Generalizing Parkinson's disease detection using keystroke dynamics: a self-supervised approach.
Journal:
Journal of the American Medical Informatics Association : JAMIA
Published Date:
May 20, 2024
Abstract
OBJECTIVE: Passive monitoring of touchscreen interactions generates keystroke dynamic signals that can be used to detect and track neurological conditions such as Parkinson's disease (PD) and psychomotor impairment with minimal burden on the user. However, this typically requires datasets with clinically confirmed labels collected in standardized environments, which is challenging, especially for a large subject pool. This study validates the efficacy of a self-supervised learning method in reducing the reliance on labels and evaluates its generalizability.
