Detection of Mild Cognitive Impairment Through Hand Motor Function Under Digital Cognitive Test: Mixed Methods Study

Area of Science:

• Neuroscience
• Gerontology
• Human-Computer Interaction

Background:

• Early detection of cognitive impairment or dementia is crucial for managing neurodegenerative diseases.
• Current diagnostic tools for mild cognitive impairment (MCI) are often inaccessible or time-consuming.
• Novel, efficient methods are needed to aid clinicians in MCI detection.

Purpose of the Study:

• To assess the feasibility and efficiency of using tablet-based "drawing and dragging" tasks to detect MCI.
• To analyze movement kinetics as a biomarker for cognitive function.
• To evaluate user experience with a novel cognitive screening system.

Main Methods:

• Iterative design of "drawing and dragging" tasks involving stakeholders.
• Evaluation of stroke patterns and movement kinetics in healthy and MCI groups.
• Analysis of hand motor function features (time, stroke, frequency, score, sequence).
• User experience assessment via questionnaires and interviews.

Main Results:

• The system achieved 85% accuracy in detecting MCI.
• Time- and score-based movement kinetics were most effective in differentiating groups.
• MCI patients exhibited increased stroke transition times, longer drawing durations, slower dragging, and lower scores.
• MCI patients showed impaired decision-making and visual-spatial sequencing.

Conclusions:

• Tablet-based system quantitatively assesses hand motor function for MCI detection.
• Identifies digital biomarkers for MCI and Alzheimer's dementia.
• Monitors cognitive and behavioral decline, including executive function and visual perception.