimation of covariate effects and efficient variable selection. By averaging over the posterior distribution of trees, the proposed method can recover both smooth and abrupt changes in the power spectrum across multiple covariates. Empirical performance is evaluated via simulations to demonstrate the proposed method's ability to accurately recover complex relationships and interactions. The proposed methodology is used to study gait maturation in young children by evaluating age-related changes in power spectra of stride interval time series in the presence of other covariates.

Prediction of injurious falls in older adults using digital gait biomarkers extracted from large-scale wrist sensor data.

OBJECTIVES: To determine whether digital gait biomarkers captured by a wrist-worn device can predict injurious falls in older people and to develop a multivariable injurious fall prediction model. DESIGN: Population-based longitudinal cohort study. SETTING AND PARTICIPANTS: Community-dwelling participants of the UK Biobank study aged 65 and older (n = 32,619) in the United Kingdom. METHODS: Participants were assessed at baseline on daily-life walking speed, quality, quantity and distribution using wrist-worn accelerometers for up to 7 days. Univariable and multivariable Cox proportional hazard regression models were used to analyse the associations between these parameters and injurious falls for up to 9 years. RESULTS: Five percent of the participants (n = 1,627) experienced at least one fall requiring medical attention over a mean of 7.0 ± 1.1 years. Daily-life walking speed, gait quality, quantity of walking and distribution of daily walking were all significantly associated with the incidence of injurious falls (P < 0.05). After adjusting for sociodemographics, lifestyle factors, comorbidities, handgrip strength and reaction time; running duration, total step counts and usual walking speed were identified as independent and significant predictors of falls (P < 0.01). These associations were consistent in those without a history of previous fall injuries. In contrast, step regularity was the only risk factor for those with a previous fall history after adjusting for covariates. CONCLUSIONS: Daily-life gait speed, quantity and quality, derived from wrist-worn sensors, are significant predictors of injurious falls in older people. These digital gait biomarkers could potentially be used to identify fall risk in screening programs and integrated into fall prevention strategies.

Physiological and Cognitive Determinants of Gait Variability of Asian Population: The Yishun Study.

INTRODUCTION: Gait variability is associated with frailty, dementia, and falls. Studies on the association of physiological and cognitive factors with gait variability have seldom included middle-aged adults, even though these adults already experienced loss of muscular strength and postural stability. This study aimed a) to examine and compare the trend of gait variability in men and women, across the adult age spectrum, and b) to identify and compare the contributions of physiological and cognitive factors to gait variability. METHODS: This was a population-based cross-sectional study at a single center. A random sample of 507 community-dwelling, well-functioning adults aged 21-90 years were studied. Cognition was measured using the Repeatable Battery for the Assessment of Neuropsychological Status. Physiological factors examined included visual contrast sensitivity (VCS), postural sway, hand reaction time, handgrip strength (HGS), knee extensor strength, and gait variability (coefficient of variation [CoV]). Multivariable regression models were used to examine the association between physiological and cognitive performance with gait CoV. RESULTS: Women walked with greater stride width CoV (p < 0.01) and double support time (DST) CoV (p < 0.01) than men. The stride width (p = 0.01) and DST variability (p = 0.03) were significantly higher in older men as compared to men in younger age-groups. Gait speed accounted for most of the gait CoV variances and attenuated the effects of physiological performance and/or attention cognition on most gait variability, except for CoV of DST and stride width. Adults with better VCS (ß = -0.19), faster hand reaction (ß = 0.12), and greater HGS (ß = -0.15) had lower variability in step length. CONCLUSION: The trends of stride width CoV and DST CoV across adult age spectrum were different between men and women. Greater stride width variability was partly attributed to greater HGS, possibly to better control lateral stability during walking. Physiological factors outweigh cognition in regulating most of the gait CoV in this study. They are modifiable and potential targets for healthy aging program.

Predictors of incident reversible and potentially reversible cognitive frailty among Taiwanese older adults.

