### Mathematical Biosciences and Engineering

2019, Issue 6: 6892-6906. doi: 10.3934/mbe.2019345
Research article Special Issues

# Sample entropy and surrogate data analysis for Alzheimer’s disease

• Received: 08 March 2019 Accepted: 18 July 2019 Published: 29 July 2019
• 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.

Citation: Xuewei Wang, Xiaohu Zhao, Fei Li, Qiang Lin, Zhenghui Hu. Sample entropy and surrogate data analysis for Alzheimer’s disease[J]. Mathematical Biosciences and Engineering, 2019, 16(6): 6892-6906. doi: 10.3934/mbe.2019345

### Related Papers:

• 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.

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沈阳化工大学材料科学与工程学院 沈阳 110142

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