【摘要】 吞咽障碍在老年群体中发病率高，若未能及时识别与干预，易引发误吸、营养不良及肺部感染等严重并发症。近年来，基于声学特征的吞咽功能评估因其非侵入性、可操作性强及适用于远程监测等优势，受到广泛关注。然而，现有研究普遍存在样本量小、音频类型单一、采集与处理标准不统一等问题，制约了声学技术在吞咽障碍识别中的深入应用。本研究在北京市和石家庄市13家养老机构中招募650名受试者，纳入635名合格受试者，共采集7 922条涵盖吞咽音、咳嗽音与语音的有效音频。每条音频提取23个声学特征，涵盖时域、频域、能量及非线性4个维度，共提取182 206个声学特征。基于波形图、时频图与频谱图分析，初步验证了不同音频事件在多维度声学特征上的显著差异。最终，本研究开发了一套标准化的吞咽声学数据采集与处理流程，构建了覆盖多类型音频事件与多维度声学特征的吞咽声学数据库，为后续声学标志物识别、智能识别模型构建、远程吞咽功能评估系统开发等提供了数据支撑，具有重要科研价值与广阔应用前景。更多还原

【Abstract】 Dysphagia is common among elderly people and may lead to aspiration,malnutrition,and pulmonary infections if not properly managed. Acoustic-based assessment offers a non-invasive,practical,and remotely applicable approach,yet current research is limited by small sample sizes and a lack of standardized data protocols. This study recruited 650 older adults from 13 care institutions in Beijing and Shijiazhuang,with 635 completing valid audio tasks. A total of 7 922 high-quality recordings were collected,including swallowing,coughing,and speech sounds. From each audio clip,23 acoustic features across time,frequency,energy,and nonlinear domains were extracted,yielding 182 206 feature data points. Waveform,spectrogram,and time-frequency analyses confirmed significant differences across sound types,highlighting the discriminative value of acoustic features. A standardized workflow for audio collection,processing,and feature extraction was developed,resulting in a comprehensive swallowing acoustic database. This database provides essential support for recognizing acoustic biomarkers,building AI-driven identification models and advancing remote dysphagia assessment. It has significant scientific research value and broad application prospects.更多还原