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Sleep state monitoring method based on GM-GP algorithm

A sleep state and algorithm technology, which is applied in the cross-field of signal and information processing and neurobiology, can solve the problems of reducing computing time, long computing time, slow computing speed, etc., and achieve high computing efficiency and improved computing efficiency

Active Publication Date: 2017-05-17
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

However, the calculation speed of this method is slow, and real-time monitoring of sleep status cannot be realized.
[0004] Gray System Theory (Grey System Theory) is a method for extracting less data information, so it is suitable for modeling chaotic signals with less data, and then calculating its correlation dimension. This method makes full use of the nonlinearity of EEG signals characteristics, this patent combines gray modeling and correlation dimension to propose a GM-GP algorithm, which overcomes the shortcoming of long calculation time and effectively reduces the calculation time

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  • Sleep state monitoring method based on GM-GP algorithm
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Embodiment Construction

[0019] The specific implementation manner of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0020] The flow process of the GM-GP algorithm that the present invention proposes is as figure 1 As shown, below in conjunction with the accompanying drawings, the specific implementation of the present invention will be described in detail.

[0021] 1. Preprocessing the original EEG, including: upgrading the EEG data to facilitate gray modeling of the data; accumulating and generating the original data to form an accumulative generation sequence;

[0022] Let X (0) =(x (0) (1),x (0) (2),...,x (0) (n)), and its one-time cumulative generation sequence is X (1) =(x (1) (1),x (1) (2),...,x (1) (n)), that is, the two satisfy the relationship:

[0023]

[0024] Among them, X (0) =(x (0) (1),x (0) (2),...,x (0) (n)) is the time series of EEG signals. x (1) Generate series for order 1 accumulation of time series. It ...

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Abstract

The invention discloses a sleep state monitoring method based on a GM-GP algorithm which combines grey theories with nonlinear dynamics. The method comprises the steps that (1)an original EEG is pre-processed by a data lifting method (coordinate translation), accumulative generation is conducted, and a GM (1,1) grey model is established; (2) the GM (1,1) model is used to extract characteristics and solve a corresponding parameter b; (3) embedding dimensions and delay time of a GP algorithm are determined aiming at the grey model parameter b; (4) phase-space reconstruction of the parameter b is conducted, and an accumulated distribution integral is computed; and (5) a corresponding correlation dimension is solved through linear fitting, so a sleep state can be determined. According to the invention, through combination of grey modeling and the GP algorithm, brain function states can be analyzed effectively, and the sleep state can be monitored in real time.

Description

technical field [0001] The invention relates to the cross field of signal and information processing and neurobiology, in particular to a method combining gray modeling-based electroencephalogram (electroencephalogram, EEG) and GP algorithm. It proposes and designs an algorithm combining gray modeling and GP algorithm (GM-GP). Due to the low computational efficiency when performing correlation dimension calculations on EEG signals, an algorithm that remains robust with less data is needed, and the gray system theory is a theory for information extraction with less data. The present invention is a method of combining the two. Background technique [0002] EEG signal, as a kind of nonlinear and complex signal, is generally considered to be generated by nonlinear dynamic process. Compared with the traditional linear analysis method, the nonlinear dynamic analysis method is more ideal for nonlinear signal analysis such as EEG. The correlation dimension is a parameter that des...

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Application Information

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IPC IPC(8): G06F19/00
CPCG16H50/50
Inventor 谢松云李亚兵段绪王伟冯怀北
Owner NORTHWESTERN POLYTECHNICAL UNIV