| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2025-12-18 |
| タイトル |
|
|
タイトル |
Modeling the Heterogeneity of Post-Stroke Gait Control in Free-Living Environments Using a Personalized Causal Network |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
Bayes theorem |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
cluster analysis |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
gait control |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
gait speed |
| キーワード |
|
|
言語 |
en |
|
主題Scheme |
Other |
|
主題 |
stroke |
| 資源タイプ |
|
|
資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
|
資源タイプ |
journal article |
| 著者 |
Nishi, Yuki
Ikuno, Koki
Takamura, Yusaku
Minamikawa, Yuji
Morioka, Shu
|
| 抄録 |
|
|
内容記述タイプ |
Abstract |
|
内容記述 |
Post-stroke gait control is a complex, often fail to account for the heterogeneity and continuity of gait in existing gait models. Precisely evaluating gait speed adjustability and gait instability in free-living environments is important to understand how individuals with post-stroke gait dysfunction approach diverse environments and contexts. This study aimed to explore individual causal interactions in the free-living gait control of persons with stroke. To this end, fifty persons with stroke wore an accelerometer on the fifth lumbar vertebra (L5) for 24 h in a free-living environment. Individually directed acyclic graphs (DAGs) were generated based on the spatiotemporal gait parameters at contemporaneous and temporal points calculated from the acceleration data. Spectral clustering and Bayesian model comparison were used to characterize the DAGs. Finally, the DAG patterns were interpreted via Bayesian logistic analysis. Spectral clustering identified three optimal clusters from the DAGs. Cluster 1 included persons with moderate stroke who showed high gait asymmetry and gait instability and primarily adjusted gait speed based on cadence. Cluster 2 included individuals with mild stroke who primarily adjusted their gait speed based on step length. Cluster 3 comprised individuals with mild stroke who primarily adjusted their gait speed based on both step length and cadence. These three clusters could be accurately classified based on four variables: Ashman’s D for step velocity, Fugl-Meyer Assessment, step time asymmetry, and step length. The diverse DAG patterns of gait control identified suggest the heterogeneity of gait patterns and the functional diversity of persons with stroke. Understanding the theoretical interactions between gait functions will provide a foundation for highly tailored rehabilitation. |
|
言語 |
en |
| 書誌情報 |
en : IEEE Transactions on Neural Systems and Rehabilitation Engineering
巻 32,
p. 3522-3530,
発行日 2024-09-11
|
| 出版者 |
|
|
出版者 |
IEEE |
|
言語 |
en |
| ISSN |
|
|
収録物識別子タイプ |
ISSN |
|
収録物識別子 |
1534-4320 |
| DOI |
|
|
関連タイプ |
isIdenticalTo |
|
|
識別子タイプ |
DOI |
|
|
関連識別子 |
https://doi.org/10.1109/TNSRE.2024.3457770 |
| 権利 |
|
|
権利情報 |
© 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ |
|
言語 |
en |
| 著者版フラグ |
|
|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| 引用 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, pp.3522-3530; 2024 |
|
言語 |
en |
IEEETNSRE32_3522.pdf (2.3 MB)
