ArticleFrontiers in aging neuroscience2022
Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network.
Article in Frontiers in aging neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed, 13 citations in OpenAlex.
- Tat-NR2B9c prevent cognitive dysfunction in mice modeling Alzheimer's Disease induced by AβIBRO neuroscience reports · 2025Article
- Multi-Threshold Recurrence Rate Plot: A Novel Methodology for EEG Analysis in Alzheimer's Disease and Frontotemporal Dementia.Brain sciences · 2024Article
- Improved Recurrence Plots Compression Distance by Learning Parameter for Video Compression Quality.Entropy (Basel, Switzerland) · 2023Article
- Treadmill Exercise Modulates Intestinal Microbes and Suppresses LPS Displacement to Alleviate Neuroinflammation in the Brains of APP/PS1 Mice.Nutrients · 2022Article
- An objective model for diagnosing comorbid cognitive impairment in patients with epilepsy based on the clinical-EEG functional connectivity features.Frontiers in neuroscience · 2022Article
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Authors and funding
3 authors at 3 institutions in 1 country.
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Abstract
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.
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