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Analysis of mean square error surface and its corresponding contour plots of spontaneous speech signals in Alzheimer's disease with adaptive wiener filter

机译:自适应维纳滤波器分析阿尔茨海默氏病自发性语音信号的均方误差面及其对应的等高线图

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The purpose of this study is to evaluate human speech rate variability and to analyze the dynamics of spontaneous speech signals of two groups, Alzheimer's and healthy subjects, to obtain a detailed understanding of their speech pattern differences so that Alzheimer's disease can be diagnosed automatically and readily. In the approach proposed in this study, the dynamics of the speech signals are analyzed by examining the mean square error (MSE) surface and contour plots quantification of these groups. In general, the results show that the speech signals transit from a high dimensional chaotic state in control subjects to a low dimensional chaotic motion in Alzheimer's patients. This can be due to the decreased interaction of variables in psychological state. Moreover, it can be partially attributed to the fact that in AD the brain begins to shrink, with the number of brain nerve fibers gradually reducing. (C) 2016 Elsevier Ltd. All rights reserved.
机译:这项研究的目的是评估人类的语速变化性,并分析阿尔茨海默氏症和健康受试者两组自发性语音信号的动态变化,以详细了解他们的语音模式差异,从而可以自动,轻松地诊断出阿尔茨海默氏病。在本研究中提出的方法中,通过检查这些组的均方误差(MSE)表面和轮廓图量化来分析语音信号的动力学。通常,结果表明,语音信号从对照组的高维混沌状态转变为阿尔茨海默氏病患者的低维混沌运​​动。这可能是由于心理状态下变量之间的交互作用减少所致。此外,这可以部分归因于以下事实:在AD中,大脑开始萎缩,大脑神经纤维的数量逐渐减少。 (C)2016 Elsevier Ltd.保留所有权利。

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