BACKGROUND: Few studies emphasize on predictors of incident cognitive frailty (CF) and examine relationships between various gait characteristics and CF. Therefore, we conducted a 2-year prospective study to investigate potential predictors, including gait characteristics, of incident reversible CF (RCF) and potentially RCF (PRCF) among Taiwanese older adults. METHODS: Eligible participants were individuals aged ≥ 65 years, who could ambulate independently, and did not have RCF/PRCF at the baseline. The baseline assessment collected information on physical frailty and cognitive measures, in addition to sociodemographic and lifestyle characteristics, preexisting comorbidities and medications, gait characteristics, Tinetti's balance, balance confidence as assessed by Activities-specific Balance Confidence (ABC) scale, and the depressive status as assessed by the Geriatric Depression Scale. The Mini-Mental State Examination (MMSE), Mattis Dementia Rating Scale, and Digit Symbol Substitution Test were used to evaluate cognitive functions. Incident RCF and PRCF were ascertained at a 2-year follow-up assessment. RESULTS: Results of the multinomial logistic regression analysis showed that incident RCF was significantly associated with older age (odds ratio [OR] = 1.05) and lower ABC scores (OR = 0.97). Furthermore, incident PRCF was significantly associated with older age (OR = 1.07), lower ABC scores (OR = 0.96), the presence of depression (OR = 3.61), lower MMSE scores (OR = 0.83), slower gait velocity (OR = 0.97), and greater double-support time variability (OR = 1.09). CONCLUSIONS: Incident RCF was independently associated with older age and lower balance confidence while incident PRCF independently associated with older age, reduced global cognition, the presence of depression, slower gait velocity, and greater double-support time variability. Balance confidence was the only modifiable factor associated with both incident RCF and PRCF.

Vertical Ground Reaction Forces in Parkinson's Disease: A Speed-Matched Comparative Analysis with Healthy Subjects.

This study aimed to investigate and compare the vertical Ground Reaction Forces (vGRFs) of patients with Parkinson's Disease (PwPD) and healthy subjects (HS) when the confounding effect of walking speed was absent. Therefore, eighteen PwPD and eighteen age- and linear walking speed-matched HS were recruited. Using plantar pressure insoles, participants walked along linear and curvilinear paths at self-selected speeds. Interestingly, PwPD exhibited similar walking speed to HS during curvilinear trajectories (p = 0.48) and similar vGRF during both linear and curvilinear paths. In both groups, vGRF at initial contact and terminal stance was higher during linear walking, while vGRF at mid-stance was higher in curvilinear trajectories. Similarly, the time to peak vGRF at each phase showed no significant group differences. The vGRF timing variability was different between the two groups, particularly at terminal stance (p < 0.001). In conclusion, PwPD and HS showed similar modifications in vGRF and a similar reduction in gait speed during curvilinear paths when matched for linear walking speed. This emphasized the importance of considering walking speed when assessing gait dynamics in PwPD. This study also suggests the possibility of the variability of specific temporal measures in differentiating the gait patterns of PwPD versus those of HS, even in the early stages of the disease.

Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease.

The aim of this study was to assess the ability of multiscale sample entropy (MSE), refined composite multiscale entropy (RCMSE), and complexity index (CI) to characterize gait complexity through trunk acceleration patterns in subjects with Parkinson's disease (swPD) and healthy subjects, regardless of age or gait speed. The trunk acceleration patterns of 51 swPD and 50 healthy subjects (HS) were acquired using a lumbar-mounted magneto-inertial measurement unit during their walking. MSE, RCMSE, and CI were calculated on 2000 data points, using scale factors (τ) 1-6. Differences between swPD and HS were calculated at each τ, and the area under the receiver operating characteristics, optimal cutoff points, post-test probabilities, and diagnostic odds ratios were calculated. MSE, RCMSE, and CIs showed to differentiate swPD from HS. MSE in the anteroposterior direction at τ4 and τ5, and MSE in the ML direction at τ4 showed to characterize the gait disorders of swPD with the best trade-off between positive and negative posttest probabilities and correlated with the motor disability, pelvic kinematics, and stance phase. Using a time series of 2000 data points, a scale factor of 4 or 5 in the MSE procedure can yield the best trade-off in terms of post-test probabilities when compared to other scale factors for detecting gait variability and complexity in swPD.

Gait disorders in CKD patients: muscle wasting or cognitive impairment? A cross-sectional pilot study to investigate gait signatures in Stage 1-5 CKD patients.

