This study investigates behavioral intentions of older adults toward stroke monitoring products by adapting the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). Focusing on 421 Chinese older adults (aged ≥60), we refined the model by excluding hedonic motivation and price value while emphasizing gerontological factors (e.g., family support, habitual health behaviors). Structural equation modeling revealed that performance expectancy (β = 0.180), effort expectancy (β = 0.172), social influence (β = 0.127), facilitating conditions (β = 0.175), and habit (β = 0.132) significantly influenced behavioral intention, which further predicted usage behavior (β = 0.153). Gender analysis highlighted females’ heightened sensitivity to health data (p < 0.001). Design implications derived from these findings include simplified hardware interfaces (e.g., one-touch operation) and app features (e.g., AIdriven risk alerts, family-sharing functions), validated through usability tests (N = 30) showing improved ease of use and reduced technostress. This research extends UTAUT2’s applicability to gerontechnology contexts and provides actionable insights for developing age-friendly healthcare devices, ultimately enhancing older adults’ health autonomy.