Handwriting characteristics analysis for Alzheimer’s Disease and Mild Cognitive Impairments Assessment

Abstract

AbstractBackgroundMotor changes are early signs of neurodegenerative diseases such as Alzheimer’s disease (AD), but they are often difficult to detect, especially in the early stages. In the past, the examination of handwriting has been used to investigate motoric changes in different neurodegenerative diseases. In this study, we explore a wide array of explainable characteristics of the handwriting of patients obtained with signal processing, and study their potential for assessment of Mild Cognitive Impairment (MCI) and AD.MethodWe collected the written tasks from 37 participants, 7 with AD, 17 with MCI, and 13 for the control group (CTL) on a digital tablet. We analyzed 14 different tasks, including holding the pen over a point, copying images, free writing/drawing, and memory copying. We extracted multiple movement characteristics, including the length of each stroke, the ratio of the time the pen spent on‐air vs in‐tablet and the standard deviation of the distance between consecutive points. The drawings of each subject were manually supervised, then processed to extract multiple characteristics, and compared to identify the ones providing the most significant differences between the three studied groups using Welch’s t‐test, with false discovery rate (FDR) correction.ResultPreliminary results showed that the ratio between the time with the pen in contact with the tablet and without (on‐air vs in‐tablet) for writing tasks, significantly differentiate between AD and CTL patients (p‐value<0.01), as well as the position standard deviation when asked to maintain the pen at a fixed position (p‐value<0.05). The comparison between MCI and CTL populations also showed that the length of the strokes for drawings and copying tasks can deliver clues to distinguish both groups (p‐value<0.05).ConclusionAutomated analysis of a large variety of handwriting segments employing machine learning techniques can provide an assessment of patients with AD and MCI that may be useful in their early diagnosis and assessment of progression.