A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process
BackgroundIn 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 biomarker...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Computational Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fncom.2025.1564932/full |
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| author | Shuwu Li Kai Li Kai Li Jiakang Liu Shouqiang Huang Chen Wang Yuting Tu Bo Wang Pengpeng Zhang Yuntian Luo Yanli Zhang Yanli Zhang Tong Chen |
| author_facet | Shuwu Li Kai Li Kai Li Jiakang Liu Shouqiang Huang Chen Wang Yuting Tu Bo Wang Pengpeng Zhang Yuntian Luo Yanli Zhang Yanli Zhang Tong Chen |
| author_sort | Shuwu Li |
| collection | DOAJ |
| description | BackgroundIn 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.MethodsThis 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.ResultsTheir 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).ConclusionTherefore, 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. |
| format | Article |
| id | doaj-art-8088454f8e71453aa7ef8ef462bbca6f |
| institution | DOAJ |
| issn | 1662-5188 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Computational Neuroscience |
| spelling | doaj-art-8088454f8e71453aa7ef8ef462bbca6f2025-08-20T03:19:50ZengFrontiers Media S.A.Frontiers in Computational Neuroscience1662-51882025-06-011910.3389/fncom.2025.15649321564932A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing processShuwu Li0Kai Li1Kai Li2Jiakang Liu3Shouqiang Huang4Chen Wang5Yuting Tu6Bo Wang7Pengpeng Zhang8Yuntian Luo9Yanli Zhang10Yanli Zhang11Tong Chen12School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, ChinaSchool of Information Engineering, Hangzhou Medical College, Hangzhou, ChinaZhejiang Engineering Research Center for Brain Cognition and Brain Diseases Digital Medical Instruments, Hangzhou Medical College, Hangzhou, ChinaSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, ChinaSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, ChinaSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, ChinaSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, ChinaSchool of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, ChinaSchool of Information Engineering, Hangzhou Medical College, Hangzhou, ChinaSchool of Information Engineering, Hangzhou Medical College, Hangzhou, ChinaSchool of Information Engineering, Hangzhou Medical College, Hangzhou, ChinaZhejiang Engineering Research Center for Brain Cognition and Brain Diseases Digital Medical Instruments, Hangzhou Medical College, Hangzhou, ChinaDepartment of Neurology, Second Medical Center of Chinese PLA General Hospital, Beijing, ChinaBackgroundIn 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.MethodsThis 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.ResultsTheir 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).ConclusionTherefore, 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.https://www.frontiersin.org/articles/10.3389/fncom.2025.1564932/fullmild cognitive impairmentAlzheimer’s diseasedigital biomarkersearly warningwriting |
| spellingShingle | Shuwu Li Kai Li Kai Li Jiakang Liu Shouqiang Huang Chen Wang Yuting Tu Bo Wang Pengpeng Zhang Yuntian Luo Yanli Zhang Yanli Zhang Tong Chen A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process Frontiers in Computational Neuroscience mild cognitive impairment Alzheimer’s disease digital biomarkers early warning writing |
| title | A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process |
| title_full | A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process |
| title_fullStr | A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process |
| title_full_unstemmed | A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process |
| title_short | A new method for community-based intelligent screening of early Alzheimer’s disease populations based on digital biomarkers of the writing process |
| title_sort | new method for community based intelligent screening of early alzheimer s disease populations based on digital biomarkers of the writing process |
| topic | mild cognitive impairment Alzheimer’s disease digital biomarkers early warning writing |
| url | https://www.frontiersin.org/articles/10.3389/fncom.2025.1564932/full |
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