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This study presents a new method to apply the interval second-order difference plot (ISODP) and interval permutation entropy (IPE) techniques to assess the depth of anaesthesia (DoA). First, the denoised electroencephalograph signals are decomposed into 13 different frequency bands. The second-order difference plot (SODP) and permutation entropy (PE) values of each frequency band are calculated. The...
This study proposes a novel index MLDoA to identify different anaesthetic states of a patient during surgery. Based on the new index MLDoA, the assessment of depth of anaesthesia (DoA) for a patient can be clearly monitored. Firstly, a modified Bayesian wavelet threshold is proposed to de-noise the electroencephalogram (EEG) signals. Secondly, the Hurst exponent is obtained to classify four states...
Electroencephalogram (EEG) signals are often contaminated with artifacts such as electromyography (EMG), eye blink and eye ball movement. These contaminated EEG signals may give incorrect values of Bispectral Index. If fixed band-pass filter is used to filter the overlapping signals between the EEG and the artifacts, the useful information in EEG signal could be lost. This paper proposes a method...
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