BACKGROUND: Instrumental gait analysis in nephrology is widely neglected, although patients with chronic kidney disease (CKD) show brain changes due to cerebrovascular disease and metabolic disorders that can potentially influence gait quality. Our study assesses the association between CKD stages and gait parameters, to understand the prevalent status of brain related gait parameters (i.e. variability) and of performance related parameters (i.e. gait speed, stride length). We hypothesize that gait changes are detectable already in early stages of CKD. METHODS: Forty-five participants distributed in 5 CKD severity groups underwent an instrumental gait analysis via a triaxial accelerometer affixed to the lower trunk under single- and dual-task conditions. In addition to spatio-temporal parameters, variability and dual-task cost of gait were extracted. A battery of clinical assessments was conducted with the aim of helping to better explain the findings of the gait analysis. A correlation analysis was made to investigate a linear relation between gait parameters and CKD severity. RESULTS: Statistically significant correlations (Pearson correlation coefficient) with CKD severity were found for gait speed (p < 0.01, r = -0.55, 95% CI [-0.73;-0.30]), stride length ( p < 0.01, r = -0.40, 95% CI [-0.62;-0.12]), step length (p < 0.01, r = -0.41, 95% CI [-0.63;-0.13], coefficient of variance (CV) of step length (p = 0.01, r = 0.36, 95% CI [0.08;0.59]), gait regularity (p < 0.01, r = -0.38, 95% CI [-0.61;-0.10]), dual-task cost of gait speed (p < 0.01, r = 0.40, 95% CI [0.13;0.62]) and dual-task cost of stride time (p = 0.03, r = 0.32, 95% CI [0.03;0.57]). Adjustment for age and gender confirmed all results except for gait regularity. With increasing severity of renal failure, Handgrip strength, Time for the Expanded Timed Get Up and Go test, executive functions, haemoglobin, and haematocrit, worsen. CONCLUSIONS: The correlation of CKD severity with spatio-temporal parameters (performance indices mainly relatable to peripheral functionality) and with variability of gait (related to central factors) supported by the results of the clinical assessments, suggests that gait disturbance in CKD patients is not only due to metabolic factors that lead to muscle wasting, but also to brain changes that affect motor control. This suggests that the treatment of renal disease should include cognitive aspects in addition to metabolic and functional factors.

Gait variability is sensitive to detect Parkinson's disease patients at high fall risk.

BACKGROUND: Gait disturbance is an important risk factor for falls in Parkinson's disease (PD). Using wearable sensors, we can obtain the spatiotemporal parameters of gait and calculate the gait variability. This prospective study aims to objectively evaluate the gait characteristics of PD fallers, and further explore the relationship between spatiotemporal parameters of gait, gait variability and falls in PD patients followed for six months. METHODS: Fifty-one PD patients were enrolled in this study. A seven-meter timed up and go test was performed. Gait characteristics were determined by a gait analysis system. Patients were followed monthly by telephone until the occurrence of falls or till the end of six months. The patients were categorized into fallers and non-fallers based on whether fell during the follow-up period. Gait parameters were compared between two groups, and binary logistic regression was used to establish the falls prediction model. In the receiver-operating characteristic curve, area under the curve (AUC) was utilized to evaluate the prediction accuracy of each indicator. RESULTS: All subjects completed the follow-up, and 14 (27.5%) patients reported falls. PD fallers had greater gait variability. The range of motion of the trunk in sagittal plane variability was an independent risk factor for falls and achieved moderate prediction accuracy (AUC = 0.751), and the logistic regression model achieved a good accuracy of falls prediction (AUC = 0.838). CONCLUSIONS: Increased gait variability is a significant feature of PD fallers and is more sensitive to detect PD patients at high risk of falls than spatiotemporal parameters.

Gait Variability to Phenotype Common Orthopedic Gait Impairments Using Wearable Sensors.

Mobility impairments are a common symptom of age-related degenerative diseases. Gait features can discriminate those with mobility disorders from healthy individuals, yet phenotyping specific pathologies remains challenging. This study aims to identify if gait parameters derived from two foot-mounted inertial measurement units (IMU) during the 6 min walk test (6MWT) can phenotype mobility impairment from different pathologies (Lumbar spinal stenosis (LSS)-neurogenic diseases, and knee osteoarthritis (KOA)-structural joint disease). Bilateral foot-mounted IMU data during the 6MWT were collected from patients with LSS and KOA and matched healthy controls (N = 30, 10 for each group). Eleven gait parameters representing four domains (pace, rhythm, asymmetry, variability) were derived for each minute of the 6MWT. In the entire 6MWT, gait parameters in all four domains distinguished between controls and both disease groups; however, the disease groups demonstrated no statistical differences, with a trend toward higher stride length variability in the LSS group (p = 0.057). Additional minute-by-minute comparisons identified stride length variability as a statistically significant marker between disease groups during the middle portion of 6WMT (3rd min: p ≤ 0.05; 4th min: p = 0.06). These findings demonstrate that gait variability measures are a potential biomarker to phenotype mobility impairment from different pathologies. Increased gait variability indicates loss of gait rhythmicity, a common feature in neurologic impairment of locomotor control, thus reflecting the underlying mechanism for the gait impairment in LSS. Findings from this work also identify the middle portion of the 6MWT as a potential window to detect subtle gait differences between individuals with different origins of gait impairment.

