Editorial: The promise of sleep technology

In the domain of obstructive sleep apnea (OSA), Nokes et al. sought to elucidate the mechanisms underlying the heterogeneous response to weight loss in OSA, finding that upper airway length was strongly associated with apnea hypopnea index (AHI), hypoxic burden, and ventilatory burden, whereas tongue fat percentage showed no significant association with AHI. Goldstein et al. reported performance of the SANSA device (Huxley Medical, Inc., Atlanta, GA), a novel chest sensor integrating electrocardiogram, photoplethysmography, oximetry, acoustic sensor, and accelerometry, demonstrating robust diagnostic accuracy for OSA detection. Hu et al. assessed the relationship between neurocognitive function and elevated low-frequency narrow band, a high loop gain biomarker that may be a clinically useful predictor of cognitive improvement following CPAP initiation. Ingolfsdottir et al reported that wearable home sleep testing was able to detect undiagnosed OSA in a sample of obese children aged 4-9, highlighting that contemporary wearable platforms hold promise in diagnosing more children for OSA.Sleep monitoring does not exist in a silo and has important ramifications for other disorders, including mental health conditions. Defillo et al. investigated odds ratio product (ORP) across sleep stages and its association with depressive symptoms in a large clinical cohort, demonstrating that ORP holds promise as a non-invasive biomarker for depressive symptoms. Defillo et al. also evaluated the screening accuracy of a novel software, MEB-001, for detecting current major depressive episode (cMDE) in individuals identified as with and without suspected comorbid insomnia and sleep apnea (COMISA), finding that MEB-001 achieved consistent cMDE screening performance comparable to the Patient Health Questionnaire, 9 items (PHQ-9). Nevertheless, CWST has largely been employed to approximate legacy polysomnography (PSG)-derived sleep metrics and are primarily considered alternatives to actigraphy. Such paradigm fails to capitalize on their distinctive capabilities of these devices, including cardiac autonomic monitoring alongside motion sensing, near-real-time data transfer and processing, and simultaneous capture of multiple health data streams (objective and self-reported) that could allow for more cutting-edge applications. For example, sleep estimates derived from movement and cardiac autonomic signals are not equivalent to EEG-defined sleep, yet may yield distinct and complementary insight into sleep physiology and changes related to prevalent and incident health conditions. Similarly, while some consumer wearables can now stratify risk for OSA, their signals may also enable modeling of cardiac autonomic responses to treatment, distinguishing responders from nonresponders and potentially identifying whether therapy is likely to reduce future OSA-associated sequelae, including cardiovascular disease. Moreover, by integrating sleep parameters with self-reported symptoms and contextual data, CWST paired with app-delivered behavioral treatment could support just-in-time adaptive interventions, further refined through reinforcement learning approaches, advancing personalized care for insomnia. Implementation studies are desperately needed to realize the full potential of CWST while systematically identifying potential undesired consequences.In the domain of OSA assessment, emerging sleep technologies are poised to transform clinical sleep medicine practice across four distinct scenarios in the years to come (Table) ( This special Frontiers issue underscores the transformative potential of emerging sleep technologies, which present unprecedented opportunities for the diagnosis and management of sleep disorders. Capitalizing this momentum, however, necessitates the continued generation of evidence-based research, alongside sustained interdisciplinary collaboration. Ultimately, the promise of sleep technology will be realized through a unified commitment, ensuring that future advances equitably improve sleep health.