A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process

Abstract

Background: In response to the shortcomings of the current Alzheimer’s disease (AD) early populations assessment, which is based on neuropsychological scales with high subjectivity, low accuracy of repeated measurements, tedious process and dependence on physicians, it was found that digital biomarkers based on the writing process can effectively characterize the cognitive deficits of patients with mild cognitive impairment (MCI) due to AD. Methods: This study designed a digital writing assessment paradigm, extracted dynamic handwriting and image data during the paradigm assessment process, and analyzed digital biomarkers of the writing process to assess subjects’ cognitive functions. A total of 72 subjects, including 34 health controls (HC) and 38 MCI due to AD, were enrolled in this study. Results: Their combined screening efficacy of digital biomarkers based on the MCI writing process due to AD populations having an area under curve (AUC) of 0.918, and a confidence interval (CI) of 0.854–0.982, was higher than the Montreal Cognitive Assessment Scale (AUC = 0.859, CI = 0.772–0.947) and the Mini-mental State Examination Scale (AUC = 0.783, CI = 0.678–0.888). Conclusion: Therefore, digital biomarkers based on the writing process can characterize and quantify the cognitive function of MCI due to AD populations at a fine-grained level, which is expected to be a new method for intelligent screening and early warning of early AD populations in a community-based physician-free setting.