Spectral analyses of wrist motion in individuals poststroke: the development of a performance measure with promise for unsupervised settings.
Spectral analyses of wrist motion in individuals poststroke: the development of a performance measure with promise for unsupervised settings.
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DOI：
10.1177/1545968313505911
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发表时间：
2014-02
影响因子：
4.2
通讯作者：
Winstein CJ
中科院分区：
文献类型：
--
作者：
Wade E;Chen C;Winstein CJ
日常生活中使用上肢是脑中风后持续功能恢复的关键因素。然而，由于现有测量工具的限制，人们对依赖于使用的运动质量的时间演变知之甚少。概念验证研究，以确定频谱分析是否可以解释不受控制的抓取任务的已知时间运动运动质量（即运动持续时间、峰值数量、加加速度）的变异性。十名慢性中风患者在有或没有任务物体的情况下，用双手进行单手目标导向运动，每只手腕上都佩戴加速度计。为每个手势提取时间和频谱测量。表现条件对结果测量的影响通过受试者内手（非麻痹与麻痹）×物体（存在与不存在）方差分析来确定。回归分析确定光谱测量是否解释了时间测量的变异性。手对所有 3 个时间测量都有主效应，物体对运动持续时间和峰值有主效应。对于偏瘫肢体，光谱测量分别解释了运动持续时间和峰值的 41.2% 和 51.1% 的变异性。对于非麻痹肢体，频谱测量分别解释了 40.1%、42.5% 和 27.8% 的运动持续时间、峰值和急动度的变异性。光谱测量解释了中风患者运动效率和控制力的变异性。 1.0 至 2.0 Hz 的信号功率对手和物体的变化很敏感。分析该指标在周围环境中的演变可能会提供迄今为止未知的信息，有助于评估长期恢复。
Upper extremity use in daily life is a critical ingredient of continued functional recovery after cerebral stroke. However, time-evolutions of use-dependent motion quality are poorly understood due to limitations of existing measurement tools. Proof-of-concept study to determine if spectral analyses explain the variability of known temporal kinematic movement quality (ie, movement duration, number of peaks, jerk) for uncontrolled reach-to-grasp tasks. Ten individuals with chronic stroke performed unimanual goal-directed movements using both hands, with and without task object present, wearing accelerometers on each wrist. Temporal and spectral measures were extracted for each gesture. The effects of performance condition on outcome measures were determined using 2-way, within subject, hand (nonparetic vs paretic) × object (present vs absent) analysis of variance. Regression analyses determined if spectral measures explained the variability of the temporal measures. There were main effects of hand on all 3 temporal measures and main effects of object on movement duration and peaks. For the paretic limb, spectral measures explain 41.2% and 51.1% of the variability in movement duration and peaks, respectively. For the nonparetic limb, spectral measures explain 40.1%, 42.5%, and 27.8% of the variability of movement duration, peaks, and jerk, respectively. Spectral measures explain the variability of motion efficiency and control in individuals with stroke. Signal power from 1.0 to 2.0 Hz is sensitive to changes in hand and object. Analyzing the evolution of this measure in ambient environments may provide as yet uncharted information useful for evaluating long-term recovery.
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影响因子：
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作者：
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