Can the EEG Indicate the FiO2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure?

E G Peranonti, M A Klados, C L Papadelis, D G Kontotasiou, C Kourtidou-Papadeli, P D Bamidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 FiO2 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.
LanguageEnglish
Title of host publicationXII Mediterranean Conference on Medical and Biological Engineering and Computing 2010
PublisherSpringer
Pages827-830
Number of pages4
ISBN (Electronic)978-3-642-13039-7
ISBN (Print)978-3-642-13038-0
DOIs
Publication statusPublished - 2010

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Entropy
Mechanical Ventilators
Respiratory Insufficiency
Artifacts
Intensive Care Units
Electrodes
Ventilator Weaning
Brain Hypoxia
Analysis of Variance
Equipment and Supplies
Brain
Neurological Rehabilitation

Keywords

  • eeg
  • entropy
  • icu
  • kurtosis
  • respiratory

Cite this

Peranonti, E. G., Klados, M. A., Papadelis, C. L., Kontotasiou, D. G., Kourtidou-Papadeli, C., & Bamidis, P. D. (2010). Can the EEG Indicate the FiO2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure? In XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010 (pp. 827-830). Springer. https://doi.org/10.1007/978-3-642-13039-7_209
Peranonti, E G ; Klados, M A ; Papadelis, C L ; Kontotasiou, D G ; Kourtidou-Papadeli, C ; Bamidis, P D. / Can the EEG Indicate the FiO2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure?. XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010. Springer, 2010. pp. 827-830
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Peranonti, EG, Klados, MA, Papadelis, CL, Kontotasiou, DG, Kourtidou-Papadeli, C & Bamidis, PD 2010, Can the EEG Indicate the FiO2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure? in XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010. Springer, pp. 827-830. https://doi.org/10.1007/978-3-642-13039-7_209

Can the EEG Indicate the FiO2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure? / Peranonti, E G; Klados, M A; Papadelis, C L; Kontotasiou, D G; Kourtidou-Papadeli, C; Bamidis, P D.

XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010. Springer, 2010. p. 827-830.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Can the EEG Indicate the FiO2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure?

AU - Peranonti, E G

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N2 - 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 FiO2 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.

AB - 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 FiO2 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.

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M3 - Conference contribution

SN - 978-3-642-13038-0

SP - 827

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BT - XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010

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Peranonti EG, Klados MA, Papadelis CL, Kontotasiou DG, Kourtidou-Papadeli C, Bamidis PD. Can the EEG Indicate the FiO2 Flow of a Mechanical Ventilator in ICU Patients with Respiratory Failure? In XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010. Springer. 2010. p. 827-830 https://doi.org/10.1007/978-3-642-13039-7_209