Wearable-derived Digital Biomarkers For Mobility Assessment And Risk Stratification In Older Adults: A Scoping Review

Gerontology. 2026 Jul 30:1. doi: 10.1159/ger/acxag001. Online ahead of print.

ABSTRACT

BACKGROUND: The global population aged ≥60 years will reach 2.1 billion by 2050. Mobility decline is a critical precursor of disability, hospitalization, and mortality in older adults, yet clinic-based assessments may have limited ecological validity and miss subtle deteriorations observable only under free-living conditions. Wearable technology offers continuous objective monitoring through digital biomarkers that may enable earlier intervention.

OBJECTIVE: To systematically map current evidence on digital biomarkers derived from wearable technology for mobility assessment and risk stratification in older adults (≥60 years), examining biomarker types, sensor devices, validation approaches, clinical applications, and evidence gaps. Evidence was stratified descriptively across cross-sectional mobility impairment, fall/frailty risk stratification, and longitudinal/prognostic decline.

METHODS: Following Joanna Briggs Institute (JBI) methodology and PRISMA-ScR guidelines, we searched four databases (Scopus, PubMed/MEDLINE, Web of Science Core Collection, and IEEE Xplore) from 1 January 2019 to 31 March 2026. The protocol was prospectively registered (OSF; https://doi.org/10.17605/OSF.IO/PABFT). Two independent reviewers conducted screening and data extraction; disagreements were resolved by a third reviewer. A narrative synthesis was employed. Formal risk-of-bias assessment was not undertaken, consistent with JBI scoping-review methodology.

RESULTS: From 3,345 identified records, 97 primary empirical studies met inclusion criteria after removing 2,796 duplicates and applying predefined eligibility (Cohen's κ = 0.86 title/abstract; κ = 0.88 full-text). Seven biomarker categories were identified (non-mutually exclusive; percentages sum to >100%): gait spatiotemporal parameters (38.1%), daily-life mobility metrics (24.7%), frailty-related biomarkers (18.6%), cognitive-physical dual biomarkers (15.5%), circadian rhythm parameters (12.4%), gait dynamics/complexity (9.3%), and consumer device metrics (8.2%). Validation performance, where comparable, ranged from ICC 0.70-0.98 (reliability vs reference systems) and AUC 0.73-0.94 for fall/frailty discrimination; these are study-specific, not pooled estimates. Among circadian biomarkers, one large registry study (UK Biobank age-stratified analysis) reported a CosinorAge hazard ratio of 1.58 per year for all-cause mortality (95% CI 1.52-1.64), warranting prospective validation in dedicated older-adult cohorts.

CONCLUSION: Wearable-derived digital biomarkers show promising, study-specific criterion and discriminative validity for mobility assessment and fall/frailty risk stratification in older adults across multiple clinical domains; however, direct longitudinal evidence for detecting mobility decline remains limited and heterogeneous. Evidence consistency and maturity vary across biomarker domains and are descriptive rather than derived from a formal risk-of-bias assessment. Critical gaps remain in longitudinal validation, standardised protocols, implementation science, and equity-focused research.

PMID:42531184 | DOI:10.1159/ger/acxag001