Real‐time assessment of swallowing sound using an electronic stethoscope and an artificial intelligence system

• Main Authors: Kazuma Suzuki (Author), Yoshitaka Shimizu (Author), Shinichiro Ohshimo (Author), Kana Oue (Author), Noboru Saeki (Author), Takuma Sadamori (Author), Yasuo Tsutsumi (Author), Masahiro Irifune (Author), Nobuaki Shime (Author)
• Format: Book
• Published: Wiley, 2022-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2057-4347; 10.1002/cre2.531
• Keywords: AI; cervical auscultation; deglutition; dysphagia; electronic stethoscope; Dentistry; RK1-715
• Source: Clinical and Experimental Dental Research, Vol 8, Iss 1, Pp 225-230 (2022)

Abstract Objectives Daily assessments of swallowing function and interventions such as rehabilitation and dietary adjustments are necessary to improve dysphagia. Cervical auscultation is convenient for health care providers for assessing swallowing ability. Although this method allows for swallowing sound evaluations, sensory evaluations with this method are difficult. Thus, we aimed to assess swallowing sound by the combined use of an electronic stethoscope and an artificial intelligence (AI) system that incorporates sound recognition. Material and Methods Herein, 20 fifth‐year dentistry student volunteers were included; each participant was drank 10 ml and then 20 ml of water in different positions (sitting and supine). We developed an algorithm for indexing bolus inflow sounds using AI, which compared the swallowing sounds and created a new index. Results The new index value used for swallowing sound was significantly higher in men than in women and in the sitting position than in the supine position. A software for acoustic analysis confirmed that the swallowing index was significantly higher in men than in women as well as in the sitting position than in the supine position. These results were similar to those obtained using the new index. However, the new index substantially differed between sexes in terms of posture compared with effective sound pressure. Conclusions We developed a new algorithm for indexing swallowing sounds using a stethoscope and an AI system, which could identify swallowing sounds. For future research and development, evaluations of patients with dysphagia are necessary to determine the efficacy of the new index for bedside screening of swallowing conditions.