标题： 呼吸作为生物标志物：呼吸道监测中接触式和非接触式应用与方法的综述 显示英文标题

标题： Breath as a biomarker: A survey of contact and contactless applications and approaches in respiratory monitoring

摘要： 呼吸分析已成为健康监测中的关键工具，提供了关于呼吸功能、疾病检测和持续健康评估的见解。 虽然传统的接触式方法是可靠的，但它们在舒适性和实用性方面往往存在挑战，尤其是在长期监测中。 本综述全面考察了接触式和非接触式方法，强调了机器学习和深度学习技术在呼吸分析中的最新进展。 非接触式方法，包括Wi-Fi信道状态信息和声学传感，被分析其提供准确、无创呼吸监测的能力。 我们探讨了广泛的应用，从单用户呼吸频率检测到多用户场景、用户识别和呼吸系统疾病检测。 此外，本综述详细介绍了必要的数据预处理、特征提取和分类技术，提供了对适用于每种方法的机器学习/深度学习模型的比较见解。 关键挑战如数据集稀缺性、多用户干扰和数据隐私也进行了讨论，并介绍了可解释人工智能、联邦学习、迁移学习和混合建模等新兴趋势。 通过综合当前的方法并确定开放的研究方向，本综述提供了一个全面的框架，以指导呼吸分析领域的未来创新，将先进的技术能力与实际的医疗应用相结合。 显示英文摘要

摘要： Breath analysis has emerged as a critical tool in health monitoring, offering insights into respiratory function, disease detection, and continuous health assessment. While traditional contact-based methods are reliable, they often pose challenges in comfort and practicality, particularly for long-term monitoring. This survey comprehensively examines contact-based and contactless approaches, emphasizing recent advances in machine learning and deep learning techniques applied to breath analysis. Contactless methods, including Wi-Fi Channel State Information and acoustic sensing, are analyzed for their ability to provide accurate, noninvasive respiratory monitoring. We explore a broad range of applications, from single-user respiratory rate detection to multi-user scenarios, user identification, and respiratory disease detection. Furthermore, this survey details essential data preprocessing, feature extraction, and classification techniques, offering comparative insights into machine learning/deep learning models suited to each approach. Key challenges like dataset scarcity, multi-user interference, and data privacy are also discussed, along with emerging trends like Explainable AI, federated learning, transfer learning, and hybrid modeling. By synthesizing current methodologies and identifying open research directions, this survey offers a comprehensive framework to guide future innovations in breath analysis, bridging advanced technological capabilities with practical healthcare applications.