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Anesthesia monitoring method based on electroencephalograph composite permutation entropy index

A technology of permutation entropy and EEG, applied in diagnostic recording/measurement, medical science, sensors, etc., can solve problems such as high computational complexity

Inactive Publication Date: 2012-11-14
刘铭湖 +2
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Problems solved by technology

It's just that the computational complexity is too large

Method used

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  • Anesthesia monitoring method based on electroencephalograph composite permutation entropy index
  • Anesthesia monitoring method based on electroencephalograph composite permutation entropy index
  • Anesthesia monitoring method based on electroencephalograph composite permutation entropy index

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Embodiment Construction

[0020] In this embodiment, EEG data of a patient under anesthesia are used, and the sampling rate is 256 Hz.

[0021] Step 1. Set parameters, so that τ=0;

[0022] Step 2. Let τ=τ+1, according to figure 2 The method shown, segmenting the signal into sequences of motifs;

[0023] Step 3. Compare image 3 Divide all the motifs into 13 categories, and pay attention to the influence of noise;

[0024] Step 4. Calculate the number of motifs contained in each type of motif, and divide by the total number of motifs to obtain the frequency of this type of motif, which is used as the probability of occurrence of the motif;

[0025] Step 5. Use the formula H=-∑p i ×1n(p i ) and the probability distribution of the motif to calculate the information entropy of the motif, and judge whether the value of τ is 3, if it is not 3, then turn to step 2, if it is 3, then turn to step 6;

[0026] Step 6. Utilize the formula Computes the composite permutation entropy index.

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Abstract

The invention belongs to a monitoring method of anesthesia depth. The method includes initialization of parameters, motif segmentation and recognition, determining motif probability and calculating an information entropy and a composite permutation entropy. According to the method, motifs are skillfully divided into 13 types according to the size relations among three points, simultaneously a threshold value is introduced to control the influence of noises on the motif recognition, then an occurrence frequency of each motif is used as an occurrence probability of each motif to calculate the information entropy, and then the composite permutation entropy is figured out. The composite permutation entropy is an ultimate anesthesia depth index. By means of the method, the computation complexity is effectively reduced, the instantaneity of an anesthesia monitoring technology is improved, and the method can be definitely applied to the engineering.

Description

technical field [0001] The invention belongs to the field of anesthesia monitoring, and the specific content is a method for realizing the monitoring of anesthesia depth by using electroencephalogram signals. Background technique [0002] At present, the research of EEG signal in detecting the depth of anesthesia has achieved good research results. The anesthesia depth monitoring methods based on EEG signals mainly include: bispectral index, anesthesia trend, artificial neural network method, complexity and wavelet analysis, etc. [0003] (1) Bispectral index (BIS) is an EEG quantitative analysis index that includes three characteristics of time domain, frequency domain and high-order spectral variables. Through a specific nonlinear algorithm, four different The EEG parameters of EEG, that is, the burst suppression rate, "QUAI", the ratio and the relative synchronization of fast and slow waves, are integrated into a dimensionless number of 100-0, which is used to represent ...

Claims

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Application Information

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IPC IPC(8): A61B5/0476
Inventor 刘铭湖杨伟伟周博
Owner 刘铭湖
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