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| Voice processing technique for patients with stroke based on chao theory and surrogate data analysis |
| LI Jiang1, ZHAO Ya-qiong1, BAO Ye-hua2 |
| 1.Department of Control Science and Engineering, Zhejiang University, Hangzhou 310027, China; 2.Chinese Medicine Hospital of Hangzhou, Hangzhou 310007, China |
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Abstract Human voices changing as a stroke result were analyzed. A method based on chaos and surrogate data method was proposed to analyze the voice signal from nonlinear aspect. The correlation dimension, the largest Lyapunov exponent of the voice signal and value of first minimum of mutual information function were calculated. There exist several fluctuations in voice when stroke patients speaking, which increases the correlation dimension of the voice signal. A new feature was proposed which is normalized variance quantity based on surrogate data method and the correlation dimension of voice. The voice analysis results of 17 patients and 20 healthy people show that the difference between the chaotic features of the normal sounds and that of the pathological sounds is significant. Results prove that the dysfunction in brain causes the disorder in voice．
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Published: 06 June 2018
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基于混沌和替代数据法的中风病人声音分析
研究中风病人因为脑损伤导致改变的声音信号,提出基于混沌和替代数据法的中风病人声音信号的分析方法,从非线性的角度分析中风病人的声音信号.计算声音信号的关联维数、最大李亚普诺夫指数和互信息图的第一个最小值；因为中风病人的声音信号会出现明显波动,增大了信号的关联维数,采用替代数据法结合混沌特征量之一的关联维数给出新的特征量,即归一化方差的检测量.对17例中风病人和20例健康人的分析结果表明：中风病人与健康人声音信号的混沌特征有明显差异,说明脑损伤导致声音信号的改变.
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