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Analysis method for causal network of multi-dimensional time-sequence physiological signals

A technology of physiological signals and time series, applied in reasoning methods, medical science, medical equipment, etc.

Active Publication Date: 2021-02-23
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

However, when applied to complex processes with naturally inherited nonlinear and non-stationary properties, these decomposition procedures do not capture important features at different time scales

Method used

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  • Analysis method for causal network of multi-dimensional time-sequence physiological signals
  • Analysis method for causal network of multi-dimensional time-sequence physiological signals
  • Analysis method for causal network of multi-dimensional time-sequence physiological signals

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Embodiment Construction

[0061] The technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following description.

[0062] Such as figure 1 As shown, a causal network analysis method of multi-scale time series physiological signals, including the following steps:

[0063] S1. Input the physiological signal to be analyzed:

[0064] u 1 ={u 1,1 ,u 1,2 ,...,u 1,t}

[0065] u 2 ={u 2,1 ,u 2,2 ,...,u 2,t}

 …

[0066] u m ={u m,1 ,u m,2 ,...,u m,t}

[0067] Physiological signal u to be analyzed using NA-MEMD algorithm 1 ,u 2 ,...,u m To break it down:

[0068]

[0069] in, Indicates that the NA-MEMD algorithm is used to decompose the signal. The NA-MEMD algorithm refers to the noise-assisted multivariate empirical mode decomposition algorithm. m represents the number of input physiological signals, and satisfies m≥2, t∈N + , N + rep...

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Abstract

The invention discloses an analysis method for a causal network of multi-dimensional time-sequence physiological signals. The method comprises the following steps: S1. decomposing physiological signals, u1, u2, ..., um to be analyzed by using a NA-MEMD algorithm; S2. carrying out causal analysis on two different physiological signals ui and uj, so as to obtain a causal relationship between the twosignals, wherein i= 1, 2, ..., m, and j= 1, 2, ..., m; and S3. repeatedly executing the step S2 on any two signals of u1, u2, ..., um until causal relationships between every two signals of u1, u2, ..., um are obtained, thereby forming the causal network. According to the method, the causal network of the physiological signals can be effectively analyzed, and convenience is provided for application of the physiological signals.

Description

technical field [0001] The invention relates to physiological signal processing, in particular to a causal network analysis method of multi-scale time series physiological signals. Background technique [0002] The causal network analysis method of multi-scale time series physiological signals can be applied in brain-computer interface technology, brain function and structural mechanism research, brain-machine interaction technology (physiological network composed of brain and eyes, heart, lungs, muscles and other human organs) and promotion. [0003] Based on the neuroscience functional separation and functional integration proposed by Gall, different brain functions are localized in specialized cortical areas, so the scientific standard for assessing brain perception, cognition and behavior by functional connectivity (FC) has been established Granger causality analysis dominates. FC was used as a visual tool to show the temporal correlation of the spatial distance betwee...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/372
CPCA61B5/7235G06N5/04G16H40/63
Inventor 张羿杨琴张力夫王冠冉宇斯蒂芬·苏布兰科·塞勒徐鹏尧德中
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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