Novel Technologies in the Diagnosis and Management of Sleep-disordered Breathing: Volume IV

Sleep-disordered breathing (SDB), ranging from habitual snoring to severe obstructive sleep apnea (OSA), is highly prevalent and represents a growing global healthcare burden. Besides disrupting sleep, SDB leads to detrimental outcomes such as excessive daytime sleepiness, neurocognitive impairment, and increased cardiometabolic morbidities.

In the Research Topic Volumes I–III, we observed the technology developments that enable rapid innovations in the field of SDB. Simple diagnostic methods and novel disease management solutions strongly suggest that the SDB diagnostics and management are moving from a one-size-fits-all approach to precision sleep medicine.

Possible topics of interest include, but are not limited to:

1. Novel insights on pathophysiology of OSA from physiological signals collected in standard sleep studies;

2. Novel signal acquisition and sensor technologies;

3. Alternative polysomnography metrics and analyses;

4. Minimally invasive data collection for screening and long-term follow-up of SDB

5. Application of artificial intelligence, machine learning, and big data for SDB diagnostics and management;

6. Biomarkers and phenotyping-based prediction models on treatment outcomes;

7. Big data approaches and telemedicine in sleep medicine;

8. Emerging technologies to provide alternative treatment options for better treatment adherence and clinical outcomes;

9. Disease management approaches encompass phenotyping, and endotyping for better patient characterization including disease severity, daytime symptoms, as well as comorbidity conditions;

10. Patient-reported outcome measures assessment and sleep disparities studies;

We are interested in original works, protocols, literature reviews, meta-analyses, perspectives and expert consensus related to sleep disorders with a specific focus on SDB.

• Novel Technologies in the Diagnosis and Management of Sleep-Disordered Breathing

• Novel Technologies in the Diagnosis and Management of Sleep-Disordered Breathing: Volume II

• Novel Technologies in the Diagnosis and Management of Sleep-Disordered Breathing: Volume III

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
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• 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
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Registered Report
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Ambulatory sleep test, artificial Intelligence, bioinformatics, cardiometabolic disease, machine learning, non-PAP therapy, obstructive sleep apnea, oximetry, phenotype, pulse wave analysis

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.