Unlock instant, AI-driven research and patent intelligence for your innovation.
A Method for Detection of Effect Connectivity Between EEG Signals Based on Three-dimensional Nonlinear Partial Direct Coherence Function
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
A technology of connectivity detection and EEG signal, applied in the field of biomedicine, can solve the problem of inability to distinguish the direct and indirect causal relationship of signals
Active Publication Date: 2021-03-19
SOUTHEAST UNIV
View PDF5 Cites 0 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
However, the two-dimensional NPDC algorithm can only process two-dimensional signals, and cannot distinguish direct and indirect causal relationships between signals when processing multi-dimensional signals.
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
Embodiment 1
[0157] In this embodiment, an analog signal generated by an autoregressive model is taken as an example to illustrate the steps of the present invention.
[0158] Firstly, the linear and nonlinear autoregressive models are used to generate analog signal data, and the three-dimensional NPDC algorithm is used to detect the causal relationship between signals, so as to verify the effectiveness of the algorithm. In this embodiment, the three-dimensional autoregressive model shown in the following formula is used to generate simulated data:
[0159]
[0160]
[0161] Among them, e 1 (n), e 2 (n) and e 3 (n) is Gaussianwhite noise with a mean of 0 and a variance of 0.01. It can be seen that in the model represented by formula (17) (model 17 for short), the signal y 1 to y 2 , signal y 2 to y 3 and signal y 3 to y 1 There is a direct effect, while the signal y 2 to y 1 , signal y 3 to y 2 and signal y 1 to y 3 There are indirect effects. These causal relationsh...
Embodiment 2
[0172] This embodiment illustrates the steps of the present invention by taking the EEG signal of an epileptic patient as an example.
[0173]In order to explore the effect connectivity between different regions of the brain in epileptic patients, this example samples the EEG signals of epileptic patients, and selects a group of 20-channel epileptic EEG signals for research. The signal names of these 20 channels are A2, A6, A11, B1, B6, B11, C1, C4, C9, D1, D5, F2, F8, H2, I2, P1, P4, P8, T1 and T8. In this embodiment, the signals P8, A2 and I2 are selected from the signals of the 20 channels to form an EEG signal model, corresponding to the signal y 1 、y 2 and y 3 , in order to explore the interaction relationship between EEG signals.
[0174] The total length of the sampled data of the EEG signal is 18432, and the sampling frequency is 256 Hz, that is, the total sampling time is 72 seconds. Among them, 0-20 seconds is the EEG signal of pre-epileptic seizure, 21-52 second...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
PUM
Login to View More
Abstract
The invention discloses an EEG signal inter-effect connectivity detection method based on a three-dimensional nonlinear partial direct coherence function, comprising the following steps: (1) constructing a single-input multi-output nonlinear autoregressive model; (2) applying the FROLS algorithm to estimate the coefficients of the model constructed in the step (1); (3) Formally transforming the three-dimensional PDS to obtain the PDC definition of the signal yi to yj described by the frequency response function; (4) carrying out frequency domain analysis of SIMO NARX model by using the multidimensional Fourier transform of Volterra series kernel function, and the nonlinear frequency response function is calculated. (5) substituting the nonlinear frequency response function calculated in the step (4) into the PDC definition in the step (3) to obtain the three-dimensional NPDC, and obtaining the causal effect of one signal on the other signal under the condition that the three-dimensional signal is taken into account at the same time. This method can detect the causality of three-dimensional EEG signals.
Description
technical field [0001] The present invention belongs to the field of biomedicine, and in particular relates to a method for detecting the effect connectivity between electroencephalogram signals. Background technique [0002] Effectorconnectivity between signals in different regions of the brain plays an important role in identifying focal regions. Current detection of effect connectivity among EEG signals includes time-domain analysis and frequency-domain analysis. PDC (Partial Directed Coherence, partial direct coherence function) is a commonly used method for analyzing the causal relationship between signals in the frequency domain. This method can identify the direct or indirect causal relationship between two signals. However, this method is based on a linear model, and the real EEG (Electro Encephalo Graph, electroencephalogram) has nonlinear characteristics, and the PDC algorithm cannot fully detect the nonlinear causal relationship in the signal. NPDC (Nonlinear P...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to View More 
Login to View More