Evolution of the Stethoscope: Advances with the Adoption of Machine Learning and Development of Wearable Devices
- Author:
Yoonjoo KIM
1
;
YunKyong HYON
;
Seong‑Dae WOO
;
Sunju LEE
;
Song-I LEE
;
Taeyoung HA
;
Chaeuk CHUNG
Author Information
- Publication Type:Review
- From:Tuberculosis and Respiratory Diseases 2023;86(4):251-263
- CountryRepublic of Korea
- Language:English
- Abstract: The stethoscope has long been used for the examination of patients, but the importance of auscultation has declined due to its several limitations and the development of other diagnostic tools. However, auscultation is still recognized as a primary diagnostic device because it is non-invasive and provides valuable information in real-time. To supplement the limitations of existing stethoscopes, digital stethoscopes with machine learning (ML) algorithms have been developed. Thus, now we can record and share respiratory sounds and artificial intelligence (AI)-assisted auscultation using ML algorithms distinguishes the type of sounds. Recently, the demands for remote care and non-face-to-face treatment diseases requiring isolation such as coronavirus disease 2019 (COVID-19) infection increased. To address these problems, wireless and wearable stethoscopes are being developed with the advances in battery technology and integrated sensors. This review provides the history of the stethoscope and classification of respiratory sounds, describes ML algorithms, and introduces new auscultation methods based on AI-assisted analysis and wireless or wearable stethoscopes.
