Anesthesia assessment based on ICA permutation entropy analysis of two-channel EEG signals
Paper
Paper/Presentation Title | Anesthesia assessment based on ICA permutation entropy analysis of two-channel EEG signals |
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Presentation Type | Paper |
Authors | Li, Tianning (Author), Sivakumar, Prashanth (Author) and Tao, Xiaohui (Author) |
Editors | Liang, Peipeng, Goel, Vinod and Shan, Chunlei |
Journal or Proceedings Title | Lecture Notes in Computer Science (Book series) |
Journal Citation | 11976, pp. 244-253 |
Number of Pages | 10 |
Year | 2019 |
Publisher | Springer |
Place of Publication | Switzerland |
ISSN | 1611-3349 |
0302-9743 | |
ISBN | 9783030370770 |
9783030370787 | |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-030-37078-7_24 |
Web Address (URL) of Paper | https://link.springer.com/chapter/10.1007/978-3-030-37078-7_24 |
Web Address (URL) of Conference Proceedings | https://link.springer.com/book/10.1007/978-3-030-37078-7 |
Conference/Event | 12th International Conference on Brain Informatics (BI 2019) |
Event Details | 12th International Conference on Brain Informatics (BI 2019) Parent International Conference on Brain Informatics (BI) Delivery In person Event Date 13 to end of 15 Dec 2019 Event Location Haikou, China Event Web Address (URL) |
Abstract | Inaccurate assessment may lead to inaccurate levels of dosage given to the patients that may lead to intraoperative awareness that is caused by under dosage during surgery or prolonged recovery in patients that is caused by over dosage after the surgery is done. Previous research and evidence show that assessing anesthetic levels with the help of electroencephalography (EEG) signals gives an overall better aspect of the patient’s anesthetic state. This paper presents a new method to assess the depth of anesthesia (DoA) using Independent Component Analysis (ICA) and permutation entropy analysis. ICA is performed on two-channel EEG to reduce the noise then Wavelet and permutation entropy are applied on these channels to extract the features. A linear regression model was used to build the new DoA index using the selected features. The new index designed by proposed methods performs well under low signal quality and it was overall consistent in most of the cases where Bispectral index (BIS) may fail to provide any valid value. |
Keywords | depth of anesthesia, electroencephalograph, independent component analysis, permutation entropy |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 400607. Signal processing |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | School of Sciences |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q59x8/anesthesia-assessment-based-on-ica-permutation-entropy-analysis-of-two-channel-eeg-signals
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