Nonlinear electroencephalogram signal analysis method and device

An EEG signal and analysis method technology, applied in the field of preprocessing and sorting entropy analysis methods and devices, can solve the problems of inaccurate signal expression and low accuracy rate, and achieve fast calculation speed, simple concept, and anti-noise ability strong effect

Inactive Publication Date: 2012-06-13
湖州康普医疗器械科技有限公司
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Problems solved by technology

Numerous studies have confirmed that MF and SEF are closely related to brain state; however, these parameters also vary among different individuals
[0005] (3) EEG signals are time-varying and non-stationary signals. Simple time-domain or frequency-domain representations cannot accurately express signals. Only by combining time and frequency for processing can we better extract useful information from EEG signals. information
Although the application of time domain and frequency doma

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  • Nonlinear electroencephalogram signal analysis method and device
  • Nonlinear electroencephalogram signal analysis method and device
  • Nonlinear electroencephalogram signal analysis method and device

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Embodiment Construction

[0066] The present invention will be further described in detail below in conjunction with the accompanying drawings and a specific embodiment.

[0067] figure 1 It is a schematic diagram of the working process of the method of the present invention. First is step 101, collecting EEG signals. In this embodiment, EEG signals were collected from 4 rats, and the sampling frequency was 128 Hz. Figure 2A An example of EEG signals during the transition from slow wave sleep (SWS) to rapid eye movement sleep (REM). Figure 3A An example of EEG signals during the transition from rapid eye movement sleep (REM) to wakefulness (AWK).

[0068] In step 102, the collected EEG signal data is segmented and processed using the moving window technique.

[0069] In order to track changes in brain state in real time, EEG signals need to be segmented. In this embodiment, the above-mentioned EEG data is segmented, and the segment length is selected to be 10s, that is, N=1280 (sampling frequenc...

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Abstract

The invention discloses an electroencephalogram signal analysis method and an electroencephalogram signal analysis device to identify the brain state. The method comprises the following steps of: segmenting the acquired electroencephalogram signal; analyzing the state of each segment of electroencephalogram signal and preprocessing to remove interference; and calculating an ordering entropy of each segment of electroencephalogram signal, and determining the activity state of the brain according to ordering entropy values. The invention can be used for analyzing electroencephalogram signals under the conditions of different cognitive function activities of the brain and physiological statues, and can be particularly applied to studying the changes of brain activities in sleep and the like. Starting from a phase space, ordering entropies are adopted for statistical analysis of the structural change modes of the electroencephalogram signals to disclose the uncertainty, stable degree and information content of the electroencephalogram signals.

Description

technical field [0001] The invention relates to an electroencephalogram signal analysis method and device to identify brain states, in particular to a method and device for preprocessing and sorting entropy analysis of electroencephalogram sequences. Background technique [0002] EEG signals express the electrical activity of brain nerve cells, directly reflecting the electrophysiological activity of brain tissue and the functional state of the brain. Research has shown that different brain states can be identified through in-depth analysis of EEG signals. At present, the main methods of EEG signal analysis are: time-domain analysis, frequency-domain analysis, time-frequency analysis, information entropy and nonlinear dynamics. An overview is as follows: [0003] (1) The time-domain analysis method extracts features directly from the time domain, which is the earliest developed method. It is intuitive and has a relatively clear physical meaning. Therefore, there are still ...

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Application Information

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IPC IPC(8): A61B5/0476
Inventor 李小俚李段欧阳高翔
Owner 湖州康普医疗器械科技有限公司
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