Toward a Speech-Based Model of Premanifest Huntington's Disease Progression Using Deep Neural Networks.

ABSTRACT:

Introduction

Huntington's disease (HD) is a progressive neurodegenerative disorder characterized by motor, cognitive, and psychiatric decline. The Unified Huntington's Disease Rating Scale Total Motor Score (UHDRS-TMS) is standard for staging manifest disease, but is relatively insensitive to subtle premanifest changes. Speech abnormalities are emerging as candidate digital biomarkers; however, reliably separating premanifest HD (preHD) from healthy controls remains challenging. Here, we assess the feasibility of a speech-only approach by training and comparing multiple classifiers across diverse feature sets and structured tasks to determine whether speech alone can discriminate preHD from controls.

Methods

Speech samples were collected from 94 individuals with HD (38 prema

SUBMITTER: Sierra LA 

PROVIDER: S-EPMC12923257 | biostudies-literature | 2026 Jan-Dec

REPOSITORIES: biostudies-literature