The Next Era of Remote Patient Monitoring: Wearables, Digital Biomarkers, Artificial Intelligence, and Personalized Chronic Disease Care

Chronic diseases remain the dominant driver of healthcare utilization, disability, and cost, yet care delivery continues to rely heavily on episodic encounters, delayed symptom reporting, and reactive treatment adjustment. Remote patient monitoring is rapidly evolving from simple physiologic data capture into a broader infrastructure for continuous, personalized, and proactive care. This Research Topic aims to examine how wearables, connected sensors, digital biomarkers, artificial intelligence, and closed-loop therapeutic models can transform chronic disease management across clinical settings.

The goal is to bring together health services researchers, clinicians, engineers, digital medicine scientists, implementation experts, and policy leaders to define the next era of remote patient monitoring. We seek work that moves beyond device adoption alone and addresses how continuous real-world data can be validated, interpreted, integrated into care pathways, and translated into measurable improvements in outcomes, equity, access, safety, and value.

Wearables, smartphones, implantable devices, home diagnostics, and ambient sensing technologies now make it possible to collect longitudinal data on physiology, behavior, function, symptoms, and treatment response outside traditional clinical environments. At the same time, artificial intelligence and advanced analytics are creating new opportunities for risk prediction, digital phenotyping, clinical decision support, and personalized intervention.

Despite this promise, major challenges remain. Many remote monitoring programs generate data without clear clinical actionability, validated endpoints, workflow integration, reimbursement pathways, or evidence of durable benefit. Digital biomarkers require rigorous validation, regulatory clarity, and contextual interpretation. Artificial intelligence-enabled systems must be transparent, equitable, clinically useful, and safely embedded into care delivery. The field now needs a more mature health services framework that links sensing to prediction, prediction to intervention, and intervention to improved outcomes.

This Research Topic welcomes manuscripts examining the development, validation, implementation, evaluation, and policy implications of next-generation remote patient monitoring in chronic disease management. Areas of interest include, but are not limited to:

• Wearables, implantables, smartphones, home diagnostics, and ambient sensors for continuous monitoring

• Digital biomarkers and digital phenotyping for chronic disease progression, symptom burden, functional status, and treatment response

• Artificial intelligence, machine learning, predictive analytics, digital twins, and clinical decision support for risk stratification and personalized care

• Closed-loop therapeutic ecosystems, including adaptive medication titration, device optimization, neuromodulation, rehabilitation, behavioral interventions, and human-in-the-loop care models

• Integration of remote monitoring into clinical workflows, electronic health records, care teams, and population health programs

• Applications across cardiometabolic disease, neurology, pulmonology, oncology, mental health, aging, rehabilitation, and complex multimorbidity

• Equity, access, digital literacy, patient engagement, privacy, cybersecurity, reimbursement, regulation, and health economics

• Clinical trials, pragmatic studies, real-world evidence, implementation science, systematic reviews, policy analyses, and expert perspectives

Together, this collection will explore how remote patient monitoring can mature from passive data collection into an intelligent, learning infrastructure for continuous precision care.

Topic Editor, Shaheen Lakhan, is the founder of Boricua Bio and a board director of Frenelle Pharma and Neurocentrx. Topic Editor, Harald Murck, owns a patent in the area of major depression.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: remote patient monitoring; wearables; digital biomarkers; artificial intelligence; chronic disease management; closed-loop therapeutics; personalized medicine; health services innovation

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.