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EEG real-time interaction analysis system and real-time interaction analysis method based on web visualization platform

A real-time interaction and analysis method technology, applied in the field of EEG signal analysis, can solve the problems of high equipment prices, single visualization results, low efficiency of EEG signal offline analysis, etc., to achieve the effect of improving efficiency and saving costs

Pending Publication Date: 2021-08-24
TIANJIN UNIV OF TECH & EDUCATION TEACHER DEV CENT OF CHINA VOCATIONAL TRAINING & GUIDANCE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a real-time interactive analysis system for EEG based on a web visualization platform in view of the problems in the prior art that the offline analysis efficiency of EEG signals is low, the required equipment is expensive, and the visualization results are single

Method used

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  • EEG real-time interaction analysis system and real-time interaction analysis method based on web visualization platform
  • EEG real-time interaction analysis system and real-time interaction analysis method based on web visualization platform
  • EEG real-time interaction analysis system and real-time interaction analysis method based on web visualization platform

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Embodiment 1

[0037] An EEG real-time interactive analysis system based on a web visualization platform, including a cloud server and a web visualization analysis module, wherein:

[0038] The cloud server includes a service port for receiving the Internet transmission request of the EEG signal acquisition device, a data preprocessing module for performing abnormal value filtering and low-pass filtering on the EEG signal data, a database for storing processed data, A server-side module for performing basic statistical feature extraction and advanced feature extraction on the EEG time series in the database;

[0039] The web visualization analysis module is used for monitoring data collection and data characteristics, and using icons to visualize them.

[0040] The web visualization analysis module is the front-end module, which is loaded and used in the browser. The cloud server is the back-end module. The transmission request of the EEG signal acquisition device is transmitted by the Inter...

Embodiment 2

[0042] An EEG real-time interactive analysis method based on a web visualization platform, comprising the following steps:

[0043] Step 1, the cloud server receives the EEG signal transmitted by the EEG signal acquisition device;

[0044] Step 2, the data preprocessing module filters the abnormal values ​​in the EEG signal data, and then performs low-pass filtering processing, and then stores the processed data in the database;

[0045] Step 3, the server-side module performs basic statistical feature extraction and custom advanced feature extraction on the processed data (EEG time series) in the database;

[0046] Step 4, the web visualization analysis module monitors and visualizes the data collection and data characteristics.

Embodiment 3

[0048] In embodiment 1 or embodiment 2, the cloud server processes the request for Internet transmission of the signal acquisition device through port 8080, and the request for Internet transmission is carried out through the post mode in the http protocol, and the time series data of this period of time is sent every minute Convert it to json format, and then upload it to the cloud server by post. The transmission request of the intelligent collection device is transmitted by the Internet through 4G or wifi.

[0049] In the data preprocessing module of embodiment 1 or step 2 of embodiment 2, when filtering outliers, take 5 times of the median of the overall signal as the threshold value, and the signal points exceeding the threshold value are filtered out, and during low-pass filter processing, The low-pass filter input-output relationship satisfies the following differential equation, V in (t) is the input signal, dV out (t) is the output signal, τ=20ms

[0050]

[0051]...

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Abstract

The invention discloses an EEG real-time interaction analysis system and real-time interaction analysis method based on a web visualization platform, and the analysis method comprises the following steps: 1, receiving an EEG signal transmitted by an EEG signal collection device through a cloud server; 2, enabling a data preprocessing module to filter abnormal values in the electroencephalogram signal data, then carrying out low-pass filtering processing, and storing the processed data into a database; step 3, performing basic statistical feature extraction and user-defined advanced feature extraction on the EEG time sequence in the database by the server side module; and step 4, enabling a web visualization analysis module to monitor and visualize the data acquisition condition and the data feature condition. Research or experimenters can analyze data conditions and EEG feature conditions in real time, so that doctors or experimenters can know information acquisition conditions and adjust acquisition schemes in real time through low-cost equipment, and meanwhile, effective cloud management is performed on EEG information.

Description

technical field [0001] The invention relates to the technical field of EEG signal analysis, in particular to an EEG real-time interactive analysis system and real-time interactive analysis method based on a web visualization platform. Background technique [0002] EEG signal is an effective detection method of brain activity, which can be used to evaluate activities such as diseases of the human nervous system, and can also be used as a method of brain-computer interface. Traditional EEG analysis has the following three problems: [0003] First, the current EEG signal analysis is mostly based on offline analysis and prediction of long-term signals. The timeliness is not good. After collecting data for a certain period of time, it is performed offline, which is inefficient and time-consuming, and may easily lead to invalid data collection. In addition, deploying the offline model on the local system will make it difficult to update the model. [0004] Second, the current EE...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/904G06K9/00G06F3/01
CPCG06F16/904G06F3/015G06F2218/08
Inventor 秦迎梅门聪车艳秋韩春晓
Owner TIANJIN UNIV OF TECH & EDUCATION TEACHER DEV CENT OF CHINA VOCATIONAL TRAINING & GUIDANCE
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