Handgrip Strength and Early Screening of Alzheimer’s Disease: Current Evidence and Emerging Role of Artificial Intelligence

Abstract

Alzheimer’s disease (AD) is the most prevalent progressive neurodegenerative disorder in older adults, marked by insidious cognitive decline and gradual loss of functional independence. Growing evidence suggests that handgrip strength (HGS) assessment may provide a simple, noninvasive approach for early screening of AD-related functional changes. This review summarizes current evidence on the association between HGS and AD, while distinguishing evidence obtained directly in AD/MCI populations from evidence derived from general aging, cognitive decline, dementia, or non-AD disease cohorts. Longitudinal and cohort studies have reported associations between reduced grip strength and a higher risk of MCI and AD; however, HGS is influenced by age, sex, body composition, frailty, physical activity, nutritional status, comorbidities, and measurement procedures, and therefore should not be interpreted as an AD-specific diagnostic biomarker. Beyond maximal grip force, dynamic features such as force variability, temporal instability, fatigue-related change, contraction smoothness, and bilateral asymmetry may provide additional information on motor control. The review further discusses measurement standardization, disease specificity, residual confounding, reverse causality, and the methodological requirements of AI-assisted analysis. Recent advances in machine learning, deep learning, and multimodal analysis are considered as tools for integrating multidimensional functional information within an early-screening framework rather than as established diagnostic solutions. In community and home settings, HGS-based assessment may serve as a first-stage screening approach to identify individuals who warrant further clinical evaluation; definitive assessment should remain based on appropriate cognitive/behavioral and neuropsychological examinations and, when clinically indicated, neuroimaging or established AD biomarkers. Future studies should prioritize standardized protocols, prospective longitudinal designs, direct comparison with conventional clinical variables, external validation, calibration, and clinically meaningful screening outcomes.