A Novel Real-time Depth of Anaesthesia Monitoring Method using Detrended Fluctuation Analysis and ANN
Paper
Paper/Presentation Title | A Novel Real-time Depth of Anaesthesia Monitoring Method using Detrended Fluctuation Analysis and ANN |
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Presentation Type | Paper |
Authors | Chen, Xing (Author) and Wen, Paul (Author) |
Journal or Proceedings Title | ICBIP '20: Proceedings of the 2020 5th International Conference on Biomedical Signal and Image Processing |
Number of Pages | 7 |
Year | 2020 |
Place of Publication | New York, United States |
ISBN | 9781450387767 |
Digital Object Identifier (DOI) | https://doi.org/10.1145/3417519.3419403 |
Web Address (URL) of Paper | https://dl.acm.org/doi/10.1145/3417519.3419403 |
Conference/Event | 2020 5th International Conference on Biomedical Signal and Image Processing (ICBIP 2020) |
Event Details | 2020 5th International Conference on Biomedical Signal and Image Processing (ICBIP 2020) Event Date 21 to end of 23 Aug 2020 Event Location Suzhou, China |
Abstract | In this paper, Detrended Fluctuation Analysis (DFA) method and artificial neural network (ANN) were applied to investigate the EEG variation during anesthesia. Rather than quantifying the loss of consciousness with a single feature, self-similarity, several cross-fluctuations from two channel raw EEG data using specific window sizes were extracted and combined to classify the patient anaesthesia state. The proposed method is evaluated using off-line data and the results are compared with the most widely used Bispectral (BIS) Index. In addition, the proposed method had reduced the calculation complexity for the real time implementation. |
Keywords | Anaesthesia; artificial neural network; Detrended Fluctuation Analysis; EEG |
ANZSRC Field of Research 2020 | 460299. Artificial intelligence not elsewhere classified |
400399. Biomedical engineering not elsewhere classified | |
Byline Affiliations | School of Mechanical and Electrical Engineering |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q6660/a-novel-real-time-depth-of-anaesthesia-monitoring-method-using-detrended-fluctuation-analysis-and-ann
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