A Detection Method for Alzheimer's Disease Based on Long-Term Visual Features

Alzheimer's disease (AD) is a neurodegenerative disease characterized by cognitive impairment. At present, there is no effective treatment for the disease, which has brought great harm to patients and society. Therefore, it is of great significance to explore the early detection method of Alzheimer's disease. In recent years, with the development of computer vision and deep neural networks, using deep neural networks to detect early Alzheimer's disease has attracted more and more researchers' attention. And gait abnormalities caused by Alzheimer's disease are gradually known. Based on this, this paper proposes a method to detect Alzheimer's disease using long-term visual features, and proves the effectiveness of the method through experiments. And discuss the characteristics of such tasks. It provides a basis for the development of deep neural network detection methods for cognitive disorders such as Alzheimer's disease in the future.