A Mobile-Based Screening System for Data Analyses of Early Dementia Traits Detection

Area of Science:

• Neurology
• Gerontology
• Digital Health

Background:

• Current dementia pre-diagnosis methods lack comprehensiveness and accessibility.
• There is a need for robust, unbiased cognitive assessment tools for early dementia detection.

Purpose of the Study:

• To introduce DementiaTest, a mobile application for early dementia trait screening.
• To provide a comprehensive and accessible platform for cognitive functioning assessment.
• To support general practitioners in identifying potential dementia cases for further evaluation.

Main Methods:

• Development and testing of the DementiaTest mobile application on Android and iOS platforms.
• Adoption of Diagnostic and Statistical Manual of Mental Disorders (DSM-V) gold standard criteria.
• Data collection from cases and controls via an interactive and accessible interface.

Main Results:

• DementiaTest provides quick pre-diagnostic reports based on cognitive indicators.
• The application is available on major mobile stores, enhancing accessibility.
• Collected data can be analyzed using Artificial Intelligence for performance evaluation.

Conclusions:

• DementiaTest offers a comprehensive, accessible, and unbiased approach to dementia screening.
• The app facilitates early detection and timely referrals for individuals with potential dementia traits.
• AI analysis of app data can refine screening performance and identify early dementia signs.