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Methodology for automatic movement cycle extraction using Switching Linear Dynamic System

机译:使用切换线性动态系统自动移动循环提取方法

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Human motion assessment is key for motor-control rehabilitation. Using standardized definitions and spatiotemporal features - usually presented as a movement cycle diagram- specialists can associate kinematic measures to progress in rehabilitation therapy or motor impairment due to trauma or disease. Although devices for capturing human motion today are cheap and widespread, the automatic interpretation of kinematic data for rehabilitation is still poor in terms of quantitative performance evaluation. In this paper we present an automatic approach to extract spatiotemporal features from kinematic data and present it as a cycle diagram. This is done by translating standard definitions from human movement analysis into mathematical elements of a Switching Linear Dynamic System model. The result is a straight-forward procedure to learn a tracking model from a sample execution. This model is robust when used to automatically extract the movement cycle diagram of the same motion (the Sit-Stand-Sit, as an example) executed in different subject-specific manner such as his own motion speed.
机译:人类运动评估是运动控制康复的关键。使用标准化定义和时空特征 - 通常作为运动周期图,专家可以将运动措施与创伤或疾病引起的康复治疗或电机障碍的进展相关。虽然今天用于捕捉人类运动的设备是便宜和广泛的,但在定量绩效评估方面,对康复的运动数据的自动解释仍然差。在本文中,我们提出了一种自动方法来提取来自运动数据的时空特征,并将其作为循环图。这是通过将标准定义从人体运动分析转化为交换线性动态系统模型的数学元素来完成的。结果是从采样执行中学习跟踪模型的直接过程。当用于自动提取相同运动的移动循环图(作为示例)以不同的主题特定方式执行的诸如他自己的运动速度的不同运动的移动循环图,该模型是稳健的。

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