Journal of Movement Disorders

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Optimal measuring height and validation of 2D-LiDAR based analysis system for spatiotemporal gait parameters: Seungki Woo, Chaewon Shin, Min Young Kim; Received June 14, 2024 Accepted August 21, 2024 Published online August 21, 2024; DOI: https://doi.org/10.14802/jmd.24134 [Accepted]

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Original Articles

Spatiotemporal Gait Parameters in Adults With Premanifest and Manifest Huntington’s Disease: A Systematic Review: Sasha Browning, Stephanie Holland, Ian Wellwood, Belinda Bilney; J Mov Disord. 2023;16(3):307-320. Published online August 10, 2023; DOI: https://doi.org/10.14802/jmd.23111

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Abstract PDF Supplementary Material: Objective
To systematically review and critically evaluate literature on spatiotemporal gait deviations in individuals with premanifest and manifest Huntington’s Disease (HD) in comparison with healthy cohorts.
Methods
We conducted a systematic review, guided by the Joanna Briggs Institute’s Manual for Evidence Synthesis and pre-registered with the International Prospective Register of Systematic Reviews. Eight electronic databases were searched. Studies comparing spatiotemporal footstep parameters in adults with premanifest and manifest HD to healthy controls were screened, included and critically appraised by independent reviewers. Data on spatiotemporal gait changes and variability were extracted and synthesised. Meta-analysis was performed on gait speed, cadence, stride length and stride length variability measures.
Results
We screened 2,721 studies, identified 1,245 studies and included 25 studies (total 1,088 participants). Sample sizes ranged from 14 to 96. Overall, the quality of the studies was assessed as good, but reporting of confounding factors was often unclear. Meta-analysis found spatiotemporal gait deviations in participants with HD compared to healthy controls, commencing in the premanifest stage. Individuals with premanifest HD walk significantly slower (-0.17 m/s; 95% confidence interval [CI] [-0.22, -0.13]), with reduced cadence (-6.63 steps/min; 95% CI [-10.62, -2.65]) and stride length (-0.09 m; 95% CI [-0.13, -0.05]). Stride length variability was also increased in premanifest cohorts by 2.18% (95% CI [0.69, 3.68]), with these changes exacerbated in participants with manifest disease.
Conclusion
Findings suggest individuals with premanifest and manifest HD display significant spatiotemporal footstep deviations. Clinicians could monitor individuals in the premanifest stage of disease for gait changes to identify the onset of Huntington’s symptoms.

Quantitative Gait Analysis in Patients with Huntington’s Disease: Seon Jong Pyo, Hanjun Kim, Il Soo Kim, Young-Min Park, Mi-Jung Kim, Hye Mi Lee, Seong-Beom Koh; J Mov Disord. 2017;10(3):140-144. Published online August 31, 2017; DOI: https://doi.org/10.14802/jmd.17041

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Objective
Gait disturbance is the main factor contributing to a negative impact on quality of life in patients with Huntington’s disease (HD). Understanding gait features in patients with HD is essential for planning a successful gait strategy. The aim of this study was to investigate temporospatial gait parameters in patients with HD compared with healthy controls.
Methods
We investigated 7 patients with HD. Diagnosis was confirmed by genetic analysis, and patients were evaluated with the Unified Huntington’s Disease Rating Scale (UHDRS). Gait features were assessed with a gait analyzer. We compared the results of patients with HD to those of 7 age- and sex-matched normal controls.
Results
Step length and stride length were decreased and base of support was increased in the HD group compared to the control group. In addition, coefficients of variability for step and stride length were increased in the HD group. The HD group showed slower walking velocity, an increased stance/swing phase in the gait cycle and a decreased proportion of single support time compared to the control group. Cadence did not differ significantly between groups. Among the UHDRS subscores, total motor score and total behavior score were positively correlated with step length, and total behavior score was positively correlated with walking velocity in patients with HD.
Conclusion
Increased variability in step and stride length, slower walking velocity, increased stance phase, and decreased swing phase and single support time with preserved cadence suggest that HD gait patterns are slow, ataxic and ineffective. This study suggests that quantitative gait analysis is needed to assess gait problems in HD.

Citations

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P. Stepanova, V. Srinivasan, D. Lindholm, M. H. Voutilainen
Scientific Reports.2020;[Epub] CrossRef
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PLOS ONE.2020; 15(12): e0243052. CrossRef
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Kartikay Gupta, Aayushi Khajuria, Niladri Chatterjee, Pradeep Joshi, Deepak Joshi
Health and Technology.2019; 9(4): 547. CrossRef
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ACS Chemical Neuroscience.2019; 10(9): 3969. CrossRef
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