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使用 Microsoft Kinect 对帕金森病患者的步态和改良计时起立行走进行自动分析:与身体结果测量的关联。

Automated analysis of gait and modified timed up and go using the Microsoft Kinect in people with Parkinson's disease: associations with physical outcome measures.

机构信息

Department of Physiotherapy, Singapore General Hospital, National Heart Centre Level 7, 5 Hospital Drive, Singapore, 169609, Republic of Singapore.

Duke-NUS Graduate Medical School, 8 College Road, Singapore, 169857, Republic of Singapore.

出版信息

Med Biol Eng Comput. 2019 Feb;57(2):369-377. doi: 10.1007/s11517-018-1868-2. Epub 2018 Aug 20.

Abstract

Instrumenting physical assessments in people with Parkinson's disease can provide valuable and sensitive information. This study aimed to investigate whether variables derived from a Kinect-based system can provide incremental value over standard habitual gait speed (HGS) and timed up and go (TUG) variables by evaluating associations with (1) motor and (2) postural instability and gait difficulty (PIGD) subscales of the Unified Parkinson's Disease Rating Scale (UPDRS). Sixty-two individuals with Parkinson's disease (age 66 ± 7 years; 74% male) undertook an instrumented HGS and modified TUG tests, in addition to the UPDRS. Multivariable regression models were used to evaluate the associations of the Kinect measures with UPDRS motor and PIGD scores. First step length during the TUG and average step length and vertical pelvic displacement during the HGS were significantly associated with the PIGD subscale (P < 0.05). The only Kinect-derived variable showing additive benefits over the standard measures for the PIGD association was HGS vertical pelvic displacement. The only standard or Kinect-derived variable significantly associated with the motor subscale was first step length during the TUG (P < 0.01). This study provides preliminary evidence to support the use of a low-cost, non-invasive method of instrumenting gait and TUG tests in people with Parkinson's disease. Graphical abstract ᅟ.

摘要

对帕金森病患者进行物理评估的仪器检测可以提供有价值且敏感的信息。本研究旨在探讨基于 Kinect 的系统得出的变量是否可以通过评估与(1)运动和(2)姿势不稳定和步态困难(PIGD)的统一帕金森病评定量表(UPDRS)亚量表的关联,提供比标准习惯性步态速度(HGS)和计时起立行走(TUG)变量更有价值的信息。62 名帕金森病患者(年龄 66 ± 7 岁;74%为男性)接受了仪器化 HGS 和改良 TUG 测试,以及 UPDRS 测试。多变量回归模型用于评估 Kinect 测量值与 UPDRS 运动和 PIGD 评分的关联。TUG 过程中的第一步长和 HGS 过程中的平均步长和垂直骨盆位移与 PIGD 亚量表显著相关(P < 0.05)。唯一在 PIGD 关联方面比标准测量值具有附加优势的 Kinect 衍生变量是 HGS 垂直骨盆位移。唯一与运动亚量表显著相关的标准或 Kinect 衍生变量是 TUG 过程中的第一步长(P < 0.01)。本研究初步证明了在帕金森病患者中使用低成本、非侵入性的步态和 TUG 测试仪器检测方法的有效性。

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