Construction and Validation of an Automatic Segmentation Method for Respiratory Sound Time Labels

作者：Jian‐Gao Fan, Haoran Ni, Xiu‐Lan Chen, Yulin Duan, Wanmin Wang, Fan Xu, Yan Shang · 发表于：The Clinical Respiratory Journal · 年份：2025 · DOI：10.1111/crj.70124 · 被引用次数：2 · 研究领域：Phonocardiography and Auscultation Techniques、Respiratory and Cough-Related Research、Voice and Speech Disorders

BACKGROUND: In the field of respiratory system diseases, the utilization of respiratory sounds in auscultation plays a crucial role in the specific disease diagnosis. However, during the process of auscultation, the personal experiences and environmental factors may affect the decision making, leading to diagnostic errors. Therefore, to accurately and effectively obtain and analyze respiratory sounds can be positively contribute to the diagnosis and treatment of respiratory system diseases. OBJECTIVES: Our aim was to develop an analytical method for the visualization and digitization of respiratory audio data, and to validate its capability to differentiate between various background diseases. METHODS: This study collected the respiratory sounds of patients admitted to the Department of General Medicine of Shanghai Changhai Hospital from June to December 2023. After strict screening according to the inclusion and exclusion criteria, a total of 84 patients were included. The research process includes using an electronic stethoscope to collect lung sounds from patients in a quiet environment. The patients expose their chests and lie flat. Sound data are collected at six landmark positions on the chest. The collected audio files are imported into an analysis tool for segmentation and feature extraction. Specific analysis methods include distinguishing heart sounds and respiratory sounds, segmenting respiratory sounds, determining the inspiratory and expiratory phases, and using ...