帕金森病患者伸手动作的亚动作组成及质量评估

L. Iuppariello, P. Bifulco, M. Romano, M. Cesarelli, G. D'Addio
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引用次数: 19

摘要

将看似连续的运动分割成片段的理论已经存在了很多年。这些片段可以被认为是“原始”运动,或者是更复杂运动的组成部分。这些碎片的存在,或者称之为次级运动,在过去的100年里得到了广泛研究的支持。在人类连续运动的基础上存在着离散子运动的证据,这促使许多人试图“提取”它们。近年来,次运动理论在康复领域引起了极大的关注。事实上,了解中枢神经系统损伤后的运动缺陷,以及这些缺陷与功能能力之间的关系,是成功康复治疗发展的基础。为此,本文提出了一种新的子运动分解方法;它基于约束-期望-最大化。这种表示允许我们通过将每个信号分解为二维高斯函数的加权组合来探索运动是否由基本运动学单元组成。这些可以用来评估帕金森病患者的伸手动作质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Submovements composition and quality assessment of reaching movements in subjects with Parkinson's Disease
The segmentation of seemingly continuous movements into segments has been theorized for many years. These segments may be considered as “primitive” movements, or building blocks of more complex movements. The existence of these fragments, or sub-movements as they are called, has been supported by a wide range of studies over the past 100 years. Evidence for the existence of discrete sub-movements underlying continuous human movement has motivated many attempts to “extract” them. Recently, the sub-movement theory gained a great appeal in the rehabilitation field. In fact, understanding movement deficits following CNS lesions, and the relationships between these deficits and functional ability, is fundamental to the development of successful rehabilitation therapies. So, here a novel sub-movements decomposition method is proposed; it is based on a constrained-Expectation-Maximization. This representation allowed us to explore whether the movements are built up of elementary kinematic units by decomposing each signal into a weighted combination of 2D Gaussian functions. These can be used to assess the quality of reaching movements in subjects with Parkinson's Disease.
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