Digital Biomarkers for Early Detection of Alzheimer’s Disease: A Comprehensive Review and Bibliometric Analysis

Alzheimer’s disease (AD) is the most common form of dementia marked by cognitive decline and memory loss. Early detection is essential for timely intervention; however, traditional biomarkers, including cerebrospinal fluid (CSF) assays, neuroimaging, and cognitive assessments, are limited by cost, invasiveness, and accessibility. Digital biomarkers, obtained from wearable sensors, smartphone applications, speech analysis, and other passive monitoring technologies, represent a promising alternative for scalable, non-invasive, and continuous assessment of early cognitive decline. This paper provides a comprehensive review of the current landscape of digital biomarkers for AD diagnosis, emphasizing their potential application in the preclinical and prodromal stages of the disease. In addition, a bibliometric analysis demonstrates the rapid expansion of digital biomarker research, highlighting key trends in publication volume, influential authors, institutions, and interdisciplinary collaborations. Despite the significant promise of digital biomarkers, challenges remain regarding validation, regulatory approval, data privacy, and integration into clinical practice. The results indicate that future research should prioritize standardization, multimodal biomarker integration, and large-scale longitudinal studies to fully realize the potential of digital technologies in AD detection.