A Proposal for New Algorithm that Defines Gait-Induced Acceleration and Gait Cycle in Daily Parkinsonian Gait Disorders

IF 3.4 Q2 ENGINEERING, BIOMEDICAL
Masahiko Suzuki, M. Yogo, M. Morita, H. Terashi, M. Iijima, M. Yoneyama, M. Takada, H. Utsumi, Y. Okuma, A. Hayashi, S. Orimo, H. Mitoma
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引用次数: 2

Abstract

We developed a new device, the portable gait rhythmogram (PGR), to record up to 70 hrs of movement-induced accelerations. Acceleration values induced by various movements, averaged every 10 min, showed gamma distribution, and the mean value of this distribu- tion was used as an index of the amount of overall movements. Furthermore, the PGR algorithm can specify gait-induced accelerations using the pattern-matching method. Analysis of the relationship between gait-induced accelerations and gait cycle duration makes it possible to quantify Parkinson’s disease (PD)-specific pathophysiological mechanisms underlying gait disorders. Patients with PD showed the following disease-specific patterns: (1) reduced amount of overall movements and (2) low amplitude of gait-induced accelerations in the early stages of the disease, which was compensated by fast stepping. Loss of compensation was associated with slow stepping gait, (3) narrow range of gait-induced acceleration amplitude and gait cycle duration, suggesting monotony, and (4) evident motor fluctuations during the day by tracing changes in the above two parameters. Prominent motor fluctuation was associated with frequent switching between slow stepping mode and active mode. These findings suggest that monitor - ing various movement- and gait-induced accelerations allows the detection of specific changes in PD. We conclude that continuous long-term monitoring of these parameters can provide accurate quantitative assessment of parkinsonian clinical motor signs.
一种定义帕金森步态障碍中步态诱导加速度和步态周期的新算法
我们开发了一种新的设备,便携式步态节律仪(PGR),可以记录长达70小时的运动引起的加速度。各种运动引起的加速度值,平均每10分钟,呈伽玛分布,该分布的平均值作为整体运动量的指标。此外,PGR算法可以使用模式匹配方法指定步态引起的加速度。分析步态诱导的加速度和步态周期持续时间之间的关系,可以量化帕金森病(PD)特异性的步态障碍的病理生理机制。PD患者表现出以下疾病特异性模式:(1)整体活动量减少;(2)疾病早期由步态引起的加速度幅度低,通过快速行走来补偿。(3)步态引起的加速度幅值和步态周期持续时间范围较窄,表现出单调性;(4)通过追踪上述两个参数的变化,可以发现白天有明显的运动波动。显著的电机波动与缓慢步进模式和主动模式之间的频繁切换有关。这些发现表明,监测各种运动和步态引起的加速度可以检测PD的特定变化。我们的结论是,持续长期监测这些参数可以提供准确的定量评估帕金森病的临床运动体征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.80
自引率
0.00%
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审稿时长
11 weeks
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