Voice Analysis Proposed For Early Alzheimer's Detection

Researchers at the Chinese University of Hong Kong are testing methods to detect Alzheimer's disease risk using AI analysis of eye fundus images. During a demonstration, a patient used a green crosshair on a screen to align their eye with the fundus camera. The process involves taking multiple photos of each eye to ensure accuracy. Experts are using AI to analyze retinal vasculature to assess brain health and detect early signs of Alzheimer's risk. This method aims to detect potential issues at an early stage before physical impairments appear. New technology can detect the risk of cognitive impairment in elderly or middle-aged individuals at an early stage, potentially before symptoms appear. This approach seeks to identify individuals who may transition to high-risk categories within a few years. The method is described as simpler and faster than traditional methods like MRI or blood tests, which can be expensive or invasive. The process aims to identify risks in the early stages, where approximately 70 percent of cases are categorized as stage one. This approach avoids the complexity and pain associated with blood analysis and long MRI sessions. Electronic sketching provides a simpler and faster method for detecting early-stage Alzheimer's compared to MRI or blood analysis. Adán, a medical professional, observed specific changes in voice rhythm, pause, or intonation as Alzheimer's began to affect his patients.