ArticleArchives of osteoporosis2026
Quantifying impact loading for osteoporosis prevention: a study on the relationship between ground reaction forces and wearable impact data.
Article in Archives of osteoporosis, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
High-impact exercise can strengthen bones, but clinical use is limited because mechanical loading is difficult to measure outside laboratories. We validated a wrist-worn accelerometer against force-plate ground reaction forces and found that wearable data reliably reflect impact loading. This approach may enable practical monitoring of bone-stimulating exercise in real-world settings. PURPOSE: Mechanical loading must surpass a minimum intensity threshold to stimulate osteogenic adaptation, yet clinicians lack practical tools to quantify impact dose outside laboratory settings. Wearable accelerometers could enable safe, scalable monitoring of bone-strengthening exercise, but their validity for estimating osteogenic loading remains uncertain. This study examined whether wrist-worn accelerometry can support approximate estimation and coarse classification of platform-derived impact loading during maximal countermovement jumps in postmenopausal women.
methodsThirty-eight women were enrolled; 37 contributed 125 valid CMJs with concurrent force-platform and wrist-accelerometer recordings. The primary model predicted peak platform-derived vertical acceleration from peak wrist vector-magnitude acceleration and body mass. Coefficient inference used linear regression with participant-clustered robust standard errors. Predictive performance and four-class osteogenic classification (< 2 g, 2- < 3 g, 3- < 3.9 g, ≥ 3.9 g) were evaluated using leave-one-subject-out cross-validation. Fuller anthropometric models and residual-based outlier filtering were examined as sensitivity analyses.
resultsIn the primary reduced model, wrist vector magnitude and body mass were both independently associated with peak platform acceleration. In leave-one-subject-out validation, the model explained 44.3% of the variance (R
conclusionsWrist-worn accelerometry provided limited precision for per-jump estimation of platform-derived loading, even under constrained laboratory conditions. However, it retained moderate utility for coarse, bin-based classification of impact intensity during maximal CMJs performed with hands on hips. Its most defensible application is session-level monitoring and conservative progression in home- and community-based osteogenic exercise programs, rather than replacement of laboratory force-platform measurement.
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