Effects of lower leg muscle quality on gait variability in community-dwelling older and healthy young adults.

[Purpose] We aimed to determine whether lower leg muscle echo intensity, an indicator of muscle quality, is a useful predictor of gait variability after examining the relationship between physical activity and gait variability in community-dwelling older and healthy young adults. [Participants and Methods] This study comprised two tasks. In the first task, 18 older and 25 young adults were included as participants. We examined the relationship between the amount of physical activity and gait variability in both groups. In the second task, muscle echo intensity related to gait variability in each group was measured using ultrasound echoes after identifying common factors related to gait variability in 19 older and 19 younger adults, and trends were compared. [Results] In the first task, gait variability was significantly higher in the younger group than in the older group. A significant negative correlation was found between the amount of physical activity and gait variability in both groups. In the second task, multiple regression analysis was performed for gait variability, and lower leg muscle echo intensity was identified as a significant factor. There was no difference in the correlation coefficient between gait variability and lower leg muscle echo intensity between the two groups. [Conclusion] Lower leg muscle quality was one of the causes of gait variability, suggesting that it is a useful predictor of gait sway status.

The Associations Between Grey Matter Volume Covariance Patterns and Gait Variability-The Tasmanian Study of Cognition and Gait.

Greater gait variability predicts dementia. However, little is known about the neural correlates of gait variability. The aims of this study were to determine (1) grey matter volume covariance patterns associated with gait variability and (2) whether these patterns were associated with specific cognitive domains. Participants (n = 351; mean age 71.9 ± 7.1) were randomly selected from the Southern Tasmanian electoral roll. Step time, step length, step width and double support time were measured using an electronic walkway. Gait variability was calculated as the standard deviation of all steps for each gait measure. Voxel-based morphometry and multivariate covariance-based analyses were used to identify grey matter patterns associated with each gait variability measure. The individual expressions of grey matter patterns were correlated with processing speed, memory, executive and visuospatial functions. The grey matter covariance pattern of double support time variability included frontal, medial temporal, anterior cingulate, insula, cerebellar and striatal regions. Greater expression of this pattern was correlated with poorer performance in all cognitive functions (p < 0.001). The covariance pattern of step length variability included frontal, temporal, insula, occipital and cerebellar regions and was correlated with all cognitive functions (p < 0.05), except memory (p = 0.76). The covariance pattern of step width variability was limited to the cerebellum and correlated only with memory (p = 0.047). No significant pattern was identified for step time variability. In conclusion, different grey matter covariance patterns were associated with individual gait variability measures. These patterns were also correlated with specific cognitive functions, suggesting common neural networks may underlie both gait and cognition.

Effects of a multimodal exercise intervention on physical and cognitive functions in patients with chronic low back pain (MultiMove): study protocol for a randomized controlled trial.

