Design of a Smart Handwriting Tool for Early Detection of Alzheimer's Disease

Alzheimer's disease (AD) remains a major challenge in modern medicine, requiring early and accurate diagnostic methods to ensure effective management. This study explores the development and application of an innovative diagnostic tool, the Smart handwriting tool, designed to detect early signs of cognitive decline through detailed handwriting analysis. Equipped with an MPU-9250 sensor, the Smart handwriting tool records the three-dimensional coordinates, velocity, and acceleration of handwriting movements. These parameters are crucial for assessing spatial control, motion consistency, speed variations, and the ability to modulate movement speed and force — all of which are often impaired in cognitive disorders such as AD.The study involved 20 patients diagnosed with AD (Alzheimer’s group, AG) and 18 healthy individuals forming the control group (CG), matched by age and education. Data collection included tasks such as sentence rewriting, figure redrawing, and number rewriting. The data were processed using the CoolTerm software with an 18 Hz sampling rate. Descriptive statistics showed lower average gyroscope and accelerometer values in the AD group, indicating slower and less variable movements compared to the control group. T-tests confirmed statistically significant differences (p < 0.001) across all measured parameters between the AD and control groups.The findings support the potential of the Smart handwriting tool as a non-invasive and cost-effective diagnostic tool for the early detection of AD. By capturing subtle neuromotor changes, the Smart handwriting tool can facilitate early diagnosis and timely intervention, potentially altering the course of the disease and improving patient outcomes. This study represents a significant advancement in early AD detection, demonstrating the Smart handwriting tool's promise as a transformative tool in diagnosing and managing neurodegenerative diseases.