Impedance-Based Ventilation Detection and Signal Quality Control During Out-of-Hospital Cardiopulmonary Resuscitation.
Impedance-Based Ventilation Detection and Signal Quality Control During Out-of-Hospital Cardiopulmonary Resuscitation.
复制标题
院外心肺复苏期间基于阻抗的通气检测和信号质量控制。
DOI：
10.1109/jbhi.2023.3253780
复制
发表时间：
2023
影响因子：
7.7
通讯作者：
Idris,AhamedH
中科院分区：
文献类型：
--
作者：
Jaureguibeitia,Xabier;Aramendi,Elisabete;Wang,HenryE;Idris,AhamedH
对通气的反馈可以帮助提高心肺复苏质量和院外心脏骤停（OHCA）的生存率。然而，目前在OHCA期间监测通气的技术非常有限。胸阻抗（TI）对肺中的空气体积变化敏感，允许识别通气，但会受到胸外按压和电极运动引起的伪影的影响。本研究介绍了一种新的算法，以确定在连续胸外按压在OHCA的TI通气。纳入了367例OHCA患者的数据，提取了2551个1分钟TI段。同时使用二氧化碳监测数据注释20724次真实通气，用于培训和评估。对每个TI段应用三步程序：首先，应用双向静态和自适应滤波器以去除压缩伪影。然后，波动可能由于通风的位置和特点。最后，一个递归神经网络被用来区分从其他虚假的波动通风。还开发了一个质量控制阶段，以预测通风检测可能受到影响的部分。该算法使用5倍交叉验证进行训练和测试，并且在研究数据集上优于文献中以前的解决方案。每节段和每例患者的F评分中位数（四分位距，IQR）分别为89.1（70.8-99.6）和84.1（69.0-93.9）。质量控制阶段确定了最低绩效的细分市场。对于质量评分最高的50%节段，每节段和每例患者的F评分中位数分别为100.0（90.9-100.0）和94.3（86.5-97.8）。所提出的算法可以在OHCA中连续手动CPR的具有挑战性的场景中允许可靠的、质量调节的通气反馈。
Feedback on ventilation could help improve cardiopulmonary resuscitation quality and survival from out-of-hospital cardiac arrest (OHCA). However, current technology that monitors ventilation during OHCA is very limited. Thoracic impedance (TI) is sensitive to air volume changes in the lungs, allowing ventilations to be identified, but is affected by artifacts due to chest compressions and electrode motion. This study introduces a novel algorithm to identify ventilations in TI during continuous chest compressions in OHCA. Data from 367 OHCA patients were included, and 2551 one-minute TI segments were extracted. Concurrent capnography data were used to annotate 20724 ground truth ventilations for training and evaluation. A three-step procedure was applied to each TI segment: First, bidirectional static and adaptive filters were applied to remove compression artifacts. Then, fluctuations potentially due to ventilations were located and characterized. Finally, a recurrent neural network was used to discriminate ventilations from other spurious fluctuations. A quality control stage was also developed to anticipate segments where ventilation detection could be compromised. The algorithm was trained and tested using 5-fold cross-validation, and outperformed previous solutions in the literature on the study dataset. The median (interquartile range, IQR) per-segment and per-patient F-scores were 89.1 (70.8–99.6) and 84.1 (69.0–93.9), respectively. The quality control stage identified most low performance segments. For the 50% of segments with highest quality scores, the median per-segment and per-patient F-scores were 100.0 (90.9–100.0) and 94.3 (86.5–97.8). The proposed algorithm could allow reliable, quality-conditioned feedback on ventilation in the challenging scenario of continuous manual CPR in OHCA.