论文标题
选择基于熵的特征，用于分析Archimedes螺旋形成必需震颤的螺旋
Selection of entropy based features for the analysis of the Archimedes' spiral applied to essential tremor
论文作者
论文摘要
生物医学系统受到相互作用的机制的调节，这些机制在多个空间和时间尺度上运行，并在内部使用线性和非线性信息产生生物信号。从这个意义上讲，熵可以提供有关系统中疾病的有用措施，时间序列中缺乏信息和/或信号的不规则性。基本震颤（ET）是最常见的运动障碍，是帕金森氏病的20倍，据估计有50％至70％的病例是遗传的。 Archimedes螺旋图是用于临床诊断的最常用的标准测试之一。这项工作是从图纸和笔迹中选择非线性生物标志物的，是一项广泛的跨研究的一部分，用于诊断BiodoNostia Health Institute的基本震颤。几种熵算法用于生成非线性纤维。自动分析系统由几个机器学习范例组成。
Biomedical systems are regulated by interacting mechanisms that operate across multiple spatial and temporal scales and produce biosignals with linear and non-linear information inside. In this sense entropy could provide a useful measure about disorder in the system, lack of information in time-series and/or irregularity of the signals. Essential tremor (ET) is the most common movement disorder, being 20 times more common than Parkinson's disease, and 50-70% of this disease cases are estimated to be genetic in origin. Archimedes spiral drawing is one of the most used standard tests for clinical diagnosis. This work, on selection of nonlinear biomarkers from drawings and handwriting, is part of a wide-ranging cross study for the diagnosis of essential tremor in BioDonostia Health Institute. Several entropy algorithms are used to generate nonlinear feayures. The automatic analysis system consists of several Machine Learning paradigms.
