通过可穿戴式阻抗肺成像和肺声音实现持续的呼吸阶段上下文化:可行性研究
IEEE journal of biomedical and health informatics
|September 26, 2023
概括
这项研究引入了一种可穿戴系统,用于同时测量肺声和呼吸背景,改进呼吸系统疾病和患者护理的计算机分析.
科学领域:
- 呼吸系统医学 呼吸系统医学
- 生物医学工程 生物医学工程
- 信号处理 信号处理
背景情况:
- 慢性呼吸道疾病是全球主要的健康负担.
- 肺部听觉是呼吸系统健康评估的关键.
- 目前的技术限制了计算机化肺声分析,因为它无法捕捉呼吸背景.
研究的目的:
- 开发和评估一种可穿戴系统,用于同时测量肺声和阻抗肺谱.
- 为了从阻抗肺谱信号中提取呼吸阶段上下文.
- 评估阶段上下文化声学特征的价值,以分析肺部声音.
主要方法:
- 一个可穿戴系统 (WIRS) 从10名健康志愿者同时捕获肺部声音和阻抗肺部扫描.
- 参与者进行了正常和强迫呼气的呼吸动作.
- 机器学习分析了逐阶段和逐呼吸的声学特征.
主要成果:
- 阶段上下文化的特征准确地区分了不同的呼吸类型,达到84.1 ±11.4%的F1分数.
- 阶段性功能是对性能贡献最大的因素.
- 语境化模型的表现始终优于传统的逐呼吸模型.
结论:
- 整合呼吸阶段的背景显著提高了计算机化肺声分析.
- 像WIRS这样的多式传感系统可以提高肺声分析的临床实用性.
- 这项技术有可能推进患者对呼吸系统疾病的护理.
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