生存干预期间的语音分析，为开发用于延迟检测的计算机系统提供信息。
An Analysis of Speech during Life Saving Interventions to Inform the Design of a Computerized System for Delay Detection.
机构信息
Drexel University, Philadelphia, PA, USA.
Childrens' National Hospital, Washington D.C., USA.
出版信息
AMIA Annu Symp Proc. 2023 Apr 29;2022:1217-1226. eCollection 2022.
We describe an analysis of speech during time-critical, team-based medical work and its potential to indicate process delays. We analyzed speech intention and sentence types during 39 trauma resuscitations with delays in one of three major lifesaving interventions: intravenous/intraosseous (IV/IO) line insertion, cardiopulmonary and resuscitation (CPR), and intubation. We found a significant difference in patterns of speech during delays vs. speech during non-delayed work. The speech intention during CPR delays, however, differed from the other LSIs, suggesting that context of speech must be considered. These findings will inform the design of a clinical decision support system (CDSS) that will use multiple sensor modalities to alert medical teams to delays in real time. We conclude with design implications and challenges associated with speech-based activity recognition in complex medical processes.
我们描述了对时间关键型、基于团队的医疗工作中的言语分析及其指示过程延迟的潜力。我们分析了 39 例创伤复苏过程中的言语意图和句子类型，这些过程中存在三种主要救生干预措施中的一个延迟：静脉/骨髓（IV/IO）线插入、心肺复苏（CPR）和插管。我们发现，在有延迟的情况下与在无延迟的情况下相比，言语模式有显著差异。然而，CPR 延迟期间的言语意图与其他 LSIs 不同，这表明必须考虑言语的上下文。这些发现将为临床决策支持系统（CDSS）的设计提供信息，该系统将使用多种传感器模式实时提醒医疗团队注意延迟。我们最后讨论了与复杂医疗过程中的基于言语的活动识别相关的设计影响和挑战。
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