Sample entropy and surrogate data analysis for Alzheimer’s disease
Alzheimer's disease (AD) is a neurological degenerative disease, which is mainly characterized by the memory loss. As electroencephalogram (EEG) device is relatively cheap, portable and non-invasive, it has been widely used in AD-related studies. We proposed a method to detect the differences b...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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AIMS Press
2019-07-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/10.3934/mbe.2019345?viewType=HTML |
| _version_ | 1818202982662012928 |
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| author | Xuewei Wang Xiaohu Zhao Fei Li Qiang Lin Zhenghui Hu |
| author_facet | Xuewei Wang Xiaohu Zhao Fei Li Qiang Lin Zhenghui Hu |
| author_sort | Xuewei Wang |
| collection | DOAJ |
| description | Alzheimer's disease (AD) is a neurological degenerative disease, which is mainly characterized by the memory loss. As electroencephalogram (EEG) device is relatively cheap, portable and non-invasive, it has been widely used in AD-related studies. We proposed a method to detect the differences between healthy subjects and AD patients, which combines classical sample entropy (SampEn) and surrogate data method. EEGs from 14 AD patients and 20 healthy subjects were analyzed. The results based on the original data showed that the SampEn of AD patients was significantly decreased (p<0.01) at electrodes c3, f3, o2 and p4, which confirmed that AD could cause complexity loss. However, using original data could be subject to human judgement, so we generated a series of surrogate data. We found that, there were significant difference of SampEn between the original time series and their surrogate data at c3 and o2 electrodes and the differences between healthy subjects and AD patients can be verified. Our method is capable of distinguishing AD patients from healthy subjects, which is consistent with the concept of physiologic complexity, and providing insights for understanding of AD. |
| first_indexed | 2024-12-12T03:18:06Z |
| format | Article |
| id | doaj.art-6974bf02430542d8a85cc8fc4c74b820 |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-12-12T03:18:06Z |
| publishDate | 2019-07-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-6974bf02430542d8a85cc8fc4c74b8202022-12-22T00:40:15ZengAIMS PressMathematical Biosciences and Engineering1551-00182019-07-011666892690610.3934/mbe.2019345Sample entropy and surrogate data analysis for Alzheimer’s diseaseXuewei Wang0Xiaohu Zhao1Fei Li 2Qiang Lin3Zhenghui Hu41. College of Science, Zhejiang University of Technology, Hangzhou, China1. College of Science, Zhejiang University of Technology, Hangzhou, China1. College of Science, Zhejiang University of Technology, Hangzhou, China1. College of Science, Zhejiang University of Technology, Hangzhou, China1. College of Science, Zhejiang University of Technology, Hangzhou, ChinaAlzheimer's disease (AD) is a neurological degenerative disease, which is mainly characterized by the memory loss. As electroencephalogram (EEG) device is relatively cheap, portable and non-invasive, it has been widely used in AD-related studies. We proposed a method to detect the differences between healthy subjects and AD patients, which combines classical sample entropy (SampEn) and surrogate data method. EEGs from 14 AD patients and 20 healthy subjects were analyzed. The results based on the original data showed that the SampEn of AD patients was significantly decreased (p<0.01) at electrodes c3, f3, o2 and p4, which confirmed that AD could cause complexity loss. However, using original data could be subject to human judgement, so we generated a series of surrogate data. We found that, there were significant difference of SampEn between the original time series and their surrogate data at c3 and o2 electrodes and the differences between healthy subjects and AD patients can be verified. Our method is capable of distinguishing AD patients from healthy subjects, which is consistent with the concept of physiologic complexity, and providing insights for understanding of AD.https://www.aimspress.com/article/10.3934/mbe.2019345?viewType=HTMLalzheimer’s diseaseelectroencephalogramsample entropysurrogate data analysisnonlinear time series |
| spellingShingle | Xuewei Wang Xiaohu Zhao Fei Li Qiang Lin Zhenghui Hu Sample entropy and surrogate data analysis for Alzheimer’s disease Mathematical Biosciences and Engineering alzheimer’s disease electroencephalogram sample entropy surrogate data analysis nonlinear time series |
| title | Sample entropy and surrogate data analysis for Alzheimer’s disease |
| title_full | Sample entropy and surrogate data analysis for Alzheimer’s disease |
| title_fullStr | Sample entropy and surrogate data analysis for Alzheimer’s disease |
| title_full_unstemmed | Sample entropy and surrogate data analysis for Alzheimer’s disease |
| title_short | Sample entropy and surrogate data analysis for Alzheimer’s disease |
| title_sort | sample entropy and surrogate data analysis for alzheimer s disease |
| topic | alzheimer’s disease electroencephalogram sample entropy surrogate data analysis nonlinear time series |
| url | https://www.aimspress.com/article/10.3934/mbe.2019345?viewType=HTML |
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