BACKGROUND: Chronic low back pain (CLBP) is a common medical condition in adults over the age of 50. It is associated with severe disability, ranging from physical impairments to psychosocial distress. Since current treatments provide only small to moderate short-term effects, alternative interventions are required, whereby guidelines recommended multimodal approaches. Dancing can be considered as an inherently multimodal approach, as it requires a combination of physical and cognitive functions. Furthermore, it has already been applied effectively in neurorehabilitation. Therefore, it seems promising to merge a dance-therapeutic component together with motor-cognitive, strength and flexibility exercises in a novel multimodal treatment (MultiMove) to target the impaired everyday mobility and cognition of CLBP patients. The aim of this study is to analyse specific physical, cognitive and psychosocial effects of MultiMove in CLBP patients. METHODS: A prospective, two-arm, single-blinded, randomized controlled trial will be conducted with an estimated sample size of 100 CLBP patients, assigned to either the MultiMove group or a control group. The intervention group will receive MultiMove twice a week for 60 min each over a period of 12 weeks. The primary outcome will be the mobility and function of the lower extremities assessed by the Timed Up-and-Go Test. Secondary outcomes comprise further physical and physiological functions (e.g. gait variability and haemodynamic response in the prefrontal cortex during motor-cognitive dual tasks), subjective health state (e.g. disability in daily life), executive functions (e.g. cognitive flexibility) and psychosocial aspects (e.g. kinesiophobia). Measures will be taken at baseline, after the intervention and at a 12-week follow-up. It is assumed that MultiMove improves the mentioned outcome parameters. DISCUSSION: The combined assessment of changes in physical and cognitive functions as well as neuropsychological aspects in response to MultiMove will allow a better understanding of the motor-cognitive adaptations induced by multimodal exercises in CLBP patients. The specific conclusions will lead to recommendations for the conservative treatment approach in this clinically relevant patient group. TRIAL REGISTRATION: German Clinical Trial Register (ID: DRKS00021696 / 10.07.2020), https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00021696.

Changes in Mediolateral Postural Control Mechanisms During Gait After Total Knee Arthroplasty.

BACKGROUND: Patients who have total knee arthroplasty (TKA) likely suffer from decreased postural stability because of postoperative changes in musculoskeletal structure and loss of proprioception. The purpose of this experimental biomechanical study was to determine if patients who have TKA improve their dynamic postural control during walking after TKA as compared with before TKA. The secondary purpose was to assess changes in postural control between post-TKA patients and healthy controls. METHODS: Twenty-three patients who had primary knee osteoarthritis scheduled to undergo unilateral or bilateral TKA were prospectively enrolled. Each patient was tested at 3 months, 6 months, and 12 months after TKA. Ten healthy controls matched for age, sex, and body mass index were selected from a database of previous healthy volunteers without knee osteoarthritis. Ten Vicon cameras and four AMTI force platforms were used to collect the marker and center of pressure (COP) data while participants performed gait. RESULTS: Initial improvement in the double stance ratio was found by 6 months after TKA compared with before TKA. Patients showed improved postural control as evidenced by a faster mediolateral COP velocity and decreased double stance ratio at 12-month post-TKA compared with pre-TKA (P < .05). However, patients who underwent TKA exhibited limited ability to maintain consistent COP movement during walking with increased variability in COP parameters as compared with controls (P < .05). CONCLUSION: Patients exhibited improvement in dynamic postural control after TKA with time, but had higher variability in COP parameters during gait than controls. It is possible that therapy aimed to improve proprioceptive balance after TKA may improve dynamic postural control.

Evaluation of the Validity and Reliability of Connected Insoles to Measure Gait Parameters in Healthy Adults.

The continuous, accurate and reliable estimation of gait parameters as a measure of mobility is essential to assess the loss of functional capacity related to the progression of disease. Connected insoles are suitable wearable devices which allow precise, continuous, remote and passive gait assessment. The data of 25 healthy volunteers aged 20 to 77 years were analysed in the study to validate gait parameters (stride length, velocity, stance, swing, step and single support durations and cadence) measured by FeetMe® insoles against the GAITRite® mat reference. The mean values and the values of variability were calculated per subject for GAITRite® and insoles. A t-test and Levene's test were used to compare the gait parameters for means and variances, respectively, obtained for both devices. Additionally, measures of bias, standard deviation of differences, Pearson's correlation and intraclass correlation were analysed to explore overall agreement between the two devices. No significant differences in mean and variance between the two devices were detected. Pearson's correlation coefficients of averaged gait estimates were higher than 0.98 and 0.8, respectively, for unipedal and bipedal gait parameters, supporting a high level of agreement between the two devices. The connected insoles are therefore a device equivalent to GAITRite® to estimate the mean and variability of gait parameters.

Gait variability across neurodegenerative and cognitive disorders: Results from the Canadian Consortium of Neurodegeneration in Aging (CCNA) and the Gait and Brain Study.

