2026-10-07T21:02:40Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33952009 2026-09-21T10:40:44Z category_16 portal_316 item_type_3 month_year_09_2026

Table 1_WMRE2030: integrating wearable devices, multi-omics, and artificial intelligence–driven real-time feedback into a daily-scale closed-loop framework for a new era of precision exercise.docx Mingrui Wang (11876964) Lun Chen (752140) Mingyue Yin (17919071) Bing Zhang (129) Jilong Wu (20369153) Haowei Sun (12358969) Linghua Yan (25083013) Bing Wei (2588902) Feng Zhang (6548) Cunjian Bi (7251932) Jun Wang (5906) Shaoliang Zhang (7523498) Physiology artificial intelligence closed-loop feedback digital health exercise physiology multi-omics personalised intervention precision exercise wearable devices <p>Precision exercise is increasingly supported by wearable technologies, multi-omics profiling, and artificial intelligence; however, these components are often applied in isolation, limiting their capacity to support continuous and interpretable decision-making in real-world settings. This review proposes WMRE2030, a day-scale closed-loop methodological framework integrating Wearables (W), Multi-omics (M), AI-driven Real-Time Feedback (R), and Exercise (E). Within this architecture, wearable devices continuously capture physiological, behavioural, and contextual states; multi-omics provides relatively stable or periodically updated biological background, response potential, and safety constraints; artificial intelligence organizes heterogeneous information into evidence-constrained and traceable decision support; and exercise functions as the executable intervention whose outcomes are returned to the system for iterative updating. The framework emphasizes “the same architecture, different parameters, “ allowing sensors, omics inputs, decision thresholds, and levels of professional oversight to be adapted across clinical populations, the general population, and high-performance athletes. WMRE2030 should currently be regarded as a testable methodological roadmap rather than a validated autonomous prescription system. Future research should evaluate its incremental value through longitudinal, micro-randomized, and multicentre studies, while addressing interoperability, privacy, algorithmic transparency, safety brakes, cost-effectiveness, scalability, and equitable access. By connecting biological interpretation with continuous sensing and adaptive decision support, WMRE2030 may provide a practical pathway toward more reliable and sustainable precision exercise.</p> 2026-09-21T10:40:44Z Dataset Dataset 10.3389/fphys.2026.1883295.s001 https://figshare.com/articles/dataset/Table_1_WMRE2030_integrating_wearable_devices_multi-omics_and_artificial_intelligence_driven_real-time_feedback_into_a_daily-scale_closed-loop_framework_for_a_new_era_of_precision_exercise_docx/33952009 CC BY 4.0