Pain detecting and positioning method and system based on brain waves and neural network

A neural network and localization method technology, applied in the field of pain detection and localization method and system based on brain waves and neural network, can solve the problem of ignoring the inherent structure of data, achieve large expansion, improve pain recognition efficiency and pain localization accuracy , the effect of improving the accuracy

Active Publication Date: 2021-06-15
GUANGZHOU UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, this approach clearly ignores the inherent structure of the data in space, frequency, and time

Method used

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  • Pain detecting and positioning method and system based on brain waves and neural network
  • Pain detecting and positioning method and system based on brain waves and neural network
  • Pain detecting and positioning method and system based on brain waves and neural network

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Embodiment 1

[0074] Such as figure 1 As shown, this embodiment provides a pain detection and localization method based on brain waves and neural networks, including the following steps:

[0075] S1: Remove the relevant noise of the original EEG signal (EEG) through the independent component analysis algorithm (ICA), perform pain level segmentation of the EEG signal (EEG), and then use the signal time segmentation window to process the recorded EEG data, and establish Pain rating dataset;

[0076] In this embodiment, the specific steps of obtaining the brain wave pain level data set include:

[0077] S11: If figure 2 As shown in Fig. 1, filter and independent component analysis algorithm (ICA) are used to remove noises such as oculoelectricity, electrocardiogram and myoelectricity in the original EEG signal, and obtain EEG data with a high signal-to-noise ratio;

[0078] In this embodiment, filter and Independent Component Analysis (ICA) algorithm is used to filter out EEG noise, and th...

Embodiment 2

[0204] This embodiment also provides a pain detection and positioning system based on brainwaves and neural networks, including: a data preprocessing module, a brainwave sequence building module, a CNN-LSTM-AM neural network building module, and a CNN-LSTM-AM neural network training module. module, Softmax pain classifier model building block, matching and recognition module;

[0205] In this embodiment, the data preprocessing module is used to perform data preprocessing on the original EEG signal, use the independent component analysis algorithm to remove the noise of the original EEG signal, perform pain level segmentation of the EEG signal, and divide each pain level into multiple equal time window, obtain multi-channel EEG time series, and obtain the preprocessed pain data set;

[0206] In this embodiment, the brainwave sequence construction module is used to construct a multi-channel brainwave sequence, and the pain-related Theta, Alpha, and Beta frequency band time windo...

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Abstract

The invention discloses a pain detecting and positioning method and system based on brain waves and neural network, and the method comprises the steps: removing related noise of original electroencephalogram signals through independent component analysis, carrying out the pain grading of the electroencephalogram signals, carrying out the processing through a signal time division window, integrating the pain level data and then establishing a pain level data set; respectively generating spectral topographic maps of time windows of Theta, Alpha and Beta frequency bands related to pain through Fourier transform, azimuth isometric projection and a CloughTocher interpolation algorithm, and combining the spectral topographic maps into a multi-channel electroencephalogram sequence; obtaining a time-space feature vector of a brain wave sequence related to the pain degree and the pain position through a CNN-LSTM-AM neural network; and inputting the brain wave pain features learned by the CNN-LSTM-AM neural network into the pain classifier model to evaluate the pain level and the pain position. According to the invention, the pain degree change and position change characteristics of the brain waves can be accurately and efficiently extracted and processed, and the pain level and the pain position can be automatically identified.

Description

technical field [0001] The invention relates to the technical field of pain detection, in particular to a pain detection and positioning method and system based on brain waves and neural networks. Background technique [0002] Studies in recent years have shown that pain is accompanied by obvious physiological changes, which are mainly reflected in the response parameters of the autonomic nervous system, such as brain waves, heart rate, and skin electrical levels. Using the electrophysiological signals that accompany pain to measure pain level is an effective way to achieve objective pain assessment. Among pain-related electrophysiological signals, electroencephalogram (EEG) is an ideal physiological index for objectively evaluating pain. It has high time resolution of millisecond level and relatively low data acquisition cost, and directly reflects A large amount of information reflecting human physiology, psychology and diseases can be obtained through feature extraction ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/369A61B5/372
CPCA61B5/4824A61B5/7264A61B5/7267A61B5/7203
Inventor 伍冯洁麦伟健唐一晟刘庆焜向宇涵罗文俊郭子芊刘根生钟键
Owner GUANGZHOU UNIVERSITY
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