新的声学监测系统量化了监控麻醉护理期间的吸入风险
Yoshitaka Shimizu1, Shinichiro Ohshimo2, Noboru Saeki3
1Department of Dental Anesthesiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, 1-2-3 Kasumi, Minami-Ku, Hiroshima, 734-8553, Japan. yshimizu@hiroshima-u.ac.jp.
Scientific reports
|November 19, 2023
概括
一个新的人工智能驱动的声学系统在麻醉期间监测上呼吸道液体,可能降低吸入风险. 这项创新技术分析呼吸声以检测液体保留,提高监控麻醉护理中的患者安全.
科学领域:
- 麻醉学和呼吸系统医学
- 生物医学工程 生物医学工程
- 医疗保健中的人工智能
背景情况:
- 在监控麻醉护理 (MAC) 期间,患者的安全至关重要,特别是在牙科干预等具有高吸收风险的程序中.
- 目前的方法缺乏实时有效评估愿望风险的能力.
- 在MAC期间,上呼吸道的液体保留构成了严重的,但难以监控的威胁.
研究的目的:
- 引入和评估一种新的声学监测系统,用于在MAC期间检测上呼吸道液体保留.
- 用人工智能 (AI) 分析呼吸声来评估系统识别液体积累的能力.
- 探索这项技术在减轻吸收风险方面的潜力.
主要方法:
- 一项前性观察性研究,涉及60名参与者接受MAC的牙科治疗.
- 使用了一种原型声学监控系统来分析鼓舞人心的声音.
- 通过口内注射水来模拟液体保留,并使用AI分析注射前和后的呼吸声,以及在咳事件期间的呼吸声.
主要成果:
- 声学系统检测到Stridor定量值 (STQV) 随着口内注水而显著增加.
- 在咳的患者中,STQV在咳后立即显著增加.
- 人工智能分析将呼吸声与检测到的呼吸暂停和咳事件相关联.
结论:
- 这种新型的人工智能驱动的声学监测系统准确地评估上呼吸道液体保留率.
- 这项技术对实时风险评估和在MAC期间减轻志向有前途.
- 进一步开发可以显著提高麻醉环境中的患者安全.
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