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. 2025 Jun 4:19:1564932.
doi: 10.3389/fncom.2025.1564932. eCollection 2025.

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

Shuwu Li #  1 , Kai Li #  2   3 , Jiakang Liu #  1 , Shouqiang Huang  1 , Chen Wang  1 , Yuting Tu  1 , Bo Wang  1 , Pengpeng Zhang  2 , Yuntian Luo  2 , Yanli Zhang  2   3 , Tong Chen  4
Affiliations

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

Shuwu Li et al. Front Comput Neurosci. .

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.

Keywords: Alzheimer’s disease; digital biomarkers; early warning; mild cognitive impairment; writing.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The schematic diagram of the paradigm.
Figure 2
Figure 2
Illustration of information processing speed digital biomarkers.
Figure 3
Figure 3
Illustration of executive function digital biomarkers.
Figure 4
Figure 4
The information of paradigm. (A) Evaluation scene; (B) visualize the results, dynamic trajectory diagram; (C) visualize the results, writing results.
Figure 5
Figure 5
Data distribution of demographic and clinical characteristics in the MCI and HC groups.
Figure 6
Figure 6
Digital biomarkers of the writing process with intergroup variability in the MCI and HC groups.
Figure 7
Figure 7
ROC curves, area under the curve, and 95% confidence intervals for the prediction of cognitive deficits for each of the 3 writing process digital biomarkers after stepwise regression for the MCI and HC groups of the populations.
Figure 8
Figure 8
ROC curves, area under the curve, and 95% confidence intervals for the prediction of cognitive deficits by multiple combined digital biomarkers of the writing process, the MMSE scale, and the MoCA scale in the MCI and HC groups of the populations.
See this image and copyright information in PMC

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