Abstract
Background: The rapid expansion of the Internet of Medical Things (IoMT) has created unprecedented opportunities for continuous patient monitoring outside traditional clinical settings. This comprehensive narrative review examines the applications, technical architectures, clinical outcomes, and implementation challenges of IoT/IoMT-based remote patient monitoring (RPM) systems from 2018 to 2026.
Methods: This narrative review conducted systematic searches across PubMed, Web of Science, Scopus, Embase, ProQuest, Cochrane Library, and Google Scholar. After removing duplicates and screening titles and abstracts, full texts of eligible studies were reviewed. The review synthesized evidence from 45+ studies examining IoMT-RPM systems across various clinical domains.
Findings: Evidence demonstrates that IoMT systems follow a standardized four-layer architecture (sensor, communication, cloud/edge processing, application). Common sensors include ECG, blood oxygen saturation (SpO2), blood pressure, body temperature, and blood glucose. The strongest evidence exists for patient safety and reduction in adverse clinical events, while quality-of-life outcomes remain mixed and cost-effectiveness evidence is insufficient. AI-driven approaches, including Transformer-based models, have achieved classification accuracies exceeding 98%. Key challenges include data security, interoperability, and clinical workflow integration.
Conclusion: IoMT is a mature technology with demonstrable clinical benefits; however, sustainable deployment requires data exchange standardization, security-by-design, clinical sensor validation, and user-centered design. Future research should prioritize long-term randomized controlled trials, comprehensive health economic evaluations, and outcome assessments in diverse populations.