首页> 外文会议>Mediterranean conference on medical and biological engineering and computing >Can the EEG Indicate the FiO_2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure?
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Can the EEG Indicate the FiO_2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure?

机译:EEG可以在ICU患者呼吸衰竭患者中表明机械呼吸机的FIO_2流量吗?

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The aim of this paper is to show that the brain activity of patients with acute respiratory failure hospitalized in Intensive Care Units (ICUs) can provide useful medical information, which is directly related to neurological rehabilitation. It also aims to show that the entropy and kurtosis, widely used indices of the electroencephalographic (EEG) signals, are able to identify EEG changes associated with cerebral hypoxia. EEG signals were recorded from eight adult patients with acute respiratory failure admitted to the ICU. The measurements were recorded in five stages, with FiO_2 at 40%, 100%, 60%, 20% and 0% (T-piece) respectively. Total time of recordings was 50min (10 min. for each stage). The EEG signals were filtered and further cleaned from ocular and muscular artifacts as well as from the artifacts introduced by other external devices, electrodes movements and electrode's bad tangencies. Afterwards the 10-min EEG signals of each stage were segmented in ten epochs with one minute fixed length. Then Kurtosis and Shannon's Entropy were calculated in each segment. One-Way ANOVA verified the assumption that there are statistically significant differences between the various stages of our protocol, while the Scheffe Post-Hoc tests revealed the homogeneous subsets compiled by the aforementioned stage. The results suggest that the EEG is directly connected with the mechanical ventilator's changes, so in the future, clinicians could probably use the EEG as particularly useful and time-critical information, especially during the weaning procedure from the mechanical ventilator.
机译:本文的目的是表明,在重症监护单位(ICU)住院急性呼吸衰竭患者的大脑活动可以提供有用的医疗信息,与神经系统康复直接相关。它还旨在表明,熵和峰氏菌,广泛使用的脑电图(EEG)信号指数,能够识别与脑缺氧相关的EEG变化。从八名成年患者记录了EEG信号,患有ICU的急性呼吸衰竭。测量以五个阶段记录,分别以40%,100%,60%,20%和0%(T-one)的FiO_2记录。录音的总时间为50分钟(每阶段10分钟)。 eEG信号被过滤并进一步从眼部和肌肉伪影以及由其他外部装置引入的伪像,电极运动和电极的不良切线。之后,每阶段的10分钟EEG信号在十个时期分段,固定长度为1分钟。然后在每个部分计算kurtosis和shannon的熵。单向ANOVA验证了我们协议的各个阶段之间存在统计学上显着差异的假设,而Scheffe后HOC测试揭示了上述阶段编译的均匀子集。结果表明,EEG与机械通风器的变化直接连接,因此在未来,临床医生可能会使用脑电图,特别是特别有用和时间关键信息,特别是在机械通风机的断奶过程中。

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