Standing balance test predicts the Berg Balance Scale score in patients with stroke using principal component analysis.

利用主成分分析法,站立平衡测试可以预测中风患者的 Berg 平衡量表评分。

阅读:10
作者:
A comprehensive analysis integrating kinematic, kinetic, and electromyographic data to evaluate balance impairments in patients with stroke is lacking. We investigated balance disparities in patients with balance impairment following stroke using principal component analysis (PCA). The complete waveforms of lower-limb-joint angles, centre of pressure, and muscle activity in 43 stroke patients during four Berg Balance Scale (BBS) standing balance tasks were analysed. Multiple regression analysis using principal components (PCs) was conducted to predict BBS scores. Thirteen patients had balance impairments (BBS score < 45). Significant differences in bilateral standing PCs were observed between patients with and without balance impairments during the standing balance tasks (p < 0.2). The strongest predictor of BBS score was the performance of the paretic leg during quiet standing with open eyes (p < 0.01). Key contributors to balance impairment included bilateral sagittal plane ankle and pelvic joint angles, bilateral vertical ground response forces, and paretic plantar-flexor activation across all standing tasks. These findings highlight that postural control of the paretic limb is a key determinant of balance ability, with distinct balance strategies observed across ability levels. Additionally, PCA effectively quantified balance impairments, revealing significant associations with Fugl-Meyer lower extremity, ankle joint range of motion, and strength. These results emphasize the role of sagittal plane postural control and plantar-flexor activation in stability and suggest that PCA may be a valuable tool for developing targeted rehabilitation strategies.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。