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A novel method for early diagnosis of Alzheimer’s disease based on higher-order spectral estimation of spontaneous speech signals

机译:一种基于自发语音信号高阶谱估计的阿尔茨海默氏病早期诊断新方法

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摘要

One main challenge for medical investigators is the early diagnosis of Alzheimer’s disease (AD) because it provides greater opportunities for patients to be eligible for more clinical trials. In this study, higher order spectra of human speech signals during AD were explored to analyze and compare the quadratic phase coupling of spontaneous speech signals for healthy and AD subjects using bispectrum and bicoherence. The results showed that the quadratic phase couplings of spontaneous speech signal of persons with Alzheimer’s were reduced compared to healthy subject. However, the speech phase coupled harmonics shifted to the higher frequencies in Alzheimer’s than healthy subjects. In addition, it was shown not only are there significant differences between Alzheimer’s and control subjects in parameters estimated, but also the speech patterns appeared to have fluctuated in both types of spontaneous speech.
机译:医学研究人员面临的主要挑战之一是阿尔茨海默氏病(AD)的早期诊断,因为它为患者提供了更多参与更多临床试验的机会。在这项研究中,探索了人类语音信号在AD期间的高阶频谱,以分析和比较双谱和双相干对健康和AD受试者自发语音信号的二次相位耦合。结果表明,与健康人相比,阿尔茨海默氏症患者自发语音信号的二次相位耦合降低了。但是,语音相位耦合谐波在阿尔茨海默氏症中的频率要比健康受试者高。此外,研究表明,不仅阿尔茨海默氏症和控制对象之间在估计参数方面存在显着差异,而且两种自发性语音的语音模式似乎都出现了波动。

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