scholarly journals Application of Multivariate Empirical Mode Decomposition and Sample Entropy in EEG Signals via Artificial Neural Networks for Interpreting Depth of Anesthesia

Entropy ◽  
2013 ◽  
Vol 15 (12) ◽  
pp. 3325-3339 ◽  
Author(s):  
Jeng-Rung Huang ◽  
Shou-Zen Fan ◽  
Maysam Abbod ◽  
Kuo-Kuang Jen ◽  
Jeng-Fu Wu ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Empirical Mode Decomposition ◽  
Sample Entropy ◽  
Depth Of Anesthesia ◽  
Eeg Signals ◽  
Multivariate Empirical Mode Decomposition ◽  
Mode Decomposition ◽  
Artificial Neural

scholarly journals Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
George J. A. Jiang ◽  
Shou-Zen Fan ◽  
Maysam F. Abbod ◽  
Hui-Hsun Huang ◽  
Jheng-Yan Lan ◽  
...  
Keyword(s):  
Sample Entropy ◽  
Expert Assessment ◽  
Ann Model ◽  
Eeg Signals ◽  
Multivariate Empirical Mode Decomposition ◽  
Consciousness Level ◽  
Mode Decomposition ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Electroencephalogram Eeg

Electroencephalogram (EEG) signals, as it can express the human brain’s activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA). Bispectral (BIS) index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA. In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers. The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD) method and analyzed using sample entropy (SampEn) analysis. The calculated signals from SampEn are utilized to train an artificial neural network (ANN) model through using expert assessment of consciousness level (EACL) which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN. The results that are achieved using the proposed system are compared to BIS index. The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.

scholarly journals Analysis of EEG via Multivariate Empirical Mode Decomposition for Depth of Anesthesia Based on Sample Entropy

Entropy ◽  
2013 ◽  
Vol 15 (12) ◽  
pp. 3458-3470 ◽  
Author(s):  
Qin Wei ◽  
Quan Liu ◽  
Shou-Zhen Fan ◽  
Cheng-Wei Lu ◽  
Tzu-Yu Lin ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Sample Entropy ◽  
Depth Of Anesthesia ◽  
Multivariate Empirical Mode Decomposition ◽  
Mode Decomposition
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