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用惯性系统评估头尾运动学转向特征作为帕金森病运动功能障碍的标志物

Cranio-Caudal Kinematic Turn Signature Assessed with Inertial Systems As a Marker of Mobility Deficits in Parkinson's Disease.

作者信息

Lebel Karina, Duval Christian, Nguyen Hung Phuc, Plamondon Réjean, Boissy Patrick

机构信息

Department of Surgery, Faculty of Medicine and Health Sciences, Orthopedic Service, Université de Sherbrooke, Sherbrooke, QC, Canada.

Research Centre on Aging, Sherbrooke, QC, Canada.

出版信息

Front Neurol. 2018 Jan 29;9:22. doi: 10.3389/fneur.2018.00022. eCollection 2018.

Abstract

BACKGROUND

Turning is a challenging mobility task requiring proper planning, coordination, and postural stability to be executed efficiently. Turn deficits can impair mobility and lead to falls in patients with neurodegenerative disease, such as Parkinson's disease (PD). It was previously shown that the cranio-caudal sequence involved during a turn (i.e., motion is initiated by the head, followed by the trunk) exhibits a signature that can be captured using an inertial system and analyzed through the Kinematics Theory. The so-called cranio-caudal kinematic turn signature (CCKS) metrics derived from this approach could, therefore, be a promising avenue to develop and track markers to measure early mobility deficits.

OBJECTIVE

The current study aims at exploring the discriminative validity and sensitivity of CCKS metrics extracted during turning tasks performed by patients with PD.

METHODS

Thirty-one participants (16 asymptomatic older adults (OA): mean age = 69.1 ± 7.5 years old; 15 OA diagnosed with early PD ON and OFF medication, mean age = 65.8 ± 8.4 years old) performed repeated timed up-and-go (TUG) tasks while wearing a portable inertial system. CCKS metrics (maximum head to trunk angle reached and commanded amplitudes of the head to trunk neuromuscular system, estimated from a sigma-lognormal model) were extracted from kinematic data recorded during the turn phase of the TUG tasks. For comparison purposes, common metrics used to analyze the quality of a turn using inertial systems were also calculated over the same trials (i.e., the number of steps required to complete the turn and the turn mean and maximum velocities).

RESULTS

All CCKS metrics discriminated between OA and patients ( ≤ 0.041) and were sensitive to change in PD medication state ( ≤ 0.033). Common metrics were also able to discriminate between OA and patients ( < 0.014), but they were unable to capture the change in medication state this early in the disease ( ≥ 0.173).

CONCLUSION

The enhanced sensitivity to change of the proposed CCKS metrics suggests a potential use of these metrics for mobility impairments identification and fluctuation assessment, even in the early stages of the disease.

摘要

背景

转身是一项具有挑战性的移动任务,需要适当的规划、协调和姿势稳定性才能高效执行。转身功能障碍会损害行动能力,并导致神经退行性疾病患者(如帕金森病(PD))跌倒。先前的研究表明,转身过程中涉及的头尾顺序(即动作由头部发起,随后是躯干)呈现出一种特征,可通过惯性系统捕捉并根据运动学理论进行分析。因此,从这种方法中得出的所谓头尾运动学转身特征(CCKS)指标,可能是开发和追踪测量早期行动能力缺陷标志物的一条有前景的途径。

目的

本研究旨在探讨帕金森病患者在转身任务中提取的CCKS指标的判别效度和敏感性。

方法

31名参与者(16名无症状老年人(OA):平均年龄=69.1±7.5岁;15名被诊断为早期帕金森病的OA,在服药和未服药状态下,平均年龄=65.8±8.4岁)在佩戴便携式惯性系统时进行重复的定时起立行走(TUG)任务。CCKS指标(从西格玛对数正态模型估计的头部到躯干的最大角度以及头部到躯干神经肌肉系统的指令幅度)从TUG任务转身阶段记录的运动学数据中提取。为了进行比较,在相同试验中还计算了使用惯性系统分析转身质量的常用指标(即完成转身所需的步数以及转身的平均速度和最大速度)。

结果

所有CCKS指标在OA和患者之间具有显著差异(≤0.041),并且对帕金森病药物状态的变化敏感(≤0.033)。常用指标也能够区分OA和患者(<0.014),但它们无法在疾病的这个早期阶段捕捉到药物状态的变化(≥0.173)。

结论

所提出的CCKS指标对变化具有更高的敏感性,这表明即使在疾病的早期阶段,这些指标也有可能用于识别行动能力障碍和评估波动情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b0b9/5796912/31124b9e12dc/fneur-09-00022-g001.jpg

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