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A causal network method for fatigue state based on multi-source data information

A fatigue state, causal network technology, applied in medical science, diagnosis, diagnostic recording/measurement, etc., to achieve the effects of high precision, improved analysis accuracy, and high application value

Active Publication Date: 2022-07-22
CAPITAL NORMAL UNIVERSITY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to provide a fatigue state causal network method based on multi-source data information, to overcome the defects of the above-mentioned machine learning method, and apply the Granger causality analysis method to analyze various physiological indicators that affect the fatigue state of the human body

Method used

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  • A causal network method for fatigue state based on multi-source data information
  • A causal network method for fatigue state based on multi-source data information
  • A causal network method for fatigue state based on multi-source data information

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Embodiment Construction

[0030] The present invention will be clearly and completely described below with reference to the embodiments and the accompanying drawings. Obviously, the described embodiments are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0031] In the present invention, descriptions involving "first", "second", etc. are only for descriptive purposes, and should not be understood as indicating or implying their relative importance or implying the number of indicated technical features.

[0032] Please refer to figure 1 , figure 1 It is a flow chart of the implementation of the method of the present invention.

[0033] Step S1, use K4b 2 The cardiopulmonary function tester collected the respiratory data of 9 subjects, and the heart rate data of the subjects was...

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Abstract

The invention discloses a fatigue state causal network method based on multi-source data information. The steps are as follows: 1. Collect respiratory and heart rate data related to the fatigue state of the human body; 2. For each item of physiological data, use an extrapolation fitting method to remove outliers; 3. Choose two items of physiological data to test the two data Whether there is a correlation between them; 4. For the two physiological data with a correlation, use the Granger causal analysis method to test whether there is a causal relationship between the two; 6. After traversing all physiological data, establish a causal relationship network between variables. The method of the invention has the advantages of high precision, small calculation amount, strong compatibility and the like. It can be used for causal analysis and detection of fatigue state of workers in vehicles, ships, and aircraft, and improves the accuracy of causal analysis of fatigue state based on multi-source data information fusion, which has high application value.

Description

technical field [0001] The invention relates to a fatigue state causal network method based on multi-source data information, which can be used for the fatigue state causal analysis and detection of vehicle, ship, aircraft and other carrier workers, and improves the fatigue state causal analysis accuracy rate based on multi-source data information fusion . Background technique [0002] When working in a special environment, some physiological index values ​​of people will change, and the changes in these physiological data may lead to the occurrence of certain physiological diseases. For example, working in a closed environment for a long time may be more prone to fatigue and depression. Fatigue state is an early warning of some physiological sub-health state, so it is of great significance to study people's fatigue state in special working environment, which will help to predict people's health state so as to reasonably improve their working conditions. [0003] The machi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/18A61B5/0205A61B5/33
CPCA61B5/18A61B5/0205A61B5/7271A61B5/318
Inventor 任长娥袁超杜涛王岩
Owner CAPITAL NORMAL UNIVERSITY
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