Snoring Vibration: A Robust Measure for Predicting Treatment Outcome for Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) represents a prevalent condition impacting over 9% of the general adult population. Various treatment options have been clinically proposed and utilized, with a particular focus on continuous positive airway pressure (CPAP) and oral appliances due to their overall effectiveness and higher adherence rates. CPAP therapy has demonstrated greater effectiveness but lower adherence compared to oral appliances. However, treatment success of oral appliances is not always guaranteed, hence sleep physicians are more cautious in their prescriptions unless they can reasonably estimate the chance of responding to oral appliance therapy. Prior studies often rely on invasive or inconvenient methodologies such as drug-induced sleep endoscopy (DISE), cephalometry, multisensor catheters, or full polysomnography (PSG). In this prospective study, we collected data with a home sleep apnea test (HSAT) device from 50 participants (38 using mandibular advancement devices [MADs] and 12 using tongue stabilizing devices [TSDs]). We used a simple yet informative data source: snoring vibrations extracted from a nasal pressure sensor with a low sampling frequency (125 Hz). Using spectro-temporal analysis of the snoring signal, we successfully predicted therapy efficacy with accuracies of 88% for MAD and 91% for TSD. Our proposed methodology presents a promising approach that can be utilized without further need for PSG or integrated within PSG testing for accurate prediction of oral appliance efficacy.