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arXiv AI By Changqing Gong, Huafeng Qin, Moun\^im A. El-Yacoubi

Segment-Level Risk Discovery in Online Handwriting for Alzheimer's Disease Detection

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The paper introduces NormPaST‑Risk, a novel framework that detects Alzheimer’s disease from online handwriting by focusing on local, segment‑level risk rather than whole‑trajectory features. It employs a multi‑scale temporal encoder, a Paper‑Air state‑space model to separate on‑paper motor execution from in‑air planning, and a healthy‑normative branch to learn normal handwriting dynamics. A weakly supervised segment‑risk module identifies high‑risk handwriting segments, achieving superior AD/HC classification on the DARWIN benchmark and offering interpretable evidence linked to disease‑related handwriting changes.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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