Automated Acoustic Analysis in Detection of Spontaneous Swallows in Parkinson's Disease

Acoustic monitoring of swallow frequency has become important as the frequency of spontaneous swallowing can be an index for dysphagia and related complications. In addition, it can be employed as an objective quantification of ingestive behavior. Commonly, swallowing complications are manually detected using videofluoroscopy recordings, which require expensive equipment and exposure to radiation. In this study, a noninvasive automated technique is proposed that uses breath and swallowing recordings obtained via a microphone located over the laryngopharynx. Nonlinear diffusion filters were used in which a scale-space decomposition of recorded sound at different levels extract swallows from breath sounds and artifacts. This technique was compared to manual detection of swallows using acoustic signals on a sample of 34 subjects with Parkinson's disease. A speech language pathologist identified five subjects who showed aspiration during the videofluoroscopic swallowing study. The proposed automated method identified swallows with a sensitivity of 86.67 %, a specificity of 77.50 %, and an accuracy of 82.35 %. These results indicate the validity of automated acoustic recognition of swallowing as a fast and efficient approach to objectively estimate spontaneous swallow frequency.