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A Programming Algorithm for Optimizing Hypoglossal Nerve Stimulator Respiratory Entrainment
David T Kent1, Holly A Budnick1, Katherine K Green2
1Department of Otolaryngology-Head and Neck Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A.
The Laryngoscope
|November 8, 2024
Summary
Hypoglossal nerve stimulation (HNS) offers a surgical solution for obstructive sleep apnea. This study introduces an algorithm to optimize HNS respiratory entrainment using office-based adjustments for better patient outcomes.
Area of Science:
- Neuromodulation
- Sleep Medicine
- Biomedical Engineering
Background:
- Obstructive sleep apnea (OSA) is a common sleep disorder.
- Hypoglossal nerve stimulation (HNS) is an effective surgical treatment for OSA.
- Current HNS devices offer respiratory entrainment settings that are underutilized.
Observation:
- The most common HNS device has programming settings for respiratory entrainment.
- These settings are not frequently used by clinicians.
- Optimizing HNS requires adjustments based on patient's breathing patterns.
Findings:
- A novel algorithm enables office-based adjustments for HNS respiratory entrainment.
- This algorithm facilitates real-time sensing and optimization of stimulation parameters.
- The proposed method aims to improve the efficacy of HNS therapy.
Implications:
- This approach could enhance treatment effectiveness for OSA patients using HNS.
- Office-based adjustments may lead to more personalized and efficient HNS therapy.
- Wider utilization of respiratory entrainment can improve patient adherence and outcomes.
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