Artificial Intelligence–Based Computerized Digit Vigilance Test in Community-Dwelling Older Adults: Development and Validation Study
We developed an AI-CDVT, which leveraged AI to extract attentional features from video recordings and integrated them to generate a comprehensive attention score. Our findings demonstrated good validity and test-retest reliability for the AI-CDVT, suggesting its potential as a reliable and valid tool for assessing sustained attention in older adults.
Authors
- Mai Thi Thuy Vu (ORCID: https://orcid.org/0009-0007-0238-3569)
- Dorothy Bai (ORCID: https://orcid.org/0000-0002-9836-1415)
- Shih‐Chieh Lee (ORCID: https://orcid.org/0000-0003-4279-522X)
- Gong‐Hong Lin (ORCID: https://orcid.org/0000-0001-6369-7165)
- Yi‐Jing Huang (ORCID: https://orcid.org/0000-0003-2943-8287)
- Tzu-Chuan Chiu (ORCID: https://orcid.org/0009-0005-6228-6432)
Institutions
- National Taiwan University (TW)
- National Taiwan University Hospital (TW)
- Nam Dinh University of Nursing (VN)
- Taipei Medical University (TW)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2025-11-26
- DOI
- https://doi.org/10.2196/73038
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 0.00