INTRODUCTION: Gait impairment is common in neurodegenerative disorders. Specifically, gait variability-the stride-to-stride fluctuations in distance and time-has been associated with neurodegeneration and cognitive impairment. However, quantitative comparisons of gait impairments across the cognitive spectrum of dementias have not been systematically investigated. METHODS: Older adults (N = 500) with subjective cognitive impairment, Parkinson disease (PD), mild cognitive impairment (MCI), PD-MCI, Alzheimer's disease (AD), PD-dementia, Lewy body dementia, and frontotemporal dementia, as well cognitive normal controls, who were assessed for their gait and cognitive performance. RESULTS: Factor analyses grouped 11 quantitative gait parameters and identified four independent gait domains: rhythm, pace, variability, and postural control, for group comparisons and classification analysis. Among these domains, only high gait variability was associated with lower cognitive performance and accurately discriminated AD from other neurodegenerative and cognitive conditions. DISCUSSION: Our findings indicate that high gait variability is a marker of cognitive-cortical dysfunction, which can help to identify Alzheimer's disease dementia.

Test-Retest Reliability and the Effects of Walking Speed on Stride Time Variability During Continuous, Overground Walking in Healthy Young Adults.

Studies have investigated the reliability and effect of walking speed on stride time variability during walking trials performed on a treadmill. The objective of this study was to investigate the reliability of stride time variability and the effect of walking speed on stride time variability, during continuous, overground walking in healthy young adults. Participants completed: (1) 2 walking trials at their preferred walking speed on 1 day and another trial 2 to 4 days later and (2) 1 trial at their preferred walking speed, 1 trial approximately 20% to 25% faster than their preferred walking speed, and 1 trial approximately 20% to 25% slower than their preferred walking speed on a separate day. Data from a waist-mounted accelerometer were used to determine the consecutive stride times for each trial. The reliability of stride time variability outcomes was generally poor (intraclass correlations: .167-.487). Although some significant differences in stride time variability were found between the preferred walking speed, fast, and slow trials, individual between-trial differences were generally below the estimated minimum difference considered to be a real difference. The development of a protocol to improve the reliability of stride time variability outcomes during continuous, overground walking would be beneficial to improve their application in research and clinical settings.

Gait Assessment in College Athletes: Do Concussion History, Symptoms, Gender, and Type of Sport Matter?

CONTEXT: Though previous research has focused on examining the effects of concussion history using a dual-task paradigm, the influence of factors like symptoms (unrelated to concussion), gender, and type of sport on gait in college athletes is unknown. OBJECTIVE: To examine the effect of concussion history, symptoms, gender, and type of sport (noncontact/limited contact/contact) individually on gait among college athletes. DESIGN: Exploratory cross-sectional study. SETTING: Laboratory. PARTICIPANTS: In total, 98 varsity athletes (age, 18.3 [1.0] y; height, 1.79 [0.11] m; mass, 77.5 [19.2] kg; 27 with concussion history, 58 reported at least one symptom, 44 females; 8 played noncontact sports and 71 played contact sports) walked under single- and dual-task (walking while counting backward by 7) conditions. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Dual-task cost (DTC; % difference between single task and dual task) of gait speed, cadence, step length and width, percentage of swing and double-support phases, symptom score, and total symptom severity score. Independent samples t tests and 1-way analysis of variance were conducted (α value = .05). RESULTS: Self-reported concussion history resulted in no significant differences (P > .05). Those who reported symptoms at testing time showed significantly greater DTC of step length (mean difference [MD], 2.7%; 95% confidence interval [CI], 0.3% to 5.1%; P = .012), % of swing phase (MD, 1.0%; 95% CI, -0.2 to 2.1%; P = .042), and % of double-support phase (MD, 3.9%; 95% CI, 0.2% to 7.8%; P = .019). Females demonstrated significantly higher DTC of gait speed (MD, 5.3%; 95% CI, 1.3% to 9.3%; P = .005), cadence (MD, 4.0%; 95% CI, 1.4% to 6.5%; P = .002), % of swing phase (MD, 1.2%; 95% CI, 0.1% to 2.3%; P = .019), and % of double-support phase (MD, 4.1%; 95% CI, 0.4% to 7.9%; P = .018). Noncontact sports athletes had significantly greater step width DTC than contact sports athletes (MD, 14.2%; 95% CI, 0.9% to 27.6%; P = .032). CONCLUSIONS: Reporting symptoms at testing time may influence gait under dual-task conditions. Additionally, female athletes showed more gait changes during a dual task. Sports medicine professionals should be aware that these variables, while unrelated to injury, may affect an athlete's gait upon analysis.