Rethinking How We Measure Sleep Apnea Treatment

Obstructive sleep apnea (OSA) is traditionally evaluated at discrete timepoints using sleep studies. This episodic approach limits understanding of how patients respond to therapy over time. Our work focuses on leveraging longitudinal, personalized sleep tracking technologies to better characterize treatment response and guide clinical decision-making.

Wearables as Continuous Physiologic Sensors

Consumer sleep technologies (CSTs) provide nightly data on both sleep and cardiovascular physiology. In patients undergoing hypoglossal nerve stimulation (HNS), our studies demonstrated 1) Reduced sleep fragmentation (WASO) with increasing stimulation intensity, 2) Changes in cardiovascular metrics, including decreases in average heart rate and heart rate variability during therapy titration. 3) Longitudinal trends across >100 nights per patient, revealing treatment responses not captured in single sleep studies.

Additional work shows that wearable-derived metrics correlate with patient-reported sleep outcomes, supporting their role as adjunctive markers of treatment response.   Parallel studies using smartphone-based snoring analysis demonstrate that symptom metrics decline over time and track with therapy adjustments.

Linking OSA Therapy to Cardiovascular Physiology

Beyond sleep quality, a central focus of our work is understanding how OSA treatment impacts cardiovascular physiology. OSA is strongly associated with alterations in autonomic balance and cardiovascular risk. Our findings suggest that changes in heart rate and heart rate variability may reflect physiologic responses to therapy and shifts in autonomic regulation that are specific to each patient.  Wearables enable continuous assessment of cardiovascular signals during sleep, offering a window into treatment-related physiologic adaptation.  Individual variability in these metrics may help identify patients with differential cardiovascular sensitivity to therapy 

This line of investigation aims to connect OSA treatment not only to symptom improvement, but also to downstream cardiovascular health and risk modification.

Toward a New Care Paradigm

Our ongoing work integrates sleep tracking technologies and serial home sleep studies to develop a more responsive model for postoperative management after sleep surgery, hypoglossal nerve stimulation and chronic OSA management.  This work focuses on real-time assessment of treatment response, data-driven therapy titration, and optimization of care pathways based on sleep data.   The goal is to develop more responsive models for obstructive sleep apnea.  Specifically, we hope to identify when therapy is effective in real time, reduce undertreatment and over-titration, and support personalized trajectories of recovery and response.  By integrating physiologic cardiac data with sleep metrics, the goal is to better understand how OSA therapies influence cardiovascular function and long-term health risks.

Why This Matters

OSA is a chronic, heterogeneous disease with significant night-to-night variability. Our work suggests that continuous, patient-specific data can shift care from episodic evaluation to dynamic, precision management.

Wearables are not replacements for diagnostic sleep studies—but they may become a critical adjunct, enabling clinicians to better understand treatment response, optimize interventions, and ultimately improve patient-centered outcomes.

Ongoing research is focused on validating these tools, integrating multimodal data streams, and defining how wearable-derived metrics can be operationalized in clinical decision-making pathways.