Gait variability in people with neurological disorders: A systematic review and meta-analysis

Moon, Yaejin; Sung, Jong Hun; An, Ruopeng; Hernandez, Manuel E.; Sosnoff, Jacob J.

doi:10.1016/j.humov.2016.03.010

Cited by 193 publications

(147 citation statements)

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“…This is consistent with previous reports of kinematic and kinetic changes of gait in older people (Brach et al 2008, Boyer et al 2017. Previous studies have also documented differences in gait between people with PD and healthy age-matched controls (Blin et al 1990, Hausdorff 2005, Hausdorff 2009, Moon et al 2016, Peterson & Horak 2016, which we did not observe in the current study. However, previous studies mainly detected PD-related gait differences by kinetic, kinematic and spatial gait parameters but less consistently in temporal gait parameters, which were assessed in the current study.…”

Section: Changes In Corticomuscular Control With Aging and Parkinson'supporting

confidence: 94%

“…Movement kinematics, including joint moments and powers at the ankle, and ground reaction forces, also change with ageing (Boyer et al 2017). PD gait is characterised by slowness, increased variability and impaired postural control (Blin et al 1990, Hausdorff 2005, Hausdorff 2009, Moon et al 2016, Peterson & Horak 2016. Many stride parameters are altered in people with PD compared to agematched controls, including decreased walking velocity, stride length, cadence, arm swing, head-trunk control and single support time (Cole et al 2010(Cole et al , 2011.…”

Section: Introductionmentioning

confidence: 99%

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Corticomuscular control of walking in older people and people with Parkinson’s disease

Roeder

Boonstra

Kerr

2019

Preprint

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Changes in human gait that result from ageing or neurodegenerative diseases are multifactorial. Here we assess the effects of age and Parkinson’s disease (PD) on corticospinal control in electrophysiological activity recorded during treadmill and overground walking. Electroencephalography (EEG) from 10 electrodes and electromyography (EMG) from two leg muscles were acquired from 22 healthy young, 24 healthy older and 20 adults with PD. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence were assessed for EEG from bilateral sensorimotor cortices and EMG from tibialis anterior muscles during the double support phase of the gait cycle. CMC and EMG power in the low beta band (13-21 Hz) was significantly decreased in older and PD participants compared to young people, but there was no difference between older and PD groups. Older and PD participants spent shorter time in the swing phase than young individuals. These findings indicate age-related changes in the temporal coordination of gait. The decrease in beta CMC suggests reduced cortical input to spinal motor neurons in older people during the double support phase. We also observed multiple changes in electrophysiological measures at high beta and low gamma frequencies during treadmill compared to overground walking, indicating task-dependent differences in corticospinal locomotor control.

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Section: Changes In Corticomuscular Control With Aging and Parkinson'supporting

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Corticomuscular control of walking in older people and people with Parkinson’s disease

Roeder

Boonstra

Kerr

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…While growing, children also learn to control their gait, and the magnitude of SI fluctuations decreases: CV reaches a minimal value of 0.015 [0.010 − 0.023] in AD group. This value is compatible with the meta-analysis conducted by Moon et al [25] reporting 6 All rights reserved. No reuse allowed without permission.…”

Section: Discussionsupporting

confidence: 92%

Added Value and Clinical Significance of Nonlinear Variability Indices of Walking Stride Interval in Neurodegenerative Diseases

Dierick¹,

Vandevoorde²,

Chantraine³

et al. 2020

Preprint

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Though self-paced walking is highly stereotyped, the stride interval fluctuates from one stride to the next around an average value with a measurable statistical variability. In clinical gait analysis, this variability is usually assessed with indices such the standard deviation or the coefficient of variation (CV). The aim of this study is to understand the added value that nonlinear indices of walking stride interval variability, such as Hurst exponent (H) and Minkowski fractal dimension (D), can provide in a clinical context and to suggest a clinical significance of these indices in the most common neurodegenerative diseases: Parkinson, Huntington, and amyotrophic lateral sclerosis. Although evidence have been accumulated that the stride interval organization at long range displays a more random, less autocorrelated, gait pattern in neurodegenerative diseases compared with young healthy individuals, it is today necessary to recompute CV, H, and D indices in a unified way and to take into account aging impact on these indices. In fact, computed nonlinear indices of variability are mainly dependent on stride interval time series length and algorithms used, making quantitative comparisons between different studies difficult or even impossible. Here, we recompute these indices from available stride interval time series, either coming from our lab or from online databases, or made available to us by the authors of previously conducted research. We confirm that both linear and nonlinear variability indices are relevant indicators of aging process and neurodegenerative diseases.

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“…Recent studies using instrumented carpets or 3d motion capture reported results indicating correlations between UHDRS TMS and stride length in a small cohort (n = 7) [9] and significant angular changes of the gait cycle (n = 30) [10]. Gait variability as a measure of regularity of gait and dynamic postural control seems to be increased in HD [8,9,11,12]. However, these monocentric studies should be interpreted with caution due to small cohorts examined.…”

Section: Introductionmentioning

confidence: 98%

Gait variability as digital biomarker of disease severity in Huntington’s disease

et al. 2020

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Background Impaired gait plays an important role for quality of life in patients with Huntington's disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments. Objective To objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particularly, gait parameters were correlated to the Unified Huntington's Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC). Methods Patients with manifest HD at two German sites (n = 43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age-and gender-matched controls performed a defined gait test (4 × 10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefficient of variance (CV). Results Stride length (− 15%) and gait velocity (− 19%) were reduced, while stride (+ 7%) and stance time (+ 2%) were increased in patients with HD. However, parameters reflecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416 ≤ r Sp ≤ 0.690). Objective gait variability parameters correlated with disease stage based upon TFC. Conclusions Sensor-based gait variability parameters were identified as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity.

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Gait variability in people with neurological disorders: A systematic review and meta-analysis

Cited by 193 publications

References 50 publications

Corticomuscular control of walking in older people and people with Parkinson’s disease

Corticomuscular control of walking in older people and people with Parkinson’s disease

Added Value and Clinical Significance of Nonlinear Variability Indices of Walking Stride Interval in Neurodegenerative Diseases

Gait variability as digital biomarker of disease severity in Huntington’s disease

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