Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
JMIR Mhealth Uhealth. 2020 Mar 20;8(3):e16650. doi: 10.2196/16650.
Gait impairments including shuffling gait and hesitation are common in people with Parkinson's disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly focus on the spatiotemporal characteristics of gait, but less is known of the angular characteristics of the gait, which may provide helpful information pertaining to the functional status and effects of the treatment in PD.
This study aimed to quantify the angles of steps during walking, and explore if this novel step angle metric is associated with the severity of PD and the effects of the treatment including the acute levodopa challenge test (ALCT) and deep brain stimulation (DBS).
A total of 18 participants with PD completed the walking test before and after the ALCT, and 25 participants with PD completed the test with the DBS on and off. The walking test was implemented under two conditions: walking normally at a preferred speed (single task) and walking while performing a cognitive serial subtraction task (dual task). A total of 17 age-matched participants without PD also completed this walking test. The angular velocity was measured using wearable sensors on each ankle, and three gait angular metrics were obtained, that is mean step angle, initial step angle, and last step angle. The conventional gait metrics (ie, step time and step number) were also calculated.
The results showed that compared to the control, the following three step angle metrics were significantly smaller in those with PD: mean step angle (F=69.75, P<.001, partial eta-square=0.59), initial step angle (F=15.56, P<.001, partial eta-square=0.25), and last step angle (F=61.99, P<.001, partial eta-square=0.56). Within the PD cohort, both the ALCT and DBS induced greater mean step angles (ACLT: F=5.77, P=.02, partial eta-square=0.13; DBS: F=8.53, P=.005, partial eta-square=0.14) and last step angles (ACLT: F=10, P=.003, partial eta-square=0.21; DBS: F=4.96, P=.003, partial eta-square=0.09), but no significant changes were observed in step time and number after the treatments. Additionally, these step angles were correlated with the Unified Parkinson's Disease Rating Scale, Part III score: mean step angle (single task: r=-0.60, P<.001; dual task: r=-0.52, P<.001), initial step angle (single task: r=-0.35, P=.006; dual task: r=-0.35, P=.01), and last step angle (single task: r=-0.43, P=.001; dual task: r=-0.41, P=.002).
This pilot study demonstrated that the gait angular characteristics, as quantified by the step angles, were sensitive to the disease severity of PD and, more importantly, can capture the effects of treatments on the gait, while the traditional metrics cannot. This indicates that these metrics may serve as novel markers to help the assessment of gait in those with PD as well as the rehabilitation of this vulnerable cohort.
包括拖曳步态和犹豫步态在内的步态障碍在帕金森病(PD)患者中很常见,与跌倒风险增加和冻结步态有关。如今,步态指标主要集中在步态的时空特征上,但对步态的角度特征知之甚少,这可能为 PD 的功能状态和治疗效果提供有价值的信息。
本研究旨在量化行走时的步幅角度,并探讨该新的步幅角度指标是否与 PD 的严重程度以及治疗效果相关,包括急性左旋多巴挑战试验(ALCT)和深部脑刺激(DBS)。
18 名 PD 患者在 ALCT 前后完成行走测试,25 名 PD 患者在 DBS 开启和关闭时完成测试。行走测试在两种情况下进行:以自身偏好的速度正常行走(单任务)和在执行认知连续减法任务时行走(双任务)。17 名年龄匹配的无 PD 参与者也完成了这项行走测试。通过每个脚踝上的可穿戴传感器测量角速度,并获得三个步态角度指标,即平均步幅角度、初始步幅角度和最后步幅角度。同时还计算了传统的步态指标(即步幅时间和步幅数)。
结果显示,与对照组相比,PD 患者的以下三个步幅角度指标明显较小:平均步幅角度(F=69.75,P<.001,部分 eta 平方=0.59)、初始步幅角度(F=15.56,P<.001,部分 eta 平方=0.25)和最后步幅角度(F=61.99,P<.001,部分 eta 平方=0.56)。在 PD 队列中,ALCT 和 DBS 均能显著增加平均步幅角度(ALCT:F=5.77,P=.02,部分 eta 平方=0.13;DBS:F=8.53,P=.005,部分 eta 平方=0.14)和最后步幅角度(ALCT:F=10,P=.003,部分 eta 平方=0.21;DBS:F=4.96,P=.003,部分 eta 平方=0.09),但治疗后步幅时间和数量无明显变化。此外,这些步幅角度与帕金森病统一评定量表(UPDRS)第三部分评分呈显著相关:平均步幅角度(单任务:r=-0.60,P<.001;双任务:r=-0.52,P<.001)、初始步幅角度(单任务:r=-0.35,P=.006;双任务:r=-0.35,P=.01)和最后步幅角度(单任务:r=-0.43,P=.001;双任务:r=-0.41,P=.002)。
本初步研究表明,步幅角度等步态角度特征对 PD 的疾病严重程度敏感,更重要的是,能够捕捉治疗对步态的影响,而传统指标则无法捕捉。这表明这些指标可能成为评估 PD 患者步态以及对这一脆弱群体进行康复的新标志物。