利用动态稳定性指标评估慢性前庭综合征患者的不稳定性。

IF 2.6 4区 医学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Yingnan Ma, Xing Gao, Li Wang, Ziyang Lyu, Fei Shen, Haijun Niu
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引用次数: 0

摘要

步态异常在慢性前庭综合征(CVS)患者中很常见,CVS 患者的稳定性分析和步态特征识别对诊断 CVS 具有临床意义。本研究探讨了用于评估 CVS 患者步态不稳定性的二维动态稳定性指标。CVS患者的质心加速度(COMa)峰值明显快于对照组(p
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Evaluation of instability in patients with chronic vestibular syndrome using dynamic stability indicators.

Evaluation of instability in patients with chronic vestibular syndrome using dynamic stability indicators.

Gait abnormalities are common in patients with chronic vestibular syndrome (CVS), and stability analysis and gait feature recognition in CVS patients have clinical significance for diagnosing CVS. This study explored two-dimensional dynamic stability indicators for evaluating gait instability in patients with CVS. The Center of Mass acceleration (COMa) peak of CVS patients was significantly faster than that of the control group (p < 0.05), closer to the back of the body, and slower at the Toe-off (TO) moment, which enlarged the Center of Mass position-velocity combination proportion within the Region of Velocity Stability (ROSv). The sensitivity, specificity, and accuracy of the Center of Mass velocity (COMv) or COMa peaks were 75.0%, 93.7%, and 90.2% for CVS patients and control groups, respectively. The two-dimensional ROSv parameters improved sensitivity, specificity, and accuracy in judging gait instability in patients over traditional dynamic stability parameters. Dynamic stability parameters quantitatively described the differences in dynamic stability during walking between patients with different degrees of CVS and those in the control group. As CVS impairment increases, the patient's dynamic stability decreases. This study provides a reference for the quantitative evaluation of gait stability in patients with CVS.

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来源期刊
Medical & Biological Engineering & Computing
Medical & Biological Engineering & Computing 医学-工程:生物医学
CiteScore
6.00
自引率
3.10%
发文量
249
审稿时长
3.5 months
期刊介绍: Founded in 1963, Medical & Biological Engineering & Computing (MBEC) continues to serve the biomedical engineering community, covering the entire spectrum of biomedical and clinical engineering. The journal presents exciting and vital experimental and theoretical developments in biomedical science and technology, and reports on advances in computer-based methodologies in these multidisciplinary subjects. The journal also incorporates new and evolving technologies including cellular engineering and molecular imaging. MBEC publishes original research articles as well as reviews and technical notes. Its Rapid Communications category focuses on material of immediate value to the readership, while the Controversies section provides a forum to exchange views on selected issues, stimulating a vigorous and informed debate in this exciting and high profile field. MBEC is an official journal of the International Federation of Medical and Biological Engineering (IFMBE).
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