Validation of the optimal site in the neck region for detecting swallowing sounds

Recently, the swallowing sound has been used to detect swallowing events non-invasively. A previous study, using an accelerometer, showed that the site over the lateral border of the trachea immediately inferior to the cricoid cartilage was the optimal site for detecting swallowing sounds. However, the optimal site for detection of the swallowing sound using a microphone remains undetermined. To validate the optimal site in the neck region for detecting swallowing sounds. Fourteen healthy subjects (mean age, 27·6 ± 2·2 years; seven male and seven female) participated in this study. Twenty condenser microphones were attached to 20 sites on the left neck surface to detect swallowing sounds. Participants were instructed to swallow five different stimuli three times as follows: Resting saliva, 1 and 5 mL of Japanese tea, and 1 and 5 mL of yoghurt. Mean relative peak intensity was used to indicate the magnitude of the swallowing sound. Sound spectrograms were used to illustrate differences in the properties of swallowing sounds. Mean relative peak intensity number was highest in sites at the inferior border of the mandible just above the sternocleidomastoid muscle (site 11) and sites over the lateral border of the trachea immediately inferior to the cricoid cartilage (site 8). Comparison of spectrograms showed a greater density distribution of higher frequency components at site 11 compared with site 8. These results indicate that the inferior border of the mandible just above the sternocleidomastoid muscle is the optimal site for the detection of swallowing sounds.

A novel automated detection system for swallowing sounds during eating and speech under everyday conditions

The wave analysis of swallowing sounds has been receiving attention because the recording process is easy and non-invasive. However, up until now, an expert has been needed to visually examine the entire recorded wave to distinguish swallowing from other sounds. The purpose of this study was to establish a methodology to automatically distinguish the sound of swallowing from sound data recorded during a meal in the presence of everyday ambient sound. Seven healthy participants (mean age: 26·7 ± 1·3 years) participated in this study. A laryngeal microphone and a condenser microphone attached to the nostril were used for simultaneous recording. Recoding took place while participants were taking a meal and talking with a conversational partner. Participants were instructed to step on a foot pedal trigger switch when they swallowed, representing self-enumeration of swallowing, and also to achieve six additional noise-making tasks during the meal in a randomised manner. The automated analysis system correctly detected 342 out of the 352 self-enumerated swallowing events (sensitivity: 97·2%) and 479 out of the 503 semblable wave periods of swallowing (specificity: 95·2%). In this study, the automated detection system for swallowing sounds using a nostril microphone was able to detect the swallowing event with high sensitivity and specificity even under the conditions of daily life, thus showing potential utility in the diagnosis or screening of dysphagic patients in future studies.