Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network | |
Li, Xuemei; Zhou, Tao; Qiu, Shi![]() | |
作者部门 | 光谱成像技术研究室 |
2022-05-10 | |
发表期刊 | FRONTIERS IN AGING NEUROSCIENCE
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ISSN | 1663-4365 |
卷号 | 14 |
产权排序 | 3 |
摘要 | Alzheimer's disease is a neurological disorder characterized by progressive cognitive dysfunction and behavioral impairment that occurs in old. Early diagnosis and treatment of Alzheimer's disease is great significance. Electroencephalography (EEG) signals can be used to detect Alzheimer's disease due to its non-invasive advantage. To solve the problem of insufficient analysis by single-channel EEG signal, we analyze the relationship between multiple channels and build PLV framework. To solve the problem of insufficient representation of 1D signal, a threshold-free recursive plot convolution network was constructed to realize 2D representation. To solve the problem of insufficient EEG signal characterization, a fusion algorithm of clinical features and imaging features was proposed to detect Alzheimer's disease. Experimental results show that the algorithm has good performance and robustness. |
关键词 | Alzheimer's disease EEG PLV recursive graph no-threshold |
DOI | 10.3389/fnagi.2022.888577 |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:000802256800001 |
出版者 | FRONTIERS MEDIA SA |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.opt.ac.cn/handle/181661/95996 |
专题 | 光谱成像技术研究室 |
推荐引用方式 GB/T 7714 | Li, Xuemei,Zhou, Tao,Qiu, Shi. Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network[J]. FRONTIERS IN AGING NEUROSCIENCE,2022,14. |
APA | Li, Xuemei,Zhou, Tao,&Qiu, Shi.(2022).Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network.FRONTIERS IN AGING NEUROSCIENCE,14. |
MLA | Li, Xuemei,et al."Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network".FRONTIERS IN AGING NEUROSCIENCE 14(2022). |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
Alzheimer's Disease (1937KB) | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 |
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