Acoustic estimation of neck fluid volume.

Recently we showed that fluid accumulation in the neck can narrow the upper airway (UA) and increase its collapsibility, which may exacerbate obstructive sleep apnea (OSA). However, the available methods for measuring neck fluid volume (NFV) are inconvenient and expensive. Narrowing of the UA due to fluid accumulation could change acoustic characteristics of respiratory sounds. In this study, we developed a novel approach for non-invasive estimation of NFV from acoustic measurements. Twenty-eight healthy subjects lay awake and supine for 90 min while NFV and tracheal sounds were measured simultaneously using bioimpedance and a microphone, respectively. Sets of tracheal sound features were calculated in time and frequency domains and were reduced using methods based on regression and minimum-redundancy-maximum-relevance. The resulting feature sets were applied to a multi-linear regression and a mixture-density neural network to estimate NFV. Our results show very small relative estimation errors of 1.25 and 3.23%, based on the regression and neural network methods, respectively. These results support the practical application of this technology in diagnosing fluid accumulation in the neck and its possible contributions to the pathogenesis